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Each time I read about a crypto hack on the internet, I usually heave a sigh of disappointment. I always ask myself whether there will ever be an end to the alarming rate of cyber attacks on blockchain protocols. For every crypto hack that has occurred, it feels like the cryptocurrency industry has taken ten steps backward, undermining its progress and worsening the industry’s image problem. Apparently, crypto hacks happen not because there are no effective cyber security measures in place but because they are either not enough or they are currently outpaced. Developing a superior cybersecurity technology must be seen as a race to beat hackers to their own game, and further improvements are required to match their tactics for tactics, so much so that cybersecurity technologies must be ten steps ahead of cyber threats. In this article, I will be delving into the efficacy of smart contract audits, highlighting the significance of a routine audit and the convergence of various approaches that are tailored towards a safer blockchain ecosystem. What Are Smart Contracts? Smart contracts are pieces of self-executing computer programs on a blockchain. They are designed to function when a particular set of conditions are fulfilled (i.e., minting an NFT), and the ultimate purpose they serve is to cut off intermediaries. It is hard to imagine today's world of decentralized applications(DApps) without its functionalities. However, deploying it on a blockchain protocol comes with potential risks. In other words, they are vulnerable to cyber attacks such as DOS attacks, phishing, flash loan attacks, and rentrancy attacks. One of the earliest events that proved that blockchain technology is not the gold standard for cybersecurity involved a smart contract. Many people remember this event as the infamous DAO hack, which happened in 2016 after hackers exploited a flaw in the code and stole over $50 million. The most recent example of this type of exploit is the Normie memecoin hack, which took place on the 26th of May 2024. This exploit not only resulted in the loss of over $800,000  but also saw the market capitalization of the memecoin slump to $35,000 from $41 million in a matter of days. Why Do Smart Contract Hacks Occur? There are bad actors in every dark corner of the web. Smart contract hacks occur because hackers are able to identify and exploit the vulnerabilities of a smart contract. In most cases, they are written by humans, making them prone to errors that hackers usually exploit. In another instance, hackers do this by tricking unsuspecting users into interacting with a malicious smart contract in order to steal their funds. Combating Smart Contract Hacks Blockchain protocols continue to suffer heavy financial loss due to the recurring exploit. To address this menace, a regular smart contract audit is usually recommended by cyber security experts. While this security measure might offer a semblance of efficacy, obtaining an audit certificate has never turned out to be the most assuring safety measure. As a matter of fact, a one-off audit is never enough because experience has shown that it must be carried out from time to time. Furthermore, the DeFi landscape has witnessed significant advances in blockchain security with the emergence of AI, so much so that AI is increasingly becoming a viable tool in the detection of anomalies. Leveraging AI can further enhance the ability of professional auditors to carry out a thorough risk assessment because it raises the bar for audit technology and reduces the dependence on the traditional manual process. The Significance of  Smart Contract Audit Auditing smart contracts is the process of running checks on the code to discover potential security flaws. While it is not the ultimate measure, it has grown in importance over the years, especially with the rise of professional audit firms. Regularly checking for vulnerability is an industry-standard procedure justified by collective wisdom: prevention is better than cure. It is also a reminder that cyber threats are always lurking around the corner. Most importantly, there is a need for blockchain protocols to diversify their cybersecurity strategies so that a regular audit is combined with other evolving techniques, such as artificial intelligence(AI). Commenting on the importance of a regular smart contract auditing UBET Sports CEO Daniel Jiwoong. Im said: “Smart contract auditing is essential for platform like UBET Sports operating in the decentralized finance (DeFi) space. These audits identify and mitigate security vulnerabilities that could be exploited by malicious actors, safeguarding user assets and maintaining the platform's integrity. Regular audits also build trust and confidence among users, reassuring them that the platform has been rigorously tested and verified by independent experts.” “Recently, UBET Sports underwent three comprehensive smart contract audits, demonstrating its commitment to security and reliability. The first audit coincided with the launch of UBET Sports' decentralized exchange (DEX) for sports betting, establishing a secure foundation. Subsequent audits focused on enhancing the Automated Market Maker (AMM) to improve slippage, optimizing gas fees, improving push settlements, and structuring revenue-sharing mechanisms for liquidity provision, ”he added. Is a routine smart contract audit worth it? “Building an on-chain product presents challenges, such as the need for audits before each release, preventing continuous integration and deployment. Despite these challenges and the high costs associated with multiple audits, we prioritized security to protect its users. With two more smart contract updates planned this year, we continue to make steady progress in the SportiFi space, merging sports and DeFi” Daniel further said. Conclusion Billions of dollars have been lost over the years to crypto hacks perpetrated by bad actors. Smart contract vulnerability can give rise to a potential hack, which can, in turn, undermine a blockchain protocol and drain the funds of its users. Promoting a secure blockchain ecosystem has been at the heart of every cybersecurity measure, like smart contract audits that are designed to combat the incidence of cyber-attacks. A smart contract audit, which typically involves a detailed examination of a protocol’s codebase, has been recognized as one of the standard techniques for combating potential crypto hacks. It has increasingly become a significant practice in blockchain security with the emergence of professional audit firms and sophisticated tools. Each time I read about a crypto hack on the internet, I usually heave a sigh of disappointment. I always ask myself whether there will ever be an end to the alarming rate of cyber attacks on blockchain protocols. For every crypto hack that has occurred, it feels like the cryptocurrency industry has taken ten steps backward, undermining its progress and worsening the industry’s image problem. Apparently, crypto hacks happen not because there are no effective cyber security measures in place but because they are either not enough or they are currently outpaced. Developing a superior cybersecurity technology must be seen as a race to beat hackers to their own game, and further improvements are required to match their tactics for tactics, so much so that cybersecurity technologies must be ten steps ahead of cyber threats. In this article, I will be delving into the efficacy of smart contract audits, highlighting the significance of a routine audit and the convergence of various approaches that are tailored towards a safer blockchain ecosystem. What Are Smart Contracts? Smart contracts are pieces of self-executing computer programs on a blockchain. They are designed to function when a particular set of conditions are fulfilled (i.e., minting an NFT), and the ultimate purpose they serve is to cut off intermediaries. It is hard to imagine today's world of decentralized applications(DApps) without its functionalities. However, deploying it on a blockchain protocol comes with potential risks. In other words, they are vulnerable to cyber attacks such as DOS attacks, phishing, flash loan attacks, and rentrancy attacks. One of the earliest events that proved that blockchain technology is not the gold standard for cybersecurity involved a smart contract. Many people remember this event as the infamous DAO hack, which happened in 2016 after hackers exploited a flaw in the code and stole over $50 million. The most recent example of this type of exploit is the Normie memecoin hack, which took place on the 26th of May 2024. This exploit not only resulted in the loss of over $800,000  but also saw the market capitalization of the memecoin slump to $35,000 from $41 million in a matter of days. Why Do Smart Contract Hacks Occur? There are bad actors in every dark corner of the web. Smart contract hacks occur because hackers are able to identify and exploit the vulnerabilities of a smart contract. In most cases, they are written by humans, making them prone to errors that hackers usually exploit. In another instance, hackers do this by tricking unsuspecting users into interacting with a malicious smart contract in order to steal their funds. Combating Smart Contract Hacks Blockchain protocols continue to suffer heavy financial loss due to the recurring exploit. To address this menace, a regular smart contract audit is usually recommended by cyber security experts. While this security measure might offer a semblance of efficacy, obtaining an audit certificate has never turned out to be the most assuring safety measure. As a matter of fact, a one-off audit is never enough because experience has shown that it must be carried out from time to time. Furthermore, the DeFi landscape has witnessed significant advances in blockchain security with the emergence of AI, so much so that AI is increasingly becoming a viable tool in the detection of anomalies. Leveraging AI can further enhance the ability of professional auditors to carry out a thorough risk assessment because it raises the bar for audit technology and reduces the dependence on the traditional manual process. The Significance of  Smart Contract Audit Auditing smart contracts is the process of running checks on the code to discover potential security flaws. While it is not the ultimate measure, it has grown in importance over the years, especially with the rise of professional audit firms. Regularly checking for vulnerability is an industry-standard procedure justified by collective wisdom: prevention is better than cure. It is also a reminder that cyber threats are always lurking around the corner. Most importantly, there is a need for blockchain protocols to diversify their cybersecurity strategies so that a regular audit is combined with other evolving techniques, such as artificial intelligence(AI). Commenting on the importance of a regular smart contract auditing UBET Sports CEO Daniel Jiwoong. Im said: “Smart contract auditing is essential for platform like UBET Sports operating in the decentralized finance (DeFi) space. These audits identify and mitigate security vulnerabilities that could be exploited by malicious actors, safeguarding user assets and maintaining the platform's integrity. Regular audits also build trust and confidence among users, reassuring them that the platform has been rigorously tested and verified by independent experts.” “Smart contract auditing is essential for platform like UBET Sports operating in the decentralized finance (DeFi) space. These audits identify and mitigate security vulnerabilities that could be exploited by malicious actors, safeguarding user assets and maintaining the platform's integrity. Regular audits also build trust and confidence among users, reassuring them that the platform has been rigorously tested and verified by independent experts.” “Recently, UBET Sports underwent three comprehensive smart contract audits, demonstrating its commitment to security and reliability. The first audit coincided with the launch of UBET Sports' decentralized exchange (DEX) for sports betting, establishing a secure foundation. Subsequent audits focused on enhancing the Automated Market Maker (AMM) to improve slippage, optimizing gas fees, improving push settlements, and structuring revenue-sharing mechanisms for liquidity provision, ”he added. “Recently, UBET Sports underwent three comprehensive smart contract audits, demonstrating its commitment to security and reliability. The first audit coincided with the launch of UBET Sports' decentralized exchange (DEX) for sports betting, establishing a secure foundation. Subsequent audits focused on enhancing the Automated Market Maker (AMM) to improve slippage, optimizing gas fees, improving push settlements, and structuring revenue-sharing mechanisms for liquidity provision, ”he added. Is a routine smart contract audit worth it? “Building an on-chain product presents challenges, such as the need for audits before each release, preventing continuous integration and deployment. Despite these challenges and the high costs associated with multiple audits, we prioritized security to protect its users. With two more smart contract updates planned this year, we continue to make steady progress in the SportiFi space, merging sports and DeFi” Daniel further said. “Building an on-chain product presents challenges, such as the need for audits before each release, preventing continuous integration and deployment. Despite these challenges and the high costs associated with multiple audits, we prioritized security to protect its users. With two more smart contract updates planned this year, we continue to make steady progress in the SportiFi space, merging sports and DeFi” Daniel further said. Conclusion Conclusion Billions of dollars have been lost over the years to crypto hacks perpetrated by bad actors. Smart contract vulnerability can give rise to a potential hack, which can, in turn, undermine a blockchain protocol and drain the funds of its users. Promoting a secure blockchain ecosystem has been at the heart of every cybersecurity measure, like smart contract audits that are designed to combat the incidence of cyber-attacks. A smart contract audit, which typically involves a detailed examination of a protocol’s codebase, has been recognized as one of the standard techniques for combating potential crypto hacks. It has increasingly become a significant practice in blockchain security with the emergence of professional audit firms and sophisticated tools.

The Importance Of a Routine Smart Contract Audit In Blockchain Security

MariaDB 11.4 introduced many advanced features. One that grabbed my attention is the general support of packages for stored routines. Although this was previously available by activating the Oracle compatibility mode, now, the feature is available generally out-of-the-box. This will help you to significantly enhance the organization of database development within a MariaDB environment. Packages provide a modular approach to managing database logic. This addition aligns MariaDB more closely with other advanced database systems that have long utilized packages, such as Oracle, and sets it apart in that regard from other open-source relational databases that don't support packages. Packages in MariaDB allow you to group related stored procedures, functions, variables, and other elements together into a single unit. This structure provides several benefits, including improved code organization, enhanced reusability, and simplified maintenance. Prior to this update, each stored procedure and function in MariaDB existed independently, which could lead to a cluttered schema and more complicated management of complex business logic when implemented in the database. Packages address this issue by providing a way to logically group related routines. Again, the primary advantage of using packages is the encapsulation of related routines. For example, in an e-commerce application, operations related to order processing can be grouped into a single package called OrderProcessing. This package might include procedures like PlaceOrder, CancelOrder, and UpdateOrderStatus, as well as functions such as GetOrderDetails. This logical grouping makes the database schema more organized and the codebase easier to navigate and hence to maintain. Creating Packages Creating and using packages in MariaDB 11.4 and later is straightforward. Simply use the CREATE PACKAGE statement to define a package and the CREATE PACKAGE BODY statement to implement the package’s routines. Here is a simplified example without the actual business logic implementation: DELIMITER $$

CREATE OR REPLACE PACKAGE OrderProcessing
  PROCEDURE PlaceOrder(customer_id INT, product_id INT, quantity INT);
  PROCEDURE CancelOrder(order_id INT);
  FUNCTION GetOrderDetails(order_id INT) RETURNS JSON;
END;

CREATE OR REPLACE PACKAGE BODY OrderProcessing
  PROCEDURE PlaceOrder(customer_id INT, product_id INT, quantity INT)
  BEGIN
    -- Implementation code here
  END;

  PROCEDURE CancelOrder(order_id INT)
  BEGIN
    -- Implementation code here
  END;

  FUNCTION GetOrderDetails(order_id INT) RETURNS JSON
  BEGIN
    -- Implementation code here
  END;
END;

$$
DELIMITER ; In this example, the OrderProcessing package is defined with two procedures and one function. The package body provides the implementation for these routines, encapsulating the logic related to order processing within a single package. Calling Packaged Stored Routines To call a procedure or function that was defined in a package, you use the "dot notation." Here's an example of how to call the CancelOrder procedure in the OrderProcessing package: CALL OrderProcessing.CancelOrder(7); The same applies to functions in packages: SELECT OrderProcessing.GetOrderDetails(7); You can also define package-level variables and constants, which are accessible to all routines within the package. This way, you can share common data without relying on global variables or passing around parameters between routines. By centrally managing shared data within the package, you reduce code duplication and minimize the risk of errors. The following is an example (don't take the variable names too seriously in this snippet of code): DELIMITER $$

CREATE OR REPLACE PACKAGE OrderProcessing
  -- procedure list (see previous example)
END;

CREATE OR REPLACE PACKAGE BODY OrderProcessing
  -- variable declarations
  DECLARE some_count INT DEFAULT 1;
  DECLARE some_total INT DEFAULT 0;

