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More than 300 exabytes of data are created every day. To put that number into perspective, one exabyte equals one billion gigabytes. Considering the amount of data being created, there is a need for more efficient and easier data management and analytics. The recent proliferation of AI in people's personal and professional lives explains why they would look at AI to address their data management challenges. In fact, 64% of business owners believe AI will help them increase productivity. Data mapping, a crucial step in data management, is ideal for automation. It's a repetitive and time-consuming process, making it well-suited for AI. Automating data mapping can free up time for higher-priority tasks. This post looks at data mapping and its different types, and the role of data mapping in data management. It will also discuss how the combination of AI and data mapping makes data management easy and accessible and presents opportunities for organizations and software vendors alike. What is Data Mapping? Data mapping connects and transforms data to be shared from one system or database to another. Consider this: A business wants to launch a referral reward program. It has a database holding all its customer data and wants to connect it to a database holding purchase records. Mapping the relevant data from the source to the newly merged database lets it do just that. With the databases properly mapped, the business will now have access to actionable information in real time, letting them know which customers to contact for the program. In other words, data mapping helps different databases connect and communicate. This can improve business intelligence capabilities throughout the organization. It also allows core functions like Marketing, Product Development, and Finance to operate synergistically, using real-time data to drive their decision-making. Types of Data Mapping Data mapping has three main types: manual, semi-automated, and automated. The manual approach to data mapping has been the norm for decades. However, semi-automated and automated data mapping approaches are quickly gaining ground due to their benefits. Let’s look at some of these benefits: Manual Data Mapping
Manual mapping offers users greater flexibility and control over their data flow. However, it can be a long and repetitive process. If done using coding languages like SQL or C++, it requires a lot of working hours and technical expertise. Manual data mapping is no longer a practical option, considering the amount of data that organizations create every minute. Semi-Automated Data Mapping
The semi-automated approach offers a good balance between flexibility and efficiency. A good example of semi-automated data mapping is schema maps. Semi-automated data mappers use visual representations of the data maps, allowing users with limited technical knowledge to construct dataflows. This approach is less time-intensive and doesn’t require much coding expertise. However, it still needs some technical knowledge, regardless of whether an organization relies on coding or drag-and-drop solutions. Automated Data Mapping Automated data mapping offers many benefits compared to manual and semi-automated data mapping. For instance, it offers flexibility and speed and doesn’t require technical knowledge. The automated approach makes scheduling, scaling, and deploying your dataflows easy. However, the necessary technical training will be platform-specific and not necessarily transferable. The Importance of Data Mapping As businesses collect more data, data mapping becomes increasingly essential. This scenario is even more challenging because businesses gather data from multiple sources. That data becomes unusable if they fail to collect, organize, clean, and transform it into actionable insights properly and on time. In other words, proper data mapping is like implementing a filing system to ensure that all your data ends up in the right place, in the suitable format, at the right time. With this filing system, your organization will catch up in data management, analytics, and business intelligence functions. AI and Data Mapping The trend of AI adoption in data management relates to the evolving data needs of organizations. With efficiency and ease of use as priorities, AI’s role becomes even more important in data management, specifically data mapping. For instance, semi-automated data mapping solutions were present well before the AI boom. So, the need to automate the data mapping process is not new. Even so, the AI wave has the potential to make fully automated data mapping the standard practice in data management. With AI getting tons of attention and resources, the time is right for organizations and software vendors to solve data management challenges using AI. While AI is already being implemented across data management tools, full data mapping automation is still a work in progress. Nevertheless, the following are some ways AI is democratizing data management by transforming the data mapping process: Automated Discovery of Data Sources and Attributes: AI-powered data mappers automate the discovery of relevant data sources, attributes, and possible connections. This allows users to eliminate the lengthy steps of manual data mapping. Users can fine-tweak the AI-generated maps to their specific needs and accept or reject AI suggestions as they see fit. This significantly simplifies data mapping, letting users handle complex dataflows in relatively shorter times.


Contextual Analysis to Identify Patterns and Connections: What sets AI apart from generic automation tools is its ability to think and analyze. An example is interaction with large language models (LLMs) like ChatGPT or Gemini. These LLMs can understand the context and tailor their responses accordingly. Similarly, AI-powered data mapping solutions can analyze and interpret the data fields to intelligently identify and establish patterns and relationships. This significantly reduces the technical knowledge requirement, allowing even beginners to use data management solutions with little expertise.