  -- procedure definitions (see previous example)
END;

$$
DELIMITER ; Other Benefits of Packages The introduction of packages in MariaDB 11.4 also brings the possibility of better version control and modularization of code. You can now manage stored routines more effectively, making it easier to track changes and updates. This modularization is particularly beneficial in large projects, where multiple developers might be working on different parts of the database logic simultaneously. By isolating different functionalities into packages, conflicts, and overlaps can be minimized, leading to a smoother development process. Moreover, packages support forward declarations, which means that the routines can be defined before their actual implementation. This feature allows for a more flexible and structured approach to coding, where developers can outline the package interface first and then fill in the details. This separation of interface and implementation can lead to cleaner, more understandable code, facilitating collaboration, and reducing the learning curve for new developers joining a project. For developers accustomed to working with Oracle databases, the inclusion of packages in MariaDB 11.4 will feel familiar and welcome. It bridges a functional gap between MariaDB and Oracle, making it easier to transition between these platforms. Packages vs Multiple Schemas It's important to note the distinction between packages and merely using multiple database schemas. While multiple schemas can help segregate different parts of a database, they do not offer the same level of organization and encapsulation as packages. Schemas are useful for dividing distinct areas of data and logic, but they do not inherently group related procedures and functions together in a way that enhances modularity and maintainability. Packages, on the other hand, allow for a more granular and cohesive approach, grouping related logic together within the same schema. This not only simplifies the management of routines but also improves the clarity and maintainability of the code. Try It Out As always, MariaDB continues to evolve. Try it out today by downloading the latest version of MariaDB, or if you have Docker running: docker run --name mariadb-11.4 -e MARIADB_ROOT_PASSWORD=my-secret-pw -e MARIADB_DATABASE=mydb -e MARIADB_USER=myuser -e MARIADB_PASSWORD=mypassword -d mariadb:11.4

docker exec -it mariadb-11.4 mariadb -p"mypassword" MariaDB 11.4 introduced many advanced features . One that grabbed my attention is the general support of packages for stored routines. Although this was previously available by activating the Oracle compatibility mode , now, the feature is available generally out-of-the-box. This will help you to significantly enhance the organization of database development within a MariaDB environment. MariaDB 11.4 advanced features Oracle compatibility mode Packages provide a modular approach to managing database logic. This addition aligns MariaDB more closely with other advanced database systems that have long utilized packages, such as Oracle, and sets it apart in that regard from other open-source relational databases that don't support packages. Packages in MariaDB allow you to group related stored procedures, functions, variables, and other elements together into a single unit. This structure provides several benefits, including improved code organization, enhanced reusability, and simplified maintenance. Prior to this update, each stored procedure and function in MariaDB existed independently, which could lead to a cluttered schema and more complicated management of complex business logic when implemented in the database . implemented in the database Packages address this issue by providing a way to logically group related routines. Again, the primary advantage of using packages is the encapsulation of related routines. For example, in an e-commerce application, operations related to order processing can be grouped into a single package called OrderProcessing . This package might include procedures like PlaceOrder , CancelOrder , and UpdateOrderStatus , as well as functions such as GetOrderDetails . OrderProcessing PlaceOrder CancelOrder UpdateOrderStatus GetOrderDetails This logical grouping makes the database schema more organized and the codebase easier to navigate and hence to maintain. Creating Packages Creating and using packages in MariaDB 11.4 and later is straightforward. Simply use the CREATE PACKAGE statement to define a package and the CREATE PACKAGE BODY statement to implement the package’s routines. Here is a simplified example without the actual business logic implementation: CREATE PACKAGE CREATE PACKAGE BODY DELIMITER $$

CREATE OR REPLACE PACKAGE OrderProcessing
  PROCEDURE PlaceOrder(customer_id INT, product_id INT, quantity INT);
  PROCEDURE CancelOrder(order_id INT);
  FUNCTION GetOrderDetails(order_id INT) RETURNS JSON;
END;

CREATE OR REPLACE PACKAGE BODY OrderProcessing
  PROCEDURE PlaceOrder(customer_id INT, product_id INT, quantity INT)
  BEGIN
    -- Implementation code here
  END;

  PROCEDURE CancelOrder(order_id INT)
  BEGIN
    -- Implementation code here
  END;

  FUNCTION GetOrderDetails(order_id INT) RETURNS JSON
  BEGIN
    -- Implementation code here
  END;
END;

$$
DELIMITER ; DELIMITER $$

CREATE OR REPLACE PACKAGE OrderProcessing
  PROCEDURE PlaceOrder(customer_id INT, product_id INT, quantity INT);
  PROCEDURE CancelOrder(order_id INT);
  FUNCTION GetOrderDetails(order_id INT) RETURNS JSON;
END;

CREATE OR REPLACE PACKAGE BODY OrderProcessing
  PROCEDURE PlaceOrder(customer_id INT, product_id INT, quantity INT)
  BEGIN
    -- Implementation code here
  END;

  PROCEDURE CancelOrder(order_id INT)
  BEGIN
    -- Implementation code here
  END;

  FUNCTION GetOrderDetails(order_id INT) RETURNS JSON
  BEGIN
    -- Implementation code here
  END;
END;

$$
DELIMITER ; In this example, the OrderProcessing package is defined with two procedures and one function. The package body provides the implementation for these routines, encapsulating the logic related to order processing within a single package. OrderProcessing Calling Packaged Stored Routines To call a procedure or function that was defined in a package, you use the "dot notation." Here's an example of how to call the CancelOrder procedure in the OrderProcessing package: CancelOrder OrderProcessing CALL OrderProcessing.CancelOrder(7); CALL OrderProcessing.CancelOrder(7); The same applies to functions in packages: SELECT OrderProcessing.GetOrderDetails(7); SELECT OrderProcessing.GetOrderDetails(7); You can also define package-level variables and constants, which are accessible to all routines within the package. This way, you can share common data without relying on global variables or passing around parameters between routines. By centrally managing shared data within the package, you reduce code duplication and minimize the risk of errors. The following is an example (don't take the variable names too seriously in this snippet of code): DELIMITER $$

CREATE OR REPLACE PACKAGE OrderProcessing
  -- procedure list (see previous example)
END;

CREATE OR REPLACE PACKAGE BODY OrderProcessing
  -- variable declarations
  DECLARE some_count INT DEFAULT 1;
  DECLARE some_total INT DEFAULT 0;

  -- procedure definitions (see previous example)
END;

$$
DELIMITER ; DELIMITER $$

CREATE OR REPLACE PACKAGE OrderProcessing
  -- procedure list (see previous example)
END;

CREATE OR REPLACE PACKAGE BODY OrderProcessing
  -- variable declarations
  DECLARE some_count INT DEFAULT 1;
  DECLARE some_total INT DEFAULT 0;

  -- procedure definitions (see previous example)
END;

$$
DELIMITER ; Other Benefits of Packages The introduction of packages in MariaDB 11.4 also brings the possibility of better version control and modularization of code. You can now manage stored routines more effectively, making it easier to track changes and updates. This modularization is particularly beneficial in large projects, where multiple developers might be working on different parts of the database logic simultaneously. By isolating different functionalities into packages, conflicts, and overlaps can be minimized, leading to a smoother development process. Moreover, packages support forward declarations, which means that the routines can be defined before their actual implementation. This feature allows for a more flexible and structured approach to coding, where developers can outline the package interface first and then fill in the details. This separation of interface and implementation can lead to cleaner, more understandable code, facilitating collaboration, and reducing the learning curve for new developers joining a project. For developers accustomed to working with Oracle databases, the inclusion of packages in MariaDB 11.4 will feel familiar and welcome. It bridges a functional gap between MariaDB and Oracle, making it easier to transition between these platforms. Packages vs Multiple Schemas It's important to note the distinction between packages and merely using multiple database schemas. While multiple schemas can help segregate different parts of a database, they do not offer the same level of organization and encapsulation as packages. Schemas are useful for dividing distinct areas of data and logic, but they do not inherently group related procedures and functions together in a way that enhances modularity and maintainability. Packages, on the other hand, allow for a more granular and cohesive approach, grouping related logic together within the same schema. This not only simplifies the management of routines but also improves the clarity and maintainability of the code. Try It Out As always, MariaDB continues to evolve . Try it out today by downloading the latest version of MariaDB, or if you have Docker running: MariaDB continues to evolve downloading docker run --name mariadb-11.4 -e MARIADB_ROOT_PASSWORD=my-secret-pw -e MARIADB_DATABASE=mydb -e MARIADB_USER=myuser -e MARIADB_PASSWORD=mypassword -d mariadb:11.4

docker exec -it mariadb-11.4 mariadb -p"mypassword" docker run --name mariadb-11.4 -e MARIADB_ROOT_PASSWORD=my-secret-pw -e MARIADB_DATABASE=mydb -e MARIADB_USER=myuser -e MARIADB_PASSWORD=mypassword -d mariadb:11.4

docker exec -it mariadb-11.4 mariadb -p"mypassword"

Packages for Store Routines in MariaDB 11.4: What You Need to Know

If a product is complex and releases are substantial, there are multiple ways to ensure quality. One key tool I use in our development process is team testing: stepping into the customer’s shoes, traversing various user journeys, and ensuring all key interactions work as intended. This approach offers numerous benefits, from engaging the entire team in understanding the product to correcting flaws in the original business logic. Despite its usefulness, team testing sessions tend to be tedious and generally disliked: building a product is far more enjoyable than repeatedly clicking through it. In this post, I will describe how I made team testing more engaging and somewhat enjoyable by incorporating ChatGPT into the process, transforming it into a competitive activity. How We Conduct Team Testing The process was straightforward: Deploy a feature to a testing environment.
Document what needs to be checked: main user journeys and definitions of success.
Gather on a call or in a room, use the product, discuss, and exchange feedback.
Organize and prioritize feedback, then act accordingly. As a result, the team has usually compiled a list of issues to address. Introducing ChatGPT With the rise of ChatGPT in mid-2023, I decided to integrate it into our testing sessions. Initially, I used it to analyze and count issue reports in Slack—since Slack lacks convenient export functionality. Here’s the prompt I tried: The text below is the log of slack channel.

It contains bugs reported by people, each bug report starts with a first name, then timestamp, then the message itself (normally 1 or 2 lines).

Strings containing ".png", IMG" or ".mov"  could be ignored.

Read the text, count the number of reports per person and rank them from highest ChatGPT struggled at first, glitching in about 60% of cases with verbose error messages. I realized I needed a different approach. Switching to a Script Since ChatGPT ran a Python interpreter for our task, I decided to directly utilize the Python code it wrote. I adjusted the script to account for the way Slack handles attached files as separate messages: # Initialize counters for each name based on the list provided
# The names should match the displayed names in Slack
name_counts = {
    "John": 0,
    "Jane": 0,
    "Rosy": 0,
}

# Open the file and count the occurrences of each name
with open("testing_session_log.txt", "r") as file:
    lines = file.readlines()

# Filtering out garbage lines and counting names
for line in lines:
    # Ignore garbage lines
    if any(garbage in line for garbage in [".png", ".IMG", ".mov"]):
        continue
    for name in name_counts.keys():
        if name in line:
            name_counts[name] += 1

print(name_counts) Returning to ChatGPT for Creativity and Recognition Implementing the script to generate a leaderboard immediately after the session introduced a sense of competition. I saw the engagement growing, and people reporting more bugs! So, I continued to use ChatGPT for crafting personalized praise based on the team’s reported issues, acknowledging their contributions: Using the attached testing session log, praise everyone for their impact and highligh one report of a choice for each person.

Participants names:
John
Jane
Rosy

Wrap the praise in a form of a short, sincere and inspirational message, no more than 4 sentences long. I found it deeply satisfying to read the praise from a machine: John: Your insight on UI details like the collapsed header buttons and gallery navigation enhances our project's usability.
Your contributions are crucial for a seamless user experience.

Jane: Your keen observations, especially on navigation issues, enhance our platform's intuitiveness.
Your ability to catch subtle bugs is invaluable.

Rosy:Your focus on mobile usability, from download behaviors to icon alignment, significantly polishes our mobile interface.
Your efforts make a substantial difference. Conclusion What I’ve implemented isn’t rocket science, but in the pre-LLM era, this would have taken considerably longer to achieve, if at all. While the future of AI-driven products is still shaping up, it’s clear that product teams can benefit greatly by integrating such technologies to simplify tasks, boost positive reinforcement, and free up time for critical projects. Image credit: Midjourney, prompt “team of engineers coding late at night, Hyper-realistic textures, Precise details --version 6.0 --weird 1000” If a product is complex and releases are substantial, there are multiple ways to ensure quality. One key tool I use in our development process is team testing: stepping into the customer’s shoes, traversing various user journeys, and ensuring all key interactions work as intended. This approach offers numerous benefits, from engaging the entire team in understanding the product to correcting flaws in the original business logic. Despite its usefulness, team testing sessions tend to be tedious and generally disliked: building a product is far more enjoyable than repeatedly clicking through it. In this post, I will describe how I made team testing more engaging and somewhat enjoyable by incorporating ChatGPT into the process, transforming it into a competitive activity. How We Conduct Team Testing The process was straightforward: Deploy a feature to a testing environment. Document what needs to be checked: main user journeys and definitions of success. Gather on a call or in a room, use the product, discuss, and exchange feedback. Organize and prioritize feedback, then act accordingly. Deploy a feature to a testing environment. Document what needs to be checked: main user journeys and definitions of success. Gather on a call or in a room, use the product, discuss, and exchange feedback. Organize and prioritize feedback, then act accordingly. As a result, the team has usually compiled a list of issues to address. Introducing ChatGPT With the rise of ChatGPT in mid-2023, I decided to integrate it into our testing sessions. Initially, I used it to analyze and count issue reports in Slack—since Slack lacks convenient export functionality. Here’s the prompt I tried: The text below is the log of slack channel.

It contains bugs reported by people, each bug report starts with a first name, then timestamp, then the message itself (normally 1 or 2 lines).

Strings containing ".png", IMG" or ".mov"  could be ignored.

Read the text, count the number of reports per person and rank them from highest The text below is the log of slack channel.

It contains bugs reported by people, each bug report starts with a first name, then timestamp, then the message itself (normally 1 or 2 lines).

Strings containing ".png", IMG" or ".mov"  could be ignored.

Read the text, count the number of reports per person and rank them from highest ChatGPT struggled at first, glitching in about 60% of cases with verbose error messages. I realized I needed a different approach. Switching to a Script Since ChatGPT ran a Python interpreter for our task, I decided to directly utilize the Python code it wrote. Python interpreter I adjusted the script to account for the way Slack handles attached files as separate messages: # Initialize counters for each name based on the list provided
# The names should match the displayed names in Slack
name_counts = {
    "John": 0,
    "Jane": 0,
    "Rosy": 0,
}

# Open the file and count the occurrences of each name
with open("testing_session_log.txt", "r") as file:
    lines = file.readlines()

# Filtering out garbage lines and counting names
for line in lines:
    # Ignore garbage lines
    if any(garbage in line for garbage in [".png", ".IMG", ".mov"]):
        continue
    for name in name_counts.keys():
        if name in line:
            name_counts[name] += 1

print(name_counts) # Initialize counters for each name based on the list provided
# The names should match the displayed names in Slack
name_counts = {
    "John": 0,
    "Jane": 0,
    "Rosy": 0,
}

# Open the file and count the occurrences of each name
with open("testing_session_log.txt", "r") as file:
    lines = file.readlines()

# Filtering out garbage lines and counting names
for line in lines:
    # Ignore garbage lines
    if any(garbage in line for garbage in [".png", ".IMG", ".mov"]):
        continue
    for name in name_counts.keys():
        if name in line:
            name_counts[name] += 1

print(name_counts) Returning to ChatGPT for Creativity and Recognition Implementing the script to generate a leaderboard immediately after the session introduced a sense of competition. I saw the engagement growing, and people reporting more bugs! So, I continued to use ChatGPT for crafting personalized praise based on the team’s reported issues, acknowledging their contributions: Using the attached testing session log, praise everyone for their impact and highligh one report of a choice for each person.

Participants names:
John
Jane
Rosy

Wrap the praise in a form of a short, sincere and inspirational message, no more than 4 sentences long. Using the attached testing session log, praise everyone for their impact and highligh one report of a choice for each person.

Participants names:
John
Jane
Rosy

Wrap the praise in a form of a short, sincere and inspirational message, no more than 4 sentences long. I found it deeply satisfying to read the praise from a machine: John: Your insight on UI details like the collapsed header buttons and gallery navigation enhances our project's usability.
Your contributions are crucial for a seamless user experience.

Jane: Your keen observations, especially on navigation issues, enhance our platform's intuitiveness.
Your ability to catch subtle bugs is invaluable.

Rosy:Your focus on mobile usability, from download behaviors to icon alignment, significantly polishes our mobile interface.
Your efforts make a substantial difference. John: Your insight on UI details like the collapsed header buttons and gallery navigation enhances our project's usability.
Your contributions are crucial for a seamless user experience.

Jane: Your keen observations, especially on navigation issues, enhance our platform's intuitiveness.
Your ability to catch subtle bugs is invaluable.

Rosy:Your focus on mobile usability, from download behaviors to icon alignment, significantly polishes our mobile interface.
Your efforts make a substantial difference. Conclusion What I’ve implemented isn’t rocket science, but in the pre-LLM era, this would have taken considerably longer to achieve, if at all. While the future of AI-driven products is still shaping up, it’s clear that product teams can benefit greatly by integrating such technologies to simplify tasks, boost positive reinforcement, and free up time for critical projects. Image credit: Midjourney, prompt “team of engineers coding late at night, Hyper-realistic textures, Precise details --version 6.0 --weird 1000” Image credit: Midjourney, prompt “team of engineers coding late at night, Hyper-realistic textures, Precise details --version 6.0 --weird 1000”

From Routine to Rewarding: Integrating ChatGPT Into Product Testing Workflow

As the world becomes increasingly digitalized, companies and individuals invest more time, effort, and money in Socializing, entertainment, money-making, and other online opportunities are a by-product of the world wide web — often, they benefit our lives meaningfully. cybersecurity. Alongside digitalization, cybersecurity is as much a top priority as it is a valid concern for most companies and individuals. From data protection to identity verification, the need for constant or routine revisions in safety procedures is of paramount importance to businesses and organizations that put internet safety first. Cybersecurity companies can be of tremendous help with tightening safety from the first step in the user journey, as they are well-equipped to guide internet users on how to protect their data. Most importantly, cybersecurity experts can help to forestall cyber attacks by routinely advising companies, the public sector, and individual users about online safety and by implementing the broader scope of their research and practices. Implementing Cybersecurity Measures For Users notes that companies have to meet the needs of underserved segments and improve technological services to offer an easy and user-friendly environment. As businesses put effort into protecting the high profit-yielding segments, the other part of the user base becomes vulnerable regarding safety. Constant education and features to support cybersecurity initiatives for every user highlight the focus on end-user safety that enables innovation. McKinsey While the cybersecurity market is forecasted to grow by by 2027, some companies are adopting new security measures to match the increasing demand for data protection, which continues to trend upwards. Businesses hire external consultants and use internal experts to monitor and improve their operations' cybersecurity. A blend of these practices can help businesses educate employees and end-users about such a topic, thus, improving their cybersecurity measures. $266.2 billion An excellent example of proper cybersecurity adoption is a communication and collaboration platform. With the rise to prominence during the COVID-19 pandemic, the company had to adapt to significant growth in user base and implement heightened security initiatives. Slack, All information about its end-user security measures is available on its website. The company lists its certificates, data protection layers, and privacy standards. Slack went through independent assessments from several organizations in different countries to ensure the security of its cloud service. Moreover, it enables users to encrypt their messages and choose data storage periods and permissions. Another important example to consider is a crowdsourced web intelligence network that continuously implements safety layers to deliver a reliable service to end users. It is focused on user consent and about what security measures apply at each step while the users share their internet resources for monetary rewards. Honeygain complies with GDPR and CCPA legislation to provide the highest standard for data protection so that every user can safely use the app. Honeygain, education While user consent on publicly available data gathering is the first step, every payout for the shared internet connection is managed by verified payment platforms as a second step. With multiple steps in strengthening the security of their users, Honeygain adopts various safety tools and standards. For example, they have implemented 2-factor authentication for payouts to strengthen the security surrounding monetary transactions alongside other cybersecurity efforts like its anti-cheat system. Honeygain chose it for its payments because it’s regarded as one of the most popular and user-friendly ways to increase online security — the multi-factor authentication system, which includes 2-factor authentication, reached a market value of $13 billion in 2022. For example, Google found that its 2-Step Verification via SMS sent to a recovery phone number stopped 100% of automated bots. Additionally, it can help companies save up to $3 million per data breach. Is 2FA really enough for cybersecurity? However, 2-factor authentication should be one of many security measures if you wish to protect your data and devices. Cybercriminals can target users who use passwords and 2-factor authentication to easily extract information like passwords themselves, secret questions, token-generated passwords, and even device ID data. Moreover, 2-factor authentication heavily relies on the user’s devices — it can’t be set up on a single device. Other security risks arise with 2-factor authentication, like SIM swapping, device theft, and different ways to gain control over users’ information. Thus, companies should adopt 2-factor authentication as an additional layer of security while simultaneously implementing other measures such as proper authorization and access systems, improved network security, and more. These examples demonstrate how important end-user safety has become for companies. While 2FA is a great tool in ensuring initial online security, it should be accompanied by additional safety measures like the examples of Slack and Honeygain suggest. Individual cybersecurity efforts are celebrated — but businesses must ensure additional customer security and support as the digital economy expands. If a security measure is popular and widely adapted, it doesn’t mean it’s foolproof. The best cybersecurity strategy consists of different procedures implemented in tandem with each other. Popular applications like Duolingo, LinkedIn, Tinder, and Dropbox offer multiple layers of cybersecurity to protect users and companies from illicit activities. When it comes to cybersecurity, every step is essential, whether it seems small or significant. Additionally, constant revisions and upgrades to current safety measures will ensure the company’s and its individual user’s online safety. Therefore, every effort in end-user security should be regarded as the top priority, just like the examples of Slack or Honeygain suggest.

The Importance of Routine Cybersecurity Practices: Learning From Slack And Honeygain

Many testers and developers use Postman for both manual and automated API testing. However, not all Postman users fully exploit its capabilities to simplify API-related tasks. In this article, I will demonstrate a few basic examples of how to make API testing faster, more efficient, and reduce time spent on various routine actions when using Postman. Let's dive in and uncover some tips and tricks that will make your API testing experience with Postman faster, more efficient, and less prone to repetitive tasks. Let’s start with Environment. Environment In Postman, the Environment feature allows you to manage environment variables during the execution of test scenarios. It serves as a container where you can define and store a set of variables that will be used in all requests and scripts associated with that environment. Using the Environment feature in Postman provides flexibility and reusability. Instead of hard-coding values or repeating them across multiple requests and scripts, you can define variables in the environment and reference them wherever needed. This way, you can easily update values in one central location without modifying each individual request. Indeed, each variable in an Environment has a name and a value. You can utilize these variables to store data such as URLs, authentication tokens, API keys, and other values that can be used in your requests Let's consider an example: We have a regular backend service with a REST API, , that we want to test. Let's create the first environment. https://reqres.in To create an environment, open the "Environments" tab in the left menu of Postman, and click on the " " button. + Now enter the name of the first environment, let's call it "Production." In an Environment, variables are typically created to be reused across requests. Let's create the first variable: Name it "service_url" and set its value to " ". https://reqres.in After creating the variable, click on "Save" to save all the changes. In the top right corner, locate "No environment" and click on it. Then, select our created environment, "Production". Now, we can use the variables from the selected environment. Let's go to Collections and create a new request. In the URL field, enter the following: “ ”. Now, you can click on "Send" and see the result: {{service_url}}/api/users Our request has been completed successfully. The request was made to the address " " which was stored in the environment variable " " and we appended " " to it. https://reqres.in service_url /api/users By utilizing the " " variable, we can easily reuse it across all our requests. This allows for flexibility and makes it convenient to manage and update the base URL in a single place, saving time and effort in case the URL needs to be modified. service_url But the real power comes when we create multiple environments. Let's go back to "Environments" and create another environment called "Stage". In this environment, let's create the " " variable again, but this time, with the value "https:// .reqres.in". service_url stage Now, in the top right corner, change the Environment to "Stage." Go back to the previous request and execute it again: We receive an error in the response because the domain "stage.reqres.in" does not exist. However, this is not a problem as it confirms that the URL has changed to the value of the " " variable from the "Stage" environment, and everything is functioning correctly. service_url By creating multiple environments with the same variables but different values, we can easily switch between them as needed. In the projects I participate in, we typically create the following environments: : Used to test requests in the live production environment. Production : Used to test requests in the development/staging environment. Stage : Created specifically for testing API branches or feature branches. Branch : Created for testing the API on a locally deployed service. It is typically used by developers to test and debug the API on their local machines. Local For each environment, variables are created and shared across requests. These variables can include API keys, URLs, user agents, and other parameters that differ from one environment to another. By utilizing environments, you can easily switch between different environments (such as Dev, Production, Branch, or Local) with just a couple of clicks. Now, let's move on to another tool that helps speed up the creation of new requests. Request Header Presets In most services, each request has a set of headers that can include the following: Content-Type: Specifies the media type of the request payload, such as application/json or application/x-www-form-urlencoded. Authorization: Provides authentication credentials or tokens to access protected resources. User-Agent: Identifies the client making the request, typically the name and version of the software or application. And other custom headers specific to different services Indeed, manually filling in all the headers for each new request can be time-consuming, especially when there are numerous headers involved. Two functions come to our rescue in such situations: : This function allows you to quickly create a new request by copying an existing one and then modifying it to suit your needs. It is a fast method but may not always be suitable if certain requests have unique headers that should not be sent in other requests. Duplicate : This is the function we will be discussing now. Header presets To access the header presets feature, follow these steps: Open any request in Postman. Go to the "Headers" section. On the right-hand side, you will find a button labeled "Presets." After clicking on the "Presets" button, select "Manage presets", and in the opened menu, click on "Add". You will then see the following screen: Here, we can add headers for presets. Let's create the first header: Key: "Accept-Language" Value: "en" Description: "Preferred content language code" It is a good practice to provide descriptions for headers in presets so that every team member understands the purpose of each header. Let's name the preset "Standard Headers", and click on "Add." Now, open the "Headers" tab of the request, and click on "Presets" once again. In the list, you will see the preset we created. Select it, and the header from the preset will be added to the list of headers: So we have added our header from the preset to the current list of headers. That way, we can create multiple presets for different types of requests. For example, in the projects I participate in, we usually create three presets: one for authenticated requests, one for unauthenticated requests, and one for internal requests. When using presets, there are a few things to keep in mind: If the request's header list already contains headers from a preset, applying the preset will not overwrite those headers. The preset will simply add all the headers to the request's header list. Therefore, it's important to check the list for duplicates. You can use variables from the Environment in the header values. This makes presets even more powerful, as you can dynamically set values based on the environment. Now, let's move on to examples of automating routine tasks using tests. Automation of Passing Authentication to All Requests After Login At many services, there are endpoints that require authentication. Let's take Bearer authentication as an example, where each request needs to include the "Authorization" header with an authentication token. This token needs to be fresh because it has a specific expiration date. For testing requests with authentication, there are multiple approaches. I will demonstrate what I consider the simplest and quickest method, in my opinion. To illustrate this, let's take the service as an example again. To access an authenticated endpoint, Bearer authentication is required. reqres.in The service has an endpoint " " that provides an authentication token. Let's make a request to this endpoint in Postman: /login After a successful request, the service returns an authentication token. We need to configure Postman to automatically include this token value in all requests that require authentication. To achieve this, navigate to the "Tests" tab (located below the URL input), and on the right side, under "Snippets", select "Set environment variable". The following code snippet will be generated: pm.environment.set("variable_key", "variable_value"); To achieve this, navigate to the "Tests" tab (located below the URL input), and on the right side, under "Snippets", select "Set environment variable". Replace "variable_key" with "authorization_token" and replace "variable_value" with "pm.response.json().token" so that it looks as follows: pm.environment.set("authorization_token", pm.response.json().token); Now, execute the request. If it is successful, click on the eye icon in the top-right corner. You will see a screen displaying the list of variables in your environment, which includes the "authorization_token" variable with the value extracted from the response of the request. What happened here: We used a test script. Tests are always executed after the request is made. You can learn more about tests here: . Postman - Writing Scripts is a function used to set the value of an environment variable, and that's how we set the value of the variable. You can even set the value of a variable that doesn't exist in the environment yet, as it will be automatically created. pm.environment.set() authorization_token retrieves the JSON object from the response of the request. Then we use to extract the value from the desired field. pm.response.json() .token As a result, we have an environment variable that will automatically be set whenever we use the ` ` endpoint. This allows us to have the authorization token automatically included in every subsequent request that requires authentication. /login Now all we need to do is go to the relevant requests and add the "Authorization" header with the value " ". This way, the authorization will be automatically included in those requests using the value of the " " variable: Bearer {{authorization_token}} authorization_token As a result, we have written a small script that eliminates the need to manually set the authorization in our environment. It will automatically be applied when a successful login request is made. This kind of automation allows us to simplify working with requests that require data sharing between them. Let's move on to the bonus part — generating various fields. Generating Random Data for Requests Quite often, when testing different APIs, we may need various data, such as: User data: names, surnames, phone numbers, company names, etc. Unique UUIDs Current date and time and much more Some of these things can be invented and written manually each time, while others need to be generated using services, websites, etc. But why bother doing that when Postman can do it all for you? Postman has a wide range of data options that it can generate. You can explore all of them by typing " " in the URL input field. {{ The menu scrolls and contains over 100 different options, such as: Current timestamp (UTC or based on your timezone) Random phone number UUID Random locale Random color And many more If you frequently test APIs, such as when modifying user data, sometimes it's much more beneficial to use random values instead of hardcoded ones. This allows you to cover unexpected scenarios as it introduces variability. By using random values, you can test edge cases and uncover potential issues that may not be apparent with fixed values. Well, Conclusion So, we have covered several simple examples of automating routine tasks with the features of Postman. These pretty little things greatly simplify working with APIs and reduce the amount of manual work and time spent on testing. Enjoy using them! 🙂