Simplified Schema Mapping: Data mapping algorithms also use pattern recognition to identify semantic relationships. This simplifies schema mapping as AI can find similarities between seemingly unrelated schemas. In short, AI-assisted field and schema mapping ensure smooth data integration, reducing complexity for end-users. AI and Data Mapping: Why It’s a Good Combination Data mapping is a crucial step, but it can get repetitive and taxing quickly. By incorporating AI, data management platforms can streamline, speed up, and simplify the entire process for their end-users. Moreover, by cutting the requirement for technical knowledge, software vendors and organizations alike can promote data literacy among their internal and external stakeholders. As a result, organizations can promote a more efficient and effective use of data across their functions. For instance, marketers without coding experience can gather actionable campaign insights. Similarly, the Research and Development team can leverage data from Customer Support to improve their offerings. Similarly, software vendors can cater to a larger customer base by customizing their offerings for non-technical users. They can empower their customers to move beyond the traditional approach, democratizing data management across all relevant functions. This win-win proposition should encourage AI adoption for data mapping among all stakeholders. Conclusion Combining data mapping and AI is a logical step to meet the evolving needs of data management for all stakeholders. For businesses, it democratizes data management, simplifies the data mapping process, and saves time and costs. For software vendors, this integration provides access to a larger audience, increasing profitability and reach. For end users, the AI and data mapping combination makes their day-to-day work easier, faster, and more effective. More than 300 exabytes of data are created every day. To put that number into perspective, one exabyte equals one billion gigabytes. 300 exabytes of data Considering the amount of data being created, there is a need for more efficient and easier data management and analytics. The recent proliferation of AI in people's personal and professional lives explains why they would look at AI to address their data management challenges. In fact, 64% of business owners believe AI will help them increase productivity. 64% of business owners Data mapping , a crucial step in data management, is ideal for automation. It's a repetitive and time-consuming process, making it well-suited for AI. Automating data mapping can free up time for higher-priority tasks. Data mapping This post looks at data mapping and its different types, and the role of data mapping in data management. It will also discuss how the combination of AI and data mapping makes data management easy and accessible and presents opportunities for organizations and software vendors alike. What is Data Mapping? Data mapping connects and transforms data to be shared from one system or database to another. Consider this: A business wants to launch a referral reward program. It has a database holding all its customer data and wants to connect it to a database holding purchase records. Mapping the relevant data from the source to the newly merged database lets it do just that. With the databases properly mapped, the business will now have access to actionable information in real time, letting them know which customers to contact for the program. In other words, data mapping helps different databases connect and communicate. This can improve business intelligence capabilities throughout the organization. It also allows core functions like Marketing, Product Development, and Finance to operate synergistically, using real-time data to drive their decision-making. Types of Data Mapping Data mapping has three main types: manual, semi-automated, and automated. The manual approach to data mapping has been the norm for decades. However, semi-automated and automated data mapping approaches are quickly gaining ground due to their benefits. Let’s look at some of these benefits: Manual Data Mapping Manual mapping offers users greater flexibility and control over their data flow. However, it can be a long and repetitive process. If done using coding languages like SQL or C++, it requires a lot of working hours and technical expertise. Manual data mapping is no longer a practical option, considering the amount of data that organizations create every minute. Manual Data Mapping Semi-Automated Data Mapping The semi-automated approach offers a good balance between flexibility and efficiency. A good example of semi-automated data mapping is schema maps. Semi-automated data mappers use visual representations of the data maps, allowing users with limited technical knowledge to construct dataflows. This approach is less time-intensive and doesn’t require much coding expertise. However, it still needs some technical knowledge, regardless of whether an organization relies on coding or drag-and-drop solutions. Semi-Automated Data Mapping Automated Data Mapping Automated Data Mapping Automated data mapping offers many benefits compared to manual and semi-automated data mapping. For instance, it offers flexibility and speed and doesn’t require technical knowledge. The automated approach makes scheduling, scaling, and deploying your dataflows easy. However, the necessary technical training will be platform-specific and not necessarily transferable. The Importance of Data Mapping As businesses collect more data, data mapping becomes increasingly essential. This scenario is even more challenging because businesses gather data from multiple sources. That data becomes unusable if they fail to collect, organize, clean, and transform it into actionable insights properly and on time. In other words, proper data mapping is like implementing a filing system to ensure that all your data ends up in the right place, in the suitable format, at the right time. With this filing system, your organization will catch up in data management, analytics, and business intelligence functions. AI and Data Mapping The trend of AI adoption in data management relates to the evolving data needs of organizations. With efficiency and ease of use as priorities, AI’s role becomes even more important in data management, specifically data mapping. For instance, semi-automated data mapping solutions were present well before the AI boom. So, the need to automate the data mapping process is not new. Even so, the AI wave has the potential to make fully automated data mapping the standard practice in data management. With AI getting tons of attention and resources, the time is right for organizations and software vendors to solve data management challenges using AI. While AI is already being implemented across data management tools, full data mapping automation is still a work in progress. Nevertheless, the following are some ways AI is democratizing data management by transforming the data mapping process: Automated Discovery of Data Sources and Attributes: AI-powered data mappers automate the discovery of relevant data sources, attributes, and possible connections. This allows users to eliminate the lengthy steps of manual data mapping. Users can fine-tweak the AI-generated maps to their specific needs and accept or reject AI suggestions as they see fit. This significantly simplifies data mapping, letting users handle complex dataflows in relatively shorter times. Contextual Analysis to Identify Patterns and Connections: What sets AI apart from generic automation tools is its ability to think and analyze. An example is interaction with large language models (LLMs) like ChatGPT or Gemini. These LLMs can understand the context and tailor their responses accordingly. Similarly, AI-powered data mapping solutions can analyze and interpret the data fields to intelligently identify and establish patterns and relationships. This significantly reduces the technical knowledge requirement, allowing even beginners to use data management solutions with little expertise. Simplified Schema Mapping: Data mapping algorithms also use pattern recognition to identify semantic relationships. This simplifies schema mapping as AI can find similarities between seemingly unrelated schemas. In short, AI-assisted field and schema mapping ensure smooth data integration, reducing complexity for end-users. Automated Discovery of Data Sources and Attributes: AI-powered data mappers automate the discovery of relevant data sources, attributes, and possible connections. This allows users to eliminate the lengthy steps of manual data mapping. Users can fine-tweak the AI-generated maps to their specific needs and accept or reject AI suggestions as they see fit. This significantly simplifies data mapping, letting users handle complex dataflows in relatively shorter times. Automated Discovery of Data Sources and Attributes: AI-powered data mappers automate the discovery of relevant data sources, attributes, and possible connections. This allows users to eliminate the lengthy steps of manual data mapping. Users can fine-tweak the AI-generated maps to their specific needs and accept or reject AI suggestions as they see fit. This significantly simplifies data mapping, letting users handle complex dataflows in relatively shorter times. Automated