Automation of Tester's Routine Using Postman

Introduction: Ever since the buzz about GenAI and ChatGPT, I have been trying to understand the space and leveraging it into my day-to-day activities as a Data Engineer. No doubt it has been useful for debugging with respective programming and documentation. Personally, it played a significant role in helping me plan my Dubai itinerary. It even contributed to naming my friend’s daughter. However, it works pretty well if you give appropriate and precise requirements. There is a lot of anxiety among people that AI is going to take our jobs as they feel almost everything will be automated through AI. Is LLM as good as everyone claims? In this article, we will look into the specifics of Gen AI’s role in data engineering and see where it flourishes, where it requires enhancement, and where human expertise remains irreplaceable. Areas of Strength: Basic Data Querying: 100% the human necessity is going to get disrupted, but the severity based on the complexity is high. Even the SQL practitioners won’t feel much difference here, and self-serve analytics will catch fire in this area which is something phenomenal! Again, to quote positively, data engineers won’t need to guide the stakeholders nearly as much! Troubleshooting Pipeline Failures: LLMs coupled with agents will slash on-call load massively. LLMs processing stack traces/quality failures can recommend the built-in remedies and nudge the ball down the field to address the problem, presumably even over Slack. And that is a fantastic percentage of data engineering hours saved! To be clear, some hard failures require manual troubleshooting. Anomaly Detection: Regardless of the structure, format, source, complexity, timeliness, or even natural play of data, large language models can identify anomalies. LLMs are well-suited to anomaly identification because they can work across a variety of data sources, identify subtle patterns, and distinguish when data isn’t behaving as expected. This will help data engineers to identify and fix data quality problems in advance. Areas for Enhancement: Data Cleansing: Our results suggest that Language Models (LLMs) are highly effective in data cleansing due to their high performance in unstructured data management and semantic error identification and correction, as well as high scalability. Furthermore, our review of the current state-of-the-art suggests that even more substantial improvements are possible, including fine-tuning of LLMs to specific domains or even organization data. In addition, various interactive mechanisms as well as coupling with data quality frameworks can significantly increase the efficiency of LLMs. Overall, LLMs allow for organizing and improving the whole process of data cleansing, helping to obtain high-quality datasets, and, consequently, valuable insights. Visualization and Report Generation: Language Models (LLMs) excel in visualization and documentation tasks by automating the creation of reports, summarizing data insights, and generating narrative-driven reports. Enhancements needed include improving document organization and categorization, data-driven storytelling capabilities integrating with version control systems and visualization tools for seamless output generation, and enhancing interpretability features to ensure clarity and coherence in reports. Writing Pipeline Code in SQL, Spark, or Flink LLM can be a helpful starting point, and for our work, it is a good boilerplate. Still, the generated material is hard to debug — or often not, worth the trouble. Prompt-driven content is still far from being able to turn out a nice, optimized, and absolutely accurate data pipeline. Optimization By providing suggestions on efficient query structures and detecting problems that slow performance, LLMs are especially powerful when it comes to SQL optimization. They can even make recommendations for optimizations on the basis of historical query data. Things for improvement include integrating database-specific optimization techniques into the training of LLM, bridging with query execution plans in order to give context-oriented advice and feedback mechanisms so that one can modify strategies for optimization according to what users prefer as well as performance metrics. Physical Data Model As soon as the logical model is finalized, LLM will be efficient in moving and upgrading this logical (or conceptual) data model into the targeted architecture. The problem that LLM encounters with all the examples is that it’s hard for most people to understand the pipeline, table, and its relationship. Areas Where Human Expertise Remains Irreplaceable: Logical Data Model Data modeling is a very soft skills-focused task. You have to communicate with different stakeholders to understand the business context in detail. Understanding what data is needed, the relationship between entities, and considering different scenarios are human-oriented tasks that LLMs must continue to struggle with. Building Pipeline and Framework Once they reach a certain level of complexity, LLMs begin to give up. Imagine if someone asked ChatGPT, “Can you provide me the source code of Android’s next version?” While LLMs can help with routine data engineering tasks, they do not have the insight or inventiveness unique to humans that allows for new solutions to complex challenges, unlocking creativity in technical terms. Domain Expertise and Intuition: Human data engineers bring a unique blend of domain expertise and intuition to their work that often surpasses what conventional software isn’t able to achieve through automation. This intuition allows them to find subtle patterns in data that no fully rigorous automated system can. Based on their knowledge of this field and their experiences in it, they can predict future trends. They can also make decisions in light of a broader context, including corporate or government needs, ethical considerations, and potential future scenarios. This holistic approach to data engineering surpasses what LLMs have achieved. Although LLMs have great power, they are typically restricted to the patterns and relationships they have been trained to recognize. Conclusion: On the whole, Gen AI can certainly automate trivial procedures such as looking for information, launching programs that don’t work properly, repeatedly correcting faults, and anomaly detection. My gut tells me that Gen AI will win out and excel at tasks such as Data Cleansing, Optimization, and Writing Pipelines — once the team understands gaps and missing patterns. But it can not learn purely human soft skills that are important for building logical data models or a framework. I believe that these skills, which cannot be automated, are also essential for stakeholders to ask for innovation in the first place. After all, no one ever asked Steve Jobs if they needed anything like an iPhone; he just thought up what would become its invention. References: https://barrmoses.medium.com/will-genai-replace-data-engineers-no-and-heres-why-708b0a27da6b ​​__https://www.linkedin.com/pulse/navigating-data-governance-challenges-era-large-fnq5e__ https://www.dataversity.net/navigating-the-risks-of-llm-ai-tools-for-data-governance/ https://www.skyflow.com/post/why-ai-governance-requires-data-governance https://coreykeyser.medium.com/you-cant-govern-ai-without-governing-data-27bb88d8f9ea https://www.ankursnewsletter.com/p/gpt-4-gpt-3-and-gpt-35-turbo-a-review https://towardsdatascience.com/from-chaos-to-clarity-streamlining-data-cleansing-using-large-language-models-a539fa0b2d90 https://medium.com/@wangshally11/data-cleaning-warm-up-before-training-large-language-models-74ed1edceead Introduction: Ever since the buzz about GenAI and ChatGPT, I have been trying to understand the space and leveraging it into my day-to-day activities as a Data Engineer. No doubt it has been useful for debugging with respective programming and documentation. Personally, it played a significant role in helping me plan my Dubai itinerary. It even contributed to naming my friend’s daughter. However, it works pretty well if you give appropriate and precise requirements. There is a lot of anxiety among people that AI is going to take our jobs as they feel almost everything will be automated through AI. Is LLM as good as everyone claims? In this article, we will look into the specifics of Gen AI’s role in data engineering and see where it flourishes, where it requires enhancement, and where human expertise remains irreplaceable. Areas of Strength: Basic Data Querying: 100% the human necessity is going to get disrupted, but the severity based on the complexity is high. Even the SQL practitioners won’t feel much difference here, and self-serve analytics will catch fire in this area which is something phenomenal! Again, to quote positively, data engineers won’t need to guide the stakeholders nearly as much! Troubleshooting Pipeline Failures: LLMs coupled with agents will slash on-call load massively. LLMs processing stack traces/quality failures can recommend the built-in remedies and nudge the ball down the field to address the problem, presumably even over Slack. And that is a fantastic percentage of data engineering hours saved! To be clear, some hard failures require manual troubleshooting. Anomaly Detection: Regardless of the structure, format, source, complexity, timeliness, or even natural play of data, large language models can identify anomalies. LLMs are well-suited to anomaly identification because they can work across a variety of data sources, identify subtle patterns, and distinguish when data isn’t behaving as expected. This will help data engineers to identify and fix data quality problems in advance. Areas for Enhancement: Data Cleansing: Our results suggest that Language Models (LLMs) are highly effective in data cleansing due to their high performance in unstructured data management and semantic error identification and correction, as well as high scalability. Furthermore, our review of the current state-of-the-art suggests that even more substantial improvements are possible, including fine-tuning of LLMs to specific domains or even organization data. In addition, various interactive mechanisms as well as coupling with data quality frameworks can significantly increase the efficiency of LLMs. Overall, LLMs allow for organizing and improving the whole process of data cleansing, helping to obtain high-quality datasets, and, consequently, valuable insights. Visualization and Report Generation: Language Models (LLMs) excel in visualization and documentation tasks by automating the creation of reports, summarizing data insights, and generating narrative-driven reports. Enhancements needed include improving document organization and categorization, data-driven storytelling capabilities integrating with version control systems and visualization tools for seamless output generation, and enhancing interpretability features to ensure clarity and coherence in reports. Writing Pipeline Code in SQL, Spark, or Flink LLM can be a helpful starting point, and for our work, it is a good boilerplate. Still, the generated material is hard to debug — or often not, worth the trouble. Prompt-driven content is still far from being able to turn out a nice, optimized, and absolutely accurate data pipeline. Optimization By providing suggestions on efficient query structures and detecting problems that slow performance, LLMs are especially powerful when it comes to SQL optimization. They can even make recommendations for optimizations on the basis of historical query data. Things for improvement include integrating database-specific optimization techniques into the training of LLM, bridging with query execution plans in order to give context-oriented advice and feedback mechanisms so that one can modify strategies for optimization according to what users prefer as well as performance metrics. Physical Data Model As soon as the logical model is finalized, LLM will be efficient in moving and upgrading this logical (or conceptual) data model into the targeted architecture. The problem that LLM encounters with all the examples is that it’s hard for most people to understand the pipeline, table, and its relationship. Areas Where Human Expertise Remains Irreplaceable: Logical Data Model Data modeling is a very soft skills-focused task. You have to communicate with different stakeholders to understand the business context in detail. Understanding what data is needed, the relationship between entities, and considering different scenarios are human-oriented tasks that LLMs must continue to struggle with. Building Pipeline and Framework Once they reach a certain level of complexity, LLMs begin to give up. Imagine if someone asked ChatGPT, “Can you provide me the source code of Android’s next version?” While LLMs can help with routine data engineering tasks, they do not have the insight or inventiveness unique to humans that allows for new solutions to complex challenges, unlocking creativity in technical terms. Domain Expertise and Intuition: Human data engineers bring a unique blend of domain expertise and intuition to their work that often surpasses what conventional software isn’t able to achieve through automation. This intuition allows them to find subtle patterns in data that no fully rigorous automated system can. Based on their knowledge of this field and their experiences in it, they can predict future trends. They can also make decisions in light of a broader context, including corporate or government needs, ethical considerations, and potential future scenarios. This holistic approach to data engineering surpasses what LLMs have achieved. Although LLMs have great power, they are typically restricted to the patterns and relationships they have been trained to recognize. Conclusion: On the whole, Gen AI can certainly automate trivial procedures such as looking for information, launching programs that don’t work properly, repeatedly correcting faults, and anomaly detection. My gut tells me that Gen AI will win out and excel at tasks such as Data Cleansing, Optimization, and Writing Pipelines — once the team understands gaps and missing patterns. But it can not learn purely human soft skills that are important for building logical data models or a framework. I believe that these skills, which cannot be automated, are also essential for stakeholders to ask for innovation in the first place. After all, no one ever asked Steve Jobs if they needed anything like an iPhone; he just thought up what would become its invention. References: https://barrmoses.medium.com/will-genai-replace-data-engineers-no-and-heres-why-708b0a27da6b https://barrmoses.medium.com/will-genai-replace-data-engineers-no-and-heres-why-708b0a27da6b https://barrmoses.medium.com/will-genai-replace-data-engineers-no-and-heres-why-708b0a27da6b ​​__ https://www.linkedin.com/pulse/navigating-data-governance-challenges-era-large-fnq5e __ https://www.linkedin.com/pulse/navigating-data-governance-challenges-era-large-fnq5e https://www.dataversity.net/navigating-the-risks-of-llm-ai-tools-for-data-governance/ https://www.dataversity.net/navigating-the-risks-of-llm-ai-tools-for-data-governance/ https://www.dataversity.net/navigating-the-risks-of-llm-ai-tools-for-data-governance/ https://www.skyflow.com/post/why-ai-governance-requires-data-governance https://www.skyflow.com/post/why-ai-governance-requires-data-governance https://www.skyflow.com/post/why-ai-governance-requires-data-governance https://coreykeyser.medium.com/you-cant-govern-ai-without-governing-data-27bb88d8f9ea https://coreykeyser.medium.com/you-cant-govern-ai-without-governing-data-27bb88d8f9ea https://coreykeyser.medium.com/you-cant-govern-ai-without-governing-data-27bb88d8f9ea https://www.ankursnewsletter.com/p/gpt-4-gpt-3-and-gpt-35-turbo-a-review https://www.ankursnewsletter.com/p/gpt-4-gpt-3-and-gpt-35-turbo-a-review https://www.ankursnewsletter.com/p/gpt-4-gpt-3-and-gpt-35-turbo-a-review https://towardsdatascience.com/from-chaos-to-clarity-streamlining-data-cleansing-using-large-language-models-a539fa0b2d90 https://towardsdatascience.com/from-chaos-to-clarity-streamlining-data-cleansing-using-large-language-models-a539fa0b2d90 https://towardsdatascience.com/from-chaos-to-clarity-streamlining-data-cleansing-using-large-language-models-a539fa0b2d90 https://medium.com/@wangshally11/data-cleaning-warm-up-before-training-large-language-models-74ed1edceead https://medium.com/@wangshally11/data-cleaning-warm-up-before-training-large-language-models-74ed1edceead https://medium.com/@wangshally11/data-cleaning-warm-up-before-training-large-language-models-74ed1edceead

LLMs: An Assessment From a Data Engineer

In a world where technology is constantly evolving, the Pebble Tracker by IoTeX stands out as a remarkable innovation. Recently, I had the opportunity to experience this blockchain-powered gadget firsthand, and I must say that it has exceeded my expectations. It was relatively easy to set up, and if you are a geek like me and are into data visualization and management, it is fun to use. It also clearly holds a lot of potential for business applications in the emerging spaces of web3 and decentralized physical infrastructure networks (DePin). What is Pebble Tracker? Pebble Tracker is a state-of-the-art IoT (Internet of Things) device developed by IoTeX. This small yet powerful piece of technology is designed to capture real-world data in real time, making it an ideal tool for tracking various environmental and locational parameters. Whether you're monitoring the climate, tracking movement, or verifying location data, the Pebble Tracker has you covered. Seamless Registration and Integration One of the standout features of the Pebble Tracker is its ease of use. Upon receiving my device, I quickly registered it and joined the MachineFi ecosystem, a decentralized network that allows users to monetize their data. The registration process was straightforward, and within minutes, my device was up and running, ready to capture and share data. However, it's important to note that the Pebble Tracker requires a separate SIM card to operate, which adds an additional step to the setup process. Capturing Real-World Data The Pebble Tracker's capabilities are impressive. It offers verifiable data on GPS location, climate conditions, motion, and light levels. This data is crucial for various applications, from logistics and supply chain management to personal fitness and environmental monitoring. The real-time data capture ensures that you always have the most current information at your fingertips. Why I Love Pebble Tracker Blockchain-Powered Security: The integration of blockchain technology ensures that the data captured by the Pebble Tracker is secure and verifiable. This added layer of security is particularly important for applications that require trustworthy data.
Real-Time Data: The ability to capture and analyze data in real-time opens up numerous possibilities for applications that depend on timely information. Whether it's tracking the movement of goods in a supply chain or monitoring environmental conditions, the Pebble Tracker delivers accurate and timely data.
Data Monetization: By joining the MachineFi ecosystem, I can earn rewards for the data my device captures. This innovative approach not only incentivizes data sharing but also ensures that users retain control over their data.
Versatility: The Pebble Tracker's ability to capture various types of data—GPS, climate, motion, and light—makes it a versatile tool for a wide range of applications. From personal use to industrial applications, the possibilities are endless. Practical Applications The practical applications of the Pebble Tracker are vast. Here are a few examples of how this device can be utilized: Logistics and Supply Chain Management: Track the location and condition of goods in transit, ensuring they reach their destination in optimal condition. This capability can improve efficiency, reduce losses, and enhance transparency in supply chain operations.
Environmental Monitoring: Monitor climate conditions in real time, providing valuable data for weather forecasting, environmental research, and disaster management. Such data can be crucial for understanding climate patterns and making informed decisions to mitigate environmental impacts.
Personal Fitness: Track your movements and activities, gaining insights into your fitness routines and progress. The Pebble Tracker can help users monitor their health metrics, set fitness goals, and track their achievements over time.
Security and Surveillance: Use the device to monitor and secure sensitive areas, ensuring that any unauthorized movements are detected and recorded. This application can be vital for enhancing security in homes, offices, and public spaces.
Asset Tracking: Beyond logistics, the Pebble Tracker can be used to track valuable assets, whether they are stationary or in transit. This can be particularly useful for industries like construction, where equipment and tools need to be monitored continuously. Final Thoughts I believe that the Pebble Tracker by IoTeX is a game-changer in the world of IoT devices. Its integration of blockchain technology for secure data capture, combined with its real-time data capabilities and versatility, makes it a must-have for anyone looking to harness the power of real-world data. Whether you're a tech enthusiast, a business owner, or someone looking to explore the possibilities of IoT, the Pebble Tracker is something to explore. Moreover, the device's potential extends beyond individual applications. As IoT and blockchain technologies continue to converge, tools like the Pebble Tracker are paving the way for more decentralized, secure, and efficient data ecosystems. This not only enhances individual capabilities but also contributes to broader technological advancements and innovation. For more information about the Pebble Tracker, its setup, and where to purchase a compatible SIM card, check out these links: Pebble Tracker Information
Pebble Tracker Setup Guide
Compatible SIM Card Purchase In a world where technology is constantly evolving, the Pebble Tracker by IoTeX stands out as a remarkable innovation. Recently, I had the opportunity to experience this blockchain-powered gadget firsthand, and I must say that it has exceeded my expectations. It was relatively easy to set up, and if you are a geek like me and are into data visualization and management, it is fun to use. It also clearly holds a lot of potential for business applications in the emerging spaces of web3 and decentralized physical infrastructure networks (DePin). web3 decentralized physical infrastructure networks What is Pebble Tracker? Pebble Tracker is a state-of-the-art IoT (Internet of Things) device developed by IoTeX. This small yet powerful piece of technology is designed to capture real-world data in real time, making it an ideal tool for tracking various environmental and locational parameters. Whether you're monitoring the climate, tracking movement, or verifying location data, the Pebble Tracker has you covered. Seamless Registration and Integration One of the standout features of the Pebble Tracker is its ease of use. Upon receiving my device, I quickly registered it and joined the MachineFi ecosystem, a decentralized network that allows users to monetize their data. The registration process was straightforward, and within minutes, my device was up and running, ready to capture and share data. However, it's important to note that the Pebble Tracker requires a separate SIM card to operate, which adds an additional step to the setup process. Capturing Real-World Data The Pebble Tracker's capabilities are impressive. It offers verifiable data on GPS location, climate conditions, motion, and light levels. This data is crucial for various applications, from logistics and supply chain management to personal fitness and environmental monitoring. The real-time data capture ensures that you always have the most current information at your fingertips. Why I Love Pebble Tracker Blockchain-Powered Security: The integration of blockchain technology ensures that the data captured by the Pebble Tracker is secure and verifiable. This added layer of security is particularly important for applications that require trustworthy data. Real-Time Data: The ability to capture and analyze data in real-time opens up numerous possibilities for applications that depend on timely information. Whether it's tracking the movement of goods in a supply chain or monitoring environmental conditions, the Pebble Tracker delivers accurate and timely data. Data Monetization: By joining the MachineFi ecosystem, I can earn rewards for the data my device captures. This innovative approach not only incentivizes data sharing but also ensures that users retain control over their data. Versatility: The Pebble Tracker's ability to capture various types of data—GPS, climate, motion, and light—makes it a versatile tool for a wide range of applications. From personal use to industrial applications, the possibilities are endless. Blockchain-Powered Security: The integration of blockchain technology ensures that the data captured by the Pebble Tracker is secure and verifiable. This added layer of security is particularly important for applications that require trustworthy data. Blockchain-Powered Security: Real-Time Data: The ability to capture and analyze data in real-time opens up numerous possibilities for applications that depend on timely information. Whether it's tracking the movement of goods in a supply chain or monitoring environmental conditions, the Pebble Tracker delivers accurate and timely data. Real-Time Data: Data Monetization: By joining the MachineFi ecosystem, I can earn rewards for the data my device captures. This innovative approach not only incentivizes data sharing but also ensures that users retain control over their data. Data Monetization: Versatility: The Pebble Tracker's ability to capture various types of data—GPS, climate, motion, and light—makes it a versatile tool for a wide range of applications. From personal use to industrial applications, the possibilities are endless. Versatility: Practical Applications The practical applications of the Pebble Tracker are vast. Here are a few examples of how this device can be utilized: Logistics and Supply Chain Management: Track the location and condition of goods in transit, ensuring they reach their destination in optimal condition. This capability can improve efficiency, reduce losses, and enhance transparency in supply chain operations. Environmental Monitoring: Monitor climate conditions in real time, providing valuable data for weather forecasting, environmental research, and disaster management. Such data can be crucial for understanding climate patterns and making informed decisions to mitigate environmental impacts. Personal Fitness: Track your movements and activities, gaining insights into your fitness routines and progress. The Pebble Tracker can help users monitor their health metrics, set fitness goals, and track their achievements over time. Security and Surveillance: Use the device to monitor and secure sensitive areas, ensuring that any unauthorized movements are detected and recorded. This application can be vital for enhancing security in homes, offices, and public spaces. Asset Tracking: Beyond logistics, the Pebble Tracker can be used to track valuable assets, whether they are stationary or in transit. This can be particularly useful for industries like construction, where equipment and tools need to be monitored continuously. Logistics and Supply Chain Management: Track the location and condition of goods in transit, ensuring they reach their destination in optimal condition. This capability can improve efficiency, reduce losses, and enhance transparency in supply chain operations. Logistics and Supply Chain Management: Environmental Monitoring: Monitor climate conditions in real time, providing valuable data for weather forecasting, environmental research, and disaster management. Such data can be crucial for understanding climate patterns and making informed decisions to mitigate environmental impacts. Environmental Monitoring: Personal Fitness: Track your movements and activities, gaining insights into your fitness routines and progress. The Pebble Tracker can help users monitor their health metrics, set fitness goals, and track their achievements over time. Personal Fitness: Security and Surveillance: Use the device to monitor and secure sensitive areas, ensuring that any unauthorized movements are detected and recorded. This application can be vital for enhancing security in homes, offices, and public spaces. Security and Surveillance: Asset Tracking: Beyond logistics, the Pebble Tracker can be used to track valuable assets, whether they are stationary or in transit. This can be particularly useful for industries like construction, where equipment and tools need to be monitored continuously. Asset Tracking: Final Thoughts I believe that the Pebble Tracker by IoTeX is a game-changer in the world of IoT devices. Its integration of blockchain technology for secure data capture, combined with its real-time data capabilities and versatility, makes it a must-have for anyone looking to harness the power of real-world data. Whether you're a tech enthusiast, a business owner, or someone looking to explore the possibilities of IoT, the Pebble Tracker is something to explore. Moreover, the device's potential extends beyond individual applications. As IoT and blockchain technologies continue to converge, tools like the Pebble Tracker are paving the way for more decentralized, secure, and efficient data ecosystems. This not only enhances individual capabilities but also contributes to broader technological advancements and innovation. For more information about the Pebble Tracker, its setup, and where to purchase a compatible SIM card, check out these links: Pebble Tracker Information Pebble Tracker Setup Guide Compatible SIM Card Purchase Pebble Tracker Information Pebble Tracker Information Pebble Tracker Setup Guide Pebble Tracker Setup Guide Compatible SIM Card Purchase Compatible SIM Card Purchase

Discovering the Capabilities of IoTeX's Pebble Tracker

Inconsistencies Found in Craig Wright’s MYOB Bitcoin Transactions

Your Guide For Overcoming Procrastination and Getting Down to Work

Staying One Step Ahead: How Fintechs and Financial Institutions Can Outsmart Fraudsters

The Declining Critical Thinking Skills: From Artificial Intelligence to Average Intelligence

Singularity: Streamlining Game Development with a Universal Backend Framework

এককতা: একটি ইউনিভার্সাল ব্যাকএন্ড ফ্রেমওয়ার্ক সহ গেম ডেভেলপমেন্টকে স্ট্রীমলাইন করা

Singularity: Optimierte Spieleentwicklung mit einem universellen Backend-Framework

Singularidad: agilización del desarrollo de juegos con un marco de backend universal

Singularity : rationaliser le développement de jeux avec un framework backend universel

सिंगलेरिटी: यूनिवर्सल बैकएंड फ्रेमवर्क के साथ गेम डेवलपमेंट को सुव्यवस्थित करना

Singularity: ユニバーサル バックエンド フレームワークによるゲーム開発の効率化

Singularity: 범용 백엔드 프레임워크로 게임 개발 간소화

Singularidade: simplificando o desenvolvimento de jogos com uma estrutura de back-end universal

Singularity: оптимизация разработки игр с помощью универсальной серверной платформы

Tekillik: Evrensel Arka Uç Çerçevesiyle Oyun Geliştirmeyi Kolaylaştırma

Điểm kỳ dị: Hợp lý hóa quá trình phát triển trò chơi với Khung phụ trợ phổ quát

Singularity：使用通用后端框架简化游戏开发

Craig Wright's Tangled Web of Lies in Bitcoin's Origin Story

The rideshare and delivery markets are undergoing an upheaval driven by rapid technological advancements and shifting consumer behaviors. Companies like Wave are surfing this change with bespoke artificial intelligence (AI) technology, carving out a competitive edge in a burgeoning industry. As the market expands, opportunities abound for those willing to adapt. Wave’s own personal brand of AI-driven safety and community involvement has positioned it quite advantageously, taking the market by storm in U.S. cities like Atlanta and Chicago. The Expanding U.S. Sector The global rideshare market is projected to reach $335 billion by 2025, growing at a compound annual growth rate (CAGR) of 18.2% from 2020 to 2025. This growth is fueled by increasing urbanization, the rising preference for shared mobility, and the convenience of on-demand services. Similarly, the online food delivery market is expected to surpass $213 billion by 2030. This explosive expansion is primarily driven by the proliferation of platform-to-consumer services and the lasting impact of the COVID-19 pandemic. In the United States, DoorDash leads the food delivery market with a 67% market share, followed by Uber Eats with 23%. The intense competition among these giants has focused on efficiency and customer experience, with companies investing heavily in AI and automation to streamline operations and reduce costs. "AI has changed the rules of the game. Not only in transportation or food delivery but every other aspect of the industry as well," says Diondre Lewis, CEO of Wave. "At Wave, AI has enabled us to optimize routes, predict demand, enhance safety, and provide better customer support." Room for Growth in the Markets The rideshare and delivery markets present numerous opportunities for savvy businesses looking to capitalize on recent technological developments. One among these trends is the increasing efficiency of last-mile delivery, which now represents 53% of the total cost of transportation. Companies are exploring various technologies, including AI, autonomous vehicles, and crowdsourcing, to reduce these costs and improve delivery times. Autonomous vehicles, including drones, are also becoming a viable solution for last-mile deliveries, offering the potential to cut costs and enhance efficiency significantly. This trend is expected to gain momentum as technology advances and regulatory frameworks evolve, addressing labor shortages and improving service efficiency. Another opportunity lies in the growing demand for personalized and efficient delivery services. AI-powered platforms can analyze vast amounts of data to provide personalized recommendations, optimize delivery routes, and predict peak demand times, much like Wave itself does. "The name of the game is customer satisfaction. There is no better way to meet the varied demands of our clients than with machine learning. We offer services from food delivery to corporate rideshares and non-emergency medical transport," Lewis explains. The Role of AI in Shaping the Future AI technology is credited with most of the transformation in the rideshare and delivery markets. Companies increasingly rely on AI to optimize their operations, improve safety, and provide personalized services. Wave's AI-powered platform is the very epitome of the potential AI presents. The company's proprietary AI algorithms, such as dynamic micro-zone demand prediction and real-time optimal route adjustment, aid drivers with picking the most efficient paths, reducing fuel consumption and wait times. These artificial intelligence algorithms are also utilized in Wave’s steadfast focus on safety. The algorithm analyzes vehicular operation to suggest the best time to perform routine maintenance and through automated disturbance or vehicular accident detection. Wave's Technological Potential Wave has carefully positioned itself to capitalize on these market opportunities. Since its inception, the company has focused on underserved markets, such as non-emergency medical transport and exclusive event transit. This allows it to tap into niche segments that larger competitors often overlook. "Beyond profit, Wave stands for serving those groups often forgotten by bigger companies. We even offer services for transportation of young children, with the requisite safety measures and monitoring in place," Lewis says. As consumer preferences shift toward shared mobility and on-demand services, Wave readies itself for further expansion. The rideshare and delivery markets are ripe with opportunities for companies willing to evolve. Wave's drive to further build upon its bespoke AI platform positions it as a formidable contender in the market. This piece was published as part of HackerNoon’s Business Blogging Program. For more details, please click here. The rideshare and delivery markets are undergoing an upheaval driven by rapid technological advancements and shifting consumer behaviors. Companies like Wave are surfing this change with bespoke artificial intelligence (AI) technology, carving out a competitive edge in a burgeoning industry. Wave Wave As the market expands, opportunities abound for those willing to adapt. Wave’s own personal brand of AI-driven safety and community involvement has positioned it quite advantageously, taking the market by storm in U.S. cities like Atlanta and Chicago. The Expanding U.S. Sector The Expanding U.S. Sector The global rideshare market is projected to reach $335 billion by 2025, growing at a compound annual growth rate (CAGR) of 18.2% from 2020 to 2025. This growth is fueled by increasing urbanization, the rising preference for shared mobility, and the convenience of on-demand services. Similarly, the online food delivery market is expected to surpass $213 billion by 2030. This explosive expansion is primarily driven by the proliferation of platform-to-consumer services and the lasting impact of the COVID-19 pandemic. In the United States, DoorDash leads the food delivery market with a 67% market share, followed by Uber Eats with 23%. The intense competition among these giants has focused on efficiency and customer experience, with companies investing heavily in AI and automation to streamline operations and reduce costs. " AI has changed the rules of the game. Not only in transportation or food delivery but every other aspect of the industry as well, " says Diondre Lewis, CEO of Wave. " At Wave, AI has enabled us to optimize routes, predict demand, enhance safety, and provide better customer support. " AI has changed the rules of the game. Not only in transportation or food delivery but every other aspect of the industry as well, At Wave, AI has enabled us to optimize routes, predict demand, enhance safety, and provide better customer support. Room for Growth in the Markets Room for Growth in the Markets The rideshare and delivery markets present numerous opportunities for savvy businesses looking to capitalize on recent technological developments. One among these trends is the increasing efficiency of last-mile delivery, which now represents 53% of the total cost of transportation. Companies are exploring various technologies, including AI, autonomous vehicles, and crowdsourcing, to reduce these costs and improve delivery times. Autonomous vehicles, including drones, are also becoming a viable solution for last-mile deliveries, offering the potential to cut costs and enhance efficiency significantly. This trend is expected to gain momentum as technology advances and regulatory frameworks evolve, addressing labor shortages and improving service efficiency. Another opportunity lies in the growing demand for personalized and efficient delivery services. AI-powered platforms can analyze vast amounts of data to provide personalized recommendations, optimize delivery routes, and predict peak demand times, much like Wave itself does. " The name of the game is customer satisfaction. There is no better way to meet the varied demands of our clients than with machine learning. We offer services from food delivery to corporate rideshares and non-emergency medical transport ," Lewis explains. The name of the game is customer satisfaction. There is no better way to meet the varied demands of our clients than with machine learning. We offer services from food delivery to corporate rideshares and non-emergency medical transport The Role of AI in Shaping the Future The Role of AI in Shaping the Future AI technology is credited with most of the transformation in the rideshare and delivery markets. Companies increasingly rely on AI to optimize their operations, improve safety, and provide personalized services. Wave's AI-powered platform is the very epitome of the potential AI presents. The company's proprietary AI algorithms, such as dynamic micro-zone demand prediction and real-time optimal route adjustment, aid drivers with picking the most efficient paths, reducing fuel consumption and wait times. These artificial intelligence algorithms are also utilized in Wave’s steadfast focus on safety. The algorithm analyzes vehicular operation to suggest the best time to perform routine maintenance and through automated disturbance or vehicular accident detection. Wave's Technological Potential Wave's Technological Potential Wave has carefully positioned itself to capitalize on these market opportunities. Since its inception, the company has focused on underserved markets, such as non-emergency medical transport and exclusive event transit. This allows it to tap into niche segments that larger competitors often overlook. " Beyond profit, Wave stands for serving those groups often forgotten by bigger companies. We even offer services for transportation of young children, with the requisite safety measures and monitoring in place ," Lewis says. Beyond profit, Wave stands for serving those groups often forgotten by bigger companies. We even offer services for transportation of young children, with the requisite safety measures and monitoring in place As consumer preferences shift toward shared mobility and on-demand services, Wave readies itself for further expansion. The rideshare and delivery markets are ripe with opportunities for companies willing to evolve. Wave's drive to further build upon its bespoke AI platform positions it as a formidable contender in the market. This piece was published as part of HackerNoon’s Business Blogging Program. For more details, please click here. This piece was published as part of HackerNoon’s Business Blogging Program. For more details, please click here . here here

Wave's AI-Based Innovations: The Key to Dominating the Rideshare and Delivery Market

ওয়েভের এআই-ভিত্তিক উদ্ভাবন: রাইডশেয়ার এবং ডেলিভারি বাজারে আধিপত্য বিস্তারের চাবিকাঠি

KI-basierte Innovationen von Wave: Der Schlüssel zur Beherrschung des Rideshare- und Liefermarkts

Innovaciones basadas en inteligencia artificial de Wave: la clave para dominar el mercado de viajes compartidos y entregas

Les innovations basées sur l'IA de Wave : la clé pour dominer le marché du covoiturage et de la livraison

वेव के एआई-आधारित नवाचार: राइडशेयर और डिलीवरी बाजार पर हावी होने की कुंजी

Wave の AI ベースのイノベーション: ライドシェアと配送市場を支配する鍵

Wave의 AI 기반 혁신: 차량 공유 및 배달 시장을 지배하는 열쇠

Inovações baseadas em IA da Wave: a chave para dominar o mercado de transporte compartilhado e entrega

Инновации Wave на основе искусственного интеллекта: ключ к доминированию на рынке совместных поездок и доставки

Wave'in Yapay Zeka Tabanlı Yenilikleri: Araç Paylaşımı ve Teslimat Pazarına Hakim Olmanın Anahtarı

Những đổi mới dựa trên AI của Wave: Chìa khóa để thống trị thị trường giao hàng và chia sẻ xe

Wave 基于人工智能的创新：主宰拼车和配送市场的关键

It is safe to describe the invention of smart contracts as one of the most significant milestones in web3 and cryptography — after Bitcoin! After all, much of what is now known as the DeFi ecosystem owes its existence to smart contract functionalities, powering a host of decentralized applications (DApps). The keypoint about smart contracts is that they are self-executing agreements stored on a blockchain. They automatically enforce their terms when predefined conditions are met. Smart contracts have come a long way since they were first proposed in 1994 by the renowned American computer scientist, Nick Szabo, such that 19 years later the Ethereum blockchain emerged as the first smart contract platform popularizing the idea of a self-executing blockchain program. In a world where the mass of humanity seek to break free of centralized control, smart contract technology offers a secure and transparent way to conduct transactions without the need for intermediaries. However, despite its level of sophistication, it has remained a subject of cyber security attacks. The DAO hack of 2016, for example,is a stark reminder of what can happen when a major flaw is exploited in a smart contract. Additionally, deploying a smart on a blockchain requires a huge amount of computation and data storage. This often leads to a high transaction fee and the need to keep the network running means that miners or validators are compensated with it. But contending with a high transaction fee can create a significant barrier the adoption of this technology. This is best imagined in a scenario where people have to pay hefty fees for transactions (i.e. buying a cup of coffee with cryptocurrency or an NFT). It not only discourages mass adoption but also hinders the growth of smart contract application across various industries. This bring us to the concept of feeless smart contracts, which is often touted as a potential solution to eliminate transaction fees entirely. Can a zero-fee smart contract unlock a new era of accessibility within the blockchain ecosystem? Let’s find out! Unpacking Feeless Smart Contracts In the realm of blockchain technology, the concept of a feeless smart contract platform has attracted a significant amount of attention. This is due to the fact that it promises to not only revolutionize how we interact with decentralized applications (dApps) but also seeks to entirely reshape smart contract technology. However, the realization of a truly feeless blockchain ecosystem can be best described as a work in a progress , with blockchain experts exploring potential solutions that can help solve the current challenges hindering it. The amount of attention it continues to command in the blockchain space has not only made feeless smart contract technology an area of ongoing research and development, but it has also facilitated the emergence of   pragmatic approaches such as proof-of-work with burning, layered architectures and proof-of-stake (PoS) consensus mechanism. Proof-of-Work (PoW) With Burning: Proof-of-work with burning is a combination of the proof-of-work (PoW) consensus mechanism and the routine practice of burning of a token to drive its scarcity. The idea behind this approach is to allow miners to earn tokens that are burned (i.e. kept out of circulation) when used for transactions. However, this solution is criticized because of the deflationary effect it creates. It is also not considered a sustainable model because critics believe that miner rewards might become insufficient and the network security jeopardized, if tokens are burned too quickly. Proof-of-Stake(PoS) Consensus Mechanisms: The proof-of-stake (PoS) consensus mechanism emerged as a viable alternative to the proof-of-work (PoW) mechanism and it has gained a significant amount of attention in the industry. Leading blockchain protocols such as Solana, Cardano, Polkadot, etc leverage this approach to PoW mainly because it requires less energy consumption and it is eco-friendly. However, it is important to note that it is not entirely feeless as a very insignificant amount of transaction fee is usually required for keep the network running. Layered Architectures: In a layered architecture, the base layer is designed to handle the security and consensus mechanism of the blockchain, while the fee layer is designed to enable the execution of smart contract. This approach is often deployed by top protocols such as Cosmos and Polkadot as it creates room for a more flexible fee increasing the chances of feeless transactions on the smart contract layer. Qubic Protocol As a Case Study Qubic is an AI blockchain ecosystem pioneering innovation in feeless smart contract in a quest to eliminate the transaction fees often associated with deploying smart contract on other platforms. To achieve this feat Qubic protocol proposes a Proof-of-Work(PoW)model with a twist: burning. Similar to Proof-of-Work mechanisms, miners compete to solve complex puzzles ad secure the Qubic network. However, instead of receiving cryptocurrency, miners are rewarded with Qubic Units, the native token of the protocol recently listed on MEXC in tandem with its 2024 road map. Its proposed solution allows users who want to execute a smart contract to BURN a specific amount of QUs, instead of paying a hefty transaction fee. This burning mechanism then removes the burned QUs from circulation, fostering a potential scarcity to increase the value of the remaining tokens. However, since Proof-of-Work(PoW) mechanisms are often criticized for their high energy consumption, Qubic needs to navigate this obstacle to create a truly feeless ecosystem. Nonetheless, Qubic’s burning POW model presents a novel approach in the development of feeless smart contract. The Challenges of Feeless Smart Contracts When it comes to feeless smart contract technology, there is a thin line between hype and reality. This is why it is important to first acknowledge that it is an emerging technology and not a one-size-fit-all solution to the high transaction fee that many blockchain protocols continue to contend with. In essence, it is crucial to state that feeless smart contract technology  faces a unique set of of challenges such as security, sustainability and scalability. Sustainability Building a feeless smart contract is not enough. It must be sustainable in the long run. As a matter of fact,its sustainability lies in its ability to function on a secure and decentralized blockchain protocol. There is also the need to create and maintain sufficient incentives for miners or validators in order to run and secure  the network. Security Smart contract audit is a routine practice of checking for vulnerabilities in code. This is an industry standard procedure that is required to minimize potential cyber security risks. It is hinged on the premise that blockchain protocols are not immune from cyber attacks, which can result in substantial financial loss. In order to address a potential security risk that may arise,it is crucial for a feeless smart contract to undergo a regular smart audit  as it can help to uncover security flaw in its code. Scalability Scalability has been recognized as one of the key challenges hindering mass adoption, next only to the complex UI problem of blockchain technology. The idea behind scalability is to ensure that a blockchain protocol can meet up with the growing number of participants on its network. It stands to reason that a feeless smart contract also needs to scale efficiently to handle a growing user base and transaction volume without undermining the performance of its network. Conclusion Exploring the idea of feeless smart technology provides valuable insights into some practical solutions tailored towards reducing transaction costs and improving blockchain scalability. Despite the fact that it is currently a distant goal , it holds a lot of potential for revolutionizing the blockchain space, especially in the area of gas fee reduction. Resolved that the idea of a completely feeless blockchain protocol is bound to lead to much skepticism, the innovative approaches that have been explored are already pushing the boundaries of smart contract technology. With continuous development and research, it is going to be finally decided whether the ultimate goal of this technology is to create a feeless blockchain ecosystem or to usher in an era of improved cost-effective user experience. It is safe to describe the invention of smart contracts as one of the most significant milestones in web3 and cryptography — after Bitcoin! After all, much of what is now known as the DeFi ecosystem owes its existence to smart contract functionalities, powering a host of decentralized applications (DApps). smart contracts smart contracts The keypoint about smart contracts is that they are self-executing agreements stored on a blockchain. They automatically enforce their terms when predefined conditions are met. Smart contracts have come a long way since they were first proposed in 1994 by the renowned American computer scientist, Nick Szabo, such that 19 years later the Ethereum blockchain emerged as the first smart contract platform popularizing the idea of a self-executing blockchain program. In a world where the mass of humanity seek to break free of centralized control, smart contract technology offers a secure and transparent way to conduct transactions without the need for intermediaries. However, despite its level of sophistication, it has remained a subject of cyber security attacks . The DAO hack of 2016 , for example,is a stark reminder of what can happen when a major flaw is exploited in a smart contract. attacks attacks DAO hack of 2016 DAO hack of 2016 Additionally, deploying a smart on a blockchain requires a huge amount of computation and data storage. This often leads to a high transaction fee and the need to keep the network running means that miners or validators are compensated with it. But contending with a high transaction fee can create a significant barrier the adoption of this technology. This is best imagined in a scenario where people have to pay hefty fees for transactions (i.e. buying a cup of coffee with cryptocurrency or an NFT). It not only discourages mass adoption but also hinders the growth of smart contract application across various industries. This bring us to the concept of feeless smart contracts, which is often touted as a potential solution to eliminate transaction fees entirely. Can a zero-fee smart contract unlock a new era of accessibility within the blockchain ecosystem? Let’s find out! Unpacking Feeless Smart Contracts Unpacking Feeless Smart Contracts In the realm of blockchain technology, the concept of a feeless smart contract platform has attracted a significant amount of attention. This is due to the fact that it promises to not only revolutionize how we interact with decentralized applications (dApps) but also seeks to entirely reshape smart contract technology. However, the realization of a truly feeless blockchain ecosystem can be best described as a work in a progress , with blockchain experts exploring potential solutions that can help solve the current challenges hindering it. The amount of attention it continues to command in the blockchain space has not only made feeless smart contract technology an area of ongoing research and development, but it has also facilitated the emergence of   pragmatic approaches such as proof-of-work with burning, layered architectures and proof-of-stake (PoS) consensus mechanism. Proof-of-Work (PoW) With Burning: Proof-of-Work (PoW) With Burning: Proof-of-work with burning is a combination of the proof-of-work (PoW) consensus mechanism and the routine practice of burning of a token to drive its scarcity. The idea behind this approach is to allow miners to earn tokens that are burned (i.e. kept out of circulation) when used for transactions. However, this solution is criticized because of the deflationary effect it creates. It is also not considered a sustainable model because critics believe that miner rewards might become insufficient and the network security jeopardized, if tokens are burned too quickly. Proof-of-Stake(PoS) Consensus Mechanisms: Proof-of-Stake(PoS) Consensus Mechanisms: The proof-of-stake (PoS) consensus mechanism emerged as a viable alternative to the proof-of-work (PoW) mechanism and it has gained a significant amount of attention in the industry. Leading blockchain protocols such as Solana, Cardano, Polkadot, etc leverage this approach to PoW mainly because it requires less energy consumption and it is eco-friendly. However, it is important to note that it is not entirely feeless as a very insignificant amount of transaction fee is usually required for keep the network running. Layered Architectures: In a layered architecture, the base layer is designed to handle the security and consensus mechanism of the blockchain, while the fee layer is designed to enable the execution of smart contract. This approach is often deployed by top protocols such as Cosmos and Polkadot as it creates room for a more flexible fee increasing the chances of feeless transactions on the smart contract layer. Qubic Protocol As a Case Study Qubic is an AI blockchain ecosystem pioneering innovation in feeless smart contract in a quest to eliminate the transaction fees often associated with deploying smart contract on other platforms. To achieve this feat Qubic protocol proposes a Proof-of-Work(PoW)model with a twist: burning. Proof-of-Work(PoW)model with a twist: burning. Similar to Proof-of-Work mechanisms, miners compete to solve complex puzzles ad secure the Qubic network. However, instead of receiving cryptocurrency, miners are rewarded with Qubic Units, the native token of the protocol recently listed on MEXC in tandem with its 2024 road map. Qubic Units, Its proposed solution allows users who want to execute a smart contract to BURN a specific amount of QUs, instead of paying a hefty transaction fee. This burning mechanism then removes the burned QUs from circulation, fostering a potential scarcity to increase the value of the remaining tokens. However, since Proof-of-Work(PoW) mechanisms are often criticized for their high energy consumption, Qubic needs to navigate this obstacle to create a truly feeless ecosystem. Nonetheless, Qubic’s burning POW model presents a novel approach in the development of feeless smart contract. The Challenges of Feeless Smart Contracts When it comes to feeless smart contract technology, there is a thin line between hype and reality. This is why it is important to first acknowledge that it is an emerging technology and not a one-size-fit-all solution to the high transaction fee that many blockchain protocols continue to contend with. In essence, it is crucial to state that feeless smart contract technology  faces a unique set of of challenges such as security, sustainability and scalability. Sustainability Building a feeless smart contract is not enough. It must be sustainable in the long run. As a matter of fact,its sustainability lies in its ability to function on a secure and decentralized blockchain protocol. There is also the need to create and maintain sufficient incentives for miners or validators in order to run and secure  the network. Security Smart contract audit is a routine practice of checking for vulnerabilities in code. This is an industry standard procedure that is required to minimize potential cyber security risks. It is hinged on the premise that blockchain protocols are not immune from cyber attacks, which can result in substantial financial loss. In order to address a potential security risk that may arise,it is crucial for a feeless smart contract to undergo a regular smart audit  as it can help to uncover security flaw in its code. Scalability Scalability has been recognized as one of the key challenges hindering mass adoption, next only to the complex UI problem of blockchain technology. The idea behind scalability is to ensure that a blockchain protocol can meet up with the growing number of participants on its network. It stands to reason that a feeless smart contract also needs to scale efficiently to handle a growing user base and transaction volume without undermining the performance of its network. Conclusion Exploring the idea of feeless smart technology provides valuable insights into some practical solutions tailored towards reducing transaction costs and improving blockchain scalability. Despite the fact that it is currently a distant goal , it holds a lot of potential for revolutionizing the blockchain space, especially in the area of gas fee reduction. Resolved that the idea of a completely feeless blockchain protocol is bound to lead to much skepticism, the innovative approaches that have been explored are already pushing the boundaries of smart contract technology. With continuous development and research, it is going to be finally decided whether the ultimate goal of this technology is to create a feeless blockchain ecosystem or to usher in an era of improved cost-effective user experience.

Are Feeless Smart Contracts the Answer?

I Grow My Money Using 5 Personal Finance Principles

Singapore, July 17, 2024 - BlockBeats, a key player in the crypto media landscape, recently interviewed Andrew Weiner, the new Vice President of WEEX's English Market. With extensive experience in the cryptocurrency sector, Andrew shared his journey, the advantages of WEEX, and the platform’s future strategies. From iComply to MEXC: Andrew Weiner's Crypto Industry Adventure BlockBeats: Can you give a quick overview of your experience in the cryptocurrency industry? I noticed you were the VP at MEXC Global? Andrew Weiner: I started at iComply Investor Services, developing a patented off-chain cryptographic verification system for securely processing consumer data in compliance with Travel Rule requirements. Later, at MEXC Global, I helped grow the user base from 6 million to 12 million users worldwide by forming strategic partnerships with top project developers and key opinion leaders, significantly enhancing MEXC's market presence. Why Choose WEEX? Andrew Weiner on the Unique Strengths of the Emerging Crypto Platform BlockBeats: Now that you're the VP at WEEX, what do you think sets WEEX apart from other platforms? Andrew Weiner: The market today is lacking a true turn-key, all-in-one destination for crypto. WEEX, with its rapidly growing network of developers, community leaders, and media partners, is emerging  to set a new standard in delivering these high quality user experiences, for everyone. Whether you are a professional, casual, or curious trader, with one login you can access all of the things you want and expect from your cryptocurrency trading platform. Debunking the Saturation Myth: WEEX’s Strategy for Success in a Crowded Market BlockBeats: Many people believe that the trading platform market is already saturated. How do you think WEEX is able to attract traffic? Andrew Weiner: I completely disagree, the industry still has immense global demand and is far from saturated, especially in derivatives trading. Traditional financial players are investing heavily in blockchain, signaling huge potential. WEEX bridges the gaps between traditional finance, centralized finance, and decentralized finance, positioning itself as the go-to platform for millions by the end of 2024. The Power of WXT Token: How WEEX's Platform Token is Redefining User Engagement BlockBeats: WEEX is recently launching its own platform token. What is unique about WXT compared to other platform tokens? Andrew Weiner: The WEEX community and their passion for sharing our brand is the reason we’ve enjoyed such incredible success to-date. With that in mind, we’ve designed $WXT to make every holder an unlimited partner in the continued growth of our audience, and enjoy the value that will be created along the way - which is a far deeper relationship than our competitors are establishing with their audience. Empowering Users with WXT: Exclusive Benefits and Future Potential for WXT Holders BlockBeats: What scenarios and potential benefits do users experience when holding WXT? Andrew Weiner: $WXT is a reinvestment into the users who made us a leader in the cryptocurrency futures trading space, providing trading fee discounts, exclusive rewards, a voice in the future development of WEEX. Our commitment to our WEEXer army is that no other platform token will empower its community of holders to have as much value and influence as WEEX. Addressing Market Gaps: WEEX’s Comprehensive Approach to Crypto Trading BlockBeats: What gaps in the trading platform market does WEEX plan to fill? Andrew Weiner: When you go to the conferences and survey the product users in attendance, you will commonly find everyone has an account on up to 4 or 5 platforms. There seems to be a considerable number of points of friction that traders encounter daily in our space. Until this is consolidated, and consumers are able to develop loyalty to one single product or service provider, an opportunity will exist for a brand like WEEX to be that proverbial 3rd place in a gem hunter’s daily routine. Familiar, reliable, secure, and comfortable - that is WEEX. Everything you need, in one single place, with none of the hassle. \Navigating Market Making: Andrew Weiner’s Take on Exchange Operations Post-FTX BlockBeats: After FTX, the market seems not to approve of exchanges having their own market makers. Should CEXs have their own market makers? Andrew Weiner: No, an exchange should not act as its own MM. As an exchange, my primary focus is the user experience, product security, service reliability. There is no room for price-action in that focus. As observed with that specific case you’ve referenced, the MM-dynamic created a conflict of interest, and millions of users are still recovering. As I said on the Mario Nawfal podcast following that event, any incestuous relationship between 2 entities should be avoided, proof of reserves is the evidence consumers deserve going forward. Innovating On-Chain: WEEX's Future Plans for Blockchain Ecosystem Development BlockBeats: lt seems like every exchange has its own on-chain ecosystem, backed by a blockchain. What are WEEX's plans regarding on-chain development? Andrew Weiner: In the near-future WEEX will provide our network of developers with unique opportunities to collaborate deeper and launch their exciting new innovations with us. We hope to reveal more in the coming months, but I am unable to disclose anything further at this time regarding our WEEX Wealth initiative. About WEEX Since its inception in 2018, WEEX has rapidly established itself as a top cryptocurrency exchange, known for stringent security measures and a user-focused platform. Holding licenses from US and Canadian MSBs, and SVGFSA, WEEX offers a regulated trading environment with 116 spot trading pairs and 225 futures trading pairs. The WEEX platform token, WXT, offers benefits like over 20% discounts on trading fees, exclusive VIP event access, and participation in platform governance and the WEEX Launchpool. WEEX blends innovative features with a commitment to user satisfaction, making it a distinguished choice in the cryptocurrency market. Sign up for a WEEX Account Visit WEEX Official Website Media Email WEEX Customer Support: support@weex.com Trading Quant & MM: market@weexglobal.com This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here. Singapore, July 17, 2024 - BlockBeats, a key player in the crypto media landscape, recently interviewed Andrew Weiner, the new Vice President of WEEX's English Market. With extensive experience in the cryptocurrency sector, Andrew shared his journey, the advantages of WEEX, and the platform’s future strategies. From iComply to MEXC: Andrew Weiner's Crypto Industry Adventure BlockBeats: Can you give a quick overview of your experience in the cryptocurrency industry? I noticed you were the VP at MEXC Global? BlockBeats: Andrew Weiner : I started at iComply Investor Services, developing a patented off-chain cryptographic verification system for securely processing consumer data in compliance with Travel Rule requirements. Later, at MEXC Global, I helped grow the user base from 6 million to 12 million users worldwide by forming strategic partnerships with top project developers and key opinion leaders, significantly enhancing MEXC's market presence. Andrew Weiner Why Choose WEEX? Andrew Weiner on the Unique Strengths of the Emerging Crypto Platform BlockBeats: Now that you're the VP at WEEX, what do you think sets WEEX apart from other platforms? BlockBeats: Andrew Weiner: The market today is lacking a true turn-key, all-in-one destination for crypto. WEEX , with its rapidly growing network of developers, community leaders, and media partners, is emerging  to set a new standard in delivering these high quality user experiences, for everyone. Whether you are a professional, casual, or curious trader, with one login you can access all of the things you want and expect from your cryptocurrency trading platform. Andrew Weiner: WEEX WEEX Debunking the Saturation Myth: WEEX’s Strategy for Success in a Crowded Market BlockBeats: Many people believe that the trading platform market is already saturated. How do you think WEEX is able to attract traffic? BlockBeats: Andrew Weiner: I completely disagree, the industry still has immense global demand and is far from saturated, especially in derivatives trading. Traditional financial players are investing heavily in blockchain, signaling huge potential. WEEX bridges the gaps between traditional finance, centralized finance, and decentralized finance, positioning itself as the go-to platform for millions by the end of 2024. Andrew Weiner: The Power of WXT Token: How WEEX's Platform Token is Redefining User Engagement BlockBeats: WEEX is recently launching its own platform token. What is unique about WXT compared to other platform tokens? BlockBeats: Andrew Weiner: The WEEX community and their passion for sharing our brand is the reason we’ve enjoyed such incredible success to-date. With that in mind, we’ve designed $WXT to make every holder an unlimited partner in the continued growth of our audience, and enjoy the value that will be created along the way - which is a far deeper relationship than our competitors are establishing with their audience. Andrew Weiner: Empowering Users with WXT: Exclusive Benefits and Future Potential for WXT Holders BlockBeats: What scenarios and potential benefits do users experience when holding WXT? BlockBeats: Andrew Weiner: $ WXT is a reinvestment into the users who made us a leader in the cryptocurrency futures trading space, providing trading fee discounts, exclusive rewards, a voice in the future development of WEEX. Our commitment to our WEEXer army is that no other platform token will empower its community of holders to have as much value and influence as WEEX. Andrew Weiner: WXT WXT Addressing Market Gaps: WEEX’s Comprehensive Approach to Crypto Trading BlockBeats: What gaps in the trading platform market does WEEX plan to fill? BlockBeats: Andrew Weiner: When you go to the conferences and survey the product users in attendance, you will commonly find everyone has an account on up to 4 or 5 platforms. There seems to be a considerable number of points of friction that traders encounter daily in our space. Andrew Weiner: Until this is consolidated, and consumers are able to develop loyalty to one single product or service provider, an opportunity will exist for a brand like WEEX to be that proverbial 3rd place in a gem hunter’s daily routine. Familiar, reliable, secure, and comfortable - that is WEEX. Everything you need, in one single place, with none of the hassle. \Navigating Market Making: Andrew Weiner’s Take on Exchange Operations Post-FTX BlockBeats: After FTX, the market seems not to approve of exchanges having their own market makers. Should CEXs have their own market makers? BlockBeats: Andrew Weiner: No, an exchange should not act as its own MM. As an exchange, my primary focus is the user experience, product security, service reliability. There is no room for price-action in that focus. As observed with that specific case you’ve referenced, the MM-dynamic created a conflict of interest, and millions of users are still recovering. As I said on the Mario Nawfal podcast following that event, any incestuous relationship between 2 entities should be avoided, proof of reserves is the evidence consumers deserve going forward. Andrew Weiner: proof of reserves proof of reserves Innovating On-Chain: WEEX's Future Plans for Blockchain Ecosystem Development BlockBeats: lt seems like every exchange has its own on-chain ecosystem, backed by a blockchain. What are WEEX's plans regarding on-chain development? BlockBeats: Andrew Weiner: In the near-future WEEX will provide our network of developers with unique opportunities to collaborate deeper and launch their exciting new innovations with us. We hope to reveal more in the coming months, but I am unable to disclose anything further at this time regarding our WEEX Wealth initiative. Andrew Weiner: WEEX WEEX About WEEX Since its inception in 2018, WEEX has rapidly established itself as a top cryptocurrency exchange, known for stringent security measures and a user-focused platform. Holding licenses from US and Canadian MSBs, and SVGFSA, WEEX offers a regulated trading environment with 116 spot trading pairs and 225 futures trading pairs. The WEEX platform token, WXT, offers benefits like over 20% discounts on trading fees, exclusive VIP event access, and participation in platform governance and the WEEX Launchpool. WEEX blends innovative features with a commitment to user satisfaction, making it a distinguished choice in the cryptocurrency market. Sign up for a WEEX Account WEEX Account Visit WEEX Official Website Official Website Media Email Email WEEX Customer Support: support@weex.com Trading Quant & MM: market@weexglobal.com This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Interview with Andrew Weiner, VP WEEX: Unlocking the Future of Crypto Trading

UMG Recordings, Inc. v. Verizon Communications Inc., Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 5 of 11. VERIZON AND ITS ACTIVITIES 52. Defendant Verizon Communications Inc. is a Delaware corporation that is headquartered at 1095 Avenue of the Americas, New York, New York 10036. 53. Defendant Verizon Services Corp. is a Delaware corporation that is headquartered at 1095 Avenue of the Americas, New York, New York 10036. 54. Defendant Cellco Partnership (d/b/a Verizon Wireless) is a Delaware corporation that is headquartered at 1095 Avenue of the Americas, New York, New York 10036. 55. Verizon Communications Inc. is one of the leading providers of technology and communications services in the United States and in the world. Through its subsidiaries, including Verizon Services Corp. and Cellco Partnership (d/b/a Verizon Wireless), Verizon Communications Inc. provides wireless and wireline data and Internet services to millions of residential and business subscribers around the country. 56. As of December 2023, Verizon’s consumer group, which focuses primarily on residential subscribers, provided 115 million wireless retail connections, 9 million broadband connections, and 3 million video connections. Verizon also provided business customers with approximately 30 million wireless retail connections and approximately 2 million total broadband connections 57. At all pertinent times, Verizon’s customers have paid substantial subscription fees for access to Verizon’s high-speed Internet service, with Verizon offering a tiered pricing structure whereby a subscriber can purchase faster downloading speeds for a higher monthly fee. 58. Many of Verizon’s customers are motivated to subscribe to Verizon’s service because it allows them to download music and other copyrighted content—including unauthorized content—as fast as possible. Accordingly, in its consumer marketing materials, Verizon touts the speed at which its customers can download content. For example, Verizon has stated, “You can download an HD movie before the popcorn is ready with speeds nearing a gigabit, just to give you an idea how fast that is.”[2] In the same consumer marketing material, Verizon also states that it is “one of the only internet service providers to offer nearly matching download and upload speeds on most plans, which is a major advantage when you’re . . . sharing large files.”[3] 59. Verizon has consistently and actively engaged in sophisticated network and customer management practices to suit its own purposes. This includes monitoring for, and taking action against, spam and other unwanted activity that might otherwise interfere with its provision of Internet service to its subscribers. At the same time, Verizon has gone out of its way not to take action against subscribers engaging in repeated copyright infringement, at the expense of copyright owners, ultimately forcing Plaintiffs to bring this action. 60. Verizon’s failure to take action against subscribers using its network to engage in repeated copyright infringement is contrary to its own policies. Indeed, Verizon’s “Copyright Infringement/Repeat Infringer Policy” prohibits subscribers from using “Verizon’s systems or servers in any manner that constitutes an infringement of third party intellectual property rights, under US copyright law,” and further states that, “[p]ursuant to Section 512 of the Digital Millennium Copyright Act (DMCA), it is Verizon’s policy to terminate the account of repeat copyright infringers in appropriate circumstances.”[4] Verizon’s “Acceptable Use Policy” (“AUP”) reiterates that subscribers may not use Verizon’s network to infringe the intellectual property rights of others, including copyright. The AUP refers to violations of “any third party’s copyright” as an example of conduct “which may lead to termination of [a subscriber’s] Service.”[5] 61. While publicly stating that its customers may not use its network to infringe, Verizon privately takes active steps to thwart copyright owners from informing Verizon about P2P infringements by its customers. Verizon purports to accept infringement notices through two avenues, but in reality, both are illusory and ineffective. 62. Through one channel, Verizon claims to allow copyright holders to send P2P notices through a so-called “Anti-Piracy Cooperation Program,” but it has attached such onerous conditions to participation that the program is rendered a nullity. Not only has Verizon required participants to pay burdensome fees for simple, automated processes like Internet Protocol (“IP”) address lookups and notice forwarding, but participants have been required to waive their copyright claims, broadly indemnify Verizon, and, tellingly, keep the terms of the program confidential. Verizon has also limited the number of notices it will forward pursuant to the program. 63. For copyright owners unwilling to waive their rights and “pay-to-play,” Verizon directs them to send email notices concerning P2P infringement to CONDUITFORMNOTICES@verizon.com. Verizon publicly states that it “do[es] not review, process, or otherwise take action on [P2P] notices . . . sent via email to any other Verizon email inbox.”[6] And yet Verizon plainly does not even review, process or otherwise take action on notices sent by email to CONDUITFORMNOTICES@verizon.com. Verizon does not forward these notices to subscribers or track the number of email notices sent regarding repeat infringing subscribers. Verizon also arbitrarily caps the number of notices permitted per copyright holder at this address—ironic, to say the least, given that Verizon ignored hundreds of thousands of Plaintiffs’ notices to this email inbox. 64. At all pertinent times, Verizon knew that its subscribers routinely used its networks for illegally downloading and uploading copyrighted works, especially sound recordings. As described below, Plaintiffs repeatedly notified Verizon that thousands of its subscribers were actively utilizing its service to infringe Plaintiffs’ copyrighted works. Those notices gave Verizon the specific identities of its subscribers engaged in copyright infringement, referred to by their unique IP addresses. Verizon also received millions of notices from other copyright owners, some of which undoubtedly addressed the same subscribers as Plaintiffs’ notices. Verizon thus knew which particular subscribers engaged in repeat infringement and Verizon had the right and ability to stop that infringement, including by suspending or terminating the accounts of repeat infringers. Yet Verizon condoned its subscribers’ illegal activity because it profited from that activity and its permissive stance toward that activity acted as a draw to attract and retain new and existing subscribers. Verizon’s customers, in turn, continued using Verizon’s services to infringe Plaintiffs’ copyrighted works. 65. Verizon undoubtedly recognized that if it terminated or otherwise prevented its repeat infringer subscribers from using its service to infringe, or made it less attractive for such use, Verizon would enroll fewer new subscribers, lose existing subscribers, and ultimately lose revenue. For those account holders and subscribers who wanted to download files illegally at faster speeds, Verizon provided the means for them to do so in exchange for higher subscription fees. Indeed, Verizon offered “tiered” service plans in which subscribers could pay less for a lower-tier plan with limits on upload and download speeds and the amount of data available monthly, or alternatively, subscribers could pay more for a higher-tier plan with unlimited data and faster upload and download speeds. In other words, the greater the bandwidth or speed its subscribers required for illegally downloading and uploading copyrighted works, the more money Verizon made. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved on July 12, 2024, storage.courtlistener is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. Lead image by Marques Thomas on Unsplash [2] Verizon Fios Home Internet webpage with FAQs, available at https://www.verizon.com/home/internet/fios-fastest-internet/ (last accessed July 8, 2024). [3] Id. [4] Verizon Customer Agreement, available at https://www.verizon.com/about/termsconditions/verizon-customer-agreement (last accessed June 19, 2024). [5] Id. [6] Copyright Infringement Claims and the Digital Millennium Copyright Act (DMCA), available at https://www.verizon.com/support/residential/account/manage-account/security/copyrightinfringement-claims (last accessed June 20, 2024). UMG Recordings, Inc. v. Verizon Communications Inc., Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 5 of 11. UMG Recordings, Inc. v. Verizon Communications Inc., Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part of this filing here . This part is 5 of 11. HackerNoon’s Legal PDF Series HackerNoon’s Legal PDF Series here here VERIZON AND ITS ACTIVITIES 52. Defendant Verizon Communications Inc. is a Delaware corporation that is headquartered at 1095 Avenue of the Americas, New York, New York 10036. 53. Defendant Verizon Services Corp. is a Delaware corporation that is headquartered at 1095 Avenue of the Americas, New York, New York 10036. 54. Defendant Cellco Partnership (d/b/a Verizon Wireless) is a Delaware corporation that is headquartered at 1095 Avenue of the Americas, New York, New York 10036. 55. Verizon Communications Inc. is one of the leading providers of technology and communications services in the United States and in the world. Through its subsidiaries, including Verizon Services Corp. and Cellco Partnership (d/b/a Verizon Wireless), Verizon Communications Inc. provides wireless and wireline data and Internet services to millions of residential and business subscribers around the country. 56. As of December 2023, Verizon’s consumer group, which focuses primarily on residential subscribers, provided 115 million wireless retail connections, 9 million broadband connections, and 3 million video connections. Verizon also provided business customers with approximately 30 million wireless retail connections and approximately 2 million total broadband connections 57. At all pertinent times, Verizon’s customers have paid substantial subscription fees for access to Verizon’s high-speed Internet service, with Verizon offering a tiered pricing structure whereby a subscriber can purchase faster downloading speeds for a higher monthly fee. 58. Many of Verizon’s customers are motivated to subscribe to Verizon’s service because it allows them to download music and other copyrighted content—including unauthorized content—as fast as possible. Accordingly, in its consumer marketing materials, Verizon touts the speed at which its customers can download content. For example, Verizon has stated, “You can download an HD movie before the popcorn is ready with speeds nearing a gigabit, just to give you an idea how fast that is.”[2] In the same consumer marketing material, Verizon also states that it is “one of the only internet service providers to offer nearly matching download and upload speeds on most plans, which is a major advantage when you’re . . . sharing large files.”[3] 59. Verizon has consistently and actively engaged in sophisticated network and customer management practices to suit its own purposes. This includes monitoring for, and taking action against, spam and other unwanted activity that might otherwise interfere with its provision of Internet service to its subscribers. At the same time, Verizon has gone out of its way not to take action against subscribers engaging in repeated copyright infringement, at the expense of copyright owners, ultimately forcing Plaintiffs to bring this action. 60. Verizon’s failure to take action against subscribers using its network to engage in repeated copyright infringement is contrary to its own policies. Indeed, Verizon’s “Copyright Infringement/Repeat Infringer Policy” prohibits subscribers from using “Verizon’s systems or servers in any manner that constitutes an infringement of third party intellectual property rights, under US copyright law,” and further states that, “[p]ursuant to Section 512 of the Digital Millennium Copyright Act (DMCA), it is Verizon’s policy to terminate the account of repeat copyright infringers in appropriate circumstances.”[4] Verizon’s “Acceptable Use Policy” (“AUP”) reiterates that subscribers may not use Verizon’s network to infringe the intellectual property rights of others, including copyright. The AUP refers to violations of “any third party’s copyright” as an example of conduct “which may lead to termination of [a subscriber’s] Service.”[5] 61. While publicly stating that its customers may not use its network to infringe, Verizon privately takes active steps to thwart copyright owners from informing Verizon about P2P infringements by its customers. Verizon purports to accept infringement notices through two avenues, but in reality, both are illusory and ineffective. 62. Through one channel, Verizon claims to allow copyright holders to send P2P notices through a so-called “Anti-Piracy Cooperation Program,” but it has attached such onerous conditions to participation that the program is rendered a nullity. Not only has Verizon required participants to pay burdensome fees for simple, automated processes like Internet Protocol (“IP”) address lookups and notice forwarding, but participants have been required to waive their copyright claims, broadly indemnify Verizon, and, tellingly, keep the terms of the program confidential. Verizon has also limited the number of notices it will forward pursuant to the program. 63. For copyright owners unwilling to waive their rights and “pay-to-play,” Verizon directs them to send email notices concerning P2P infringement to CONDUITFORMNOTICES@verizon.com. Verizon publicly states that it “do[es] not review, process, or otherwise take action on [P2P] notices . . . sent via email to any other Verizon email inbox.”[6] And yet Verizon plainly does not even review, process or otherwise take action on notices sent by email to CONDUITFORMNOTICES@verizon.com. Verizon does not forward these notices to subscribers or track the number of email notices sent regarding repeat infringing subscribers. Verizon also arbitrarily caps the number of notices permitted per copyright holder at this address—ironic, to say the least, given that Verizon ignored hundreds of thousands of Plaintiffs’ notices to this email inbox. 64. At all pertinent times, Verizon knew that its subscribers routinely used its networks for illegally downloading and uploading copyrighted works, especially sound recordings. As described below, Plaintiffs repeatedly notified Verizon that thousands of its subscribers were actively utilizing its service to infringe Plaintiffs’ copyrighted works. Those notices gave Verizon the specific identities of its subscribers engaged in copyright infringement, referred to by their unique IP addresses. Verizon also received millions of notices from other copyright owners, some of which undoubtedly addressed the same subscribers as Plaintiffs’ notices. Verizon thus knew which particular subscribers engaged in repeat infringement and Verizon had the right and ability to stop that infringement, including by suspending or terminating the accounts of repeat infringers. Yet Verizon condoned its subscribers’ illegal activity because it profited from that activity and its permissive stance toward that activity acted as a draw to attract and retain new and existing subscribers. Verizon’s customers, in turn, continued using Verizon’s services to infringe Plaintiffs’ copyrighted works. 65. Verizon undoubtedly recognized that if it terminated or otherwise prevented its repeat infringer subscribers from using its service to infringe, or made it less attractive for such use, Verizon would enroll fewer new subscribers, lose existing subscribers, and ultimately lose revenue. For those account holders and subscribers who wanted to download files illegally at faster speeds, Verizon provided the means for them to do so in exchange for higher subscription fees. Indeed, Verizon offered “tiered” service plans in which subscribers could pay less for a lower-tier plan with limits on upload and download speeds and the amount of data available monthly, or alternatively, subscribers could pay more for a higher-tier plan with unlimited data and faster upload and download speeds. In other words, the greater the bandwidth or speed its subscribers required for illegally downloading and uploading copyrighted works, the more money Verizon made. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on July 12, 2024, storage.courtlistener is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on July 12, 2024, storage.courtlistener is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener Lead image by Marques Thomas on Unsplash Lead image by Marques Thomas on Unsplash Marques Thomas on Unsplash [2] Verizon Fios Home Internet webpage with FAQs, available at https://www.verizon.com/home/internet/fios-fastest-internet/ (last accessed July 8, 2024). https://www.verizon.com/home/internet/fios-fastest-internet/ [3] Id. [4] Verizon Customer Agreement, available at https://www.verizon.com/about/termsconditions/verizon-customer-agreement (last accessed June 19, 2024). https://www.verizon.com/about/termsconditions/verizon-customer-agreement [5] Id. [6] Copyright Infringement Claims and the Digital Millennium Copyright Act (DMCA), available at https://www.verizon.com/support/residential/account/manage-account/security/copyrightinfringement-claims (last accessed June 20, 2024). https://www.verizon.com/support/residential/account/manage-account/security/copyrightinfringement-claims

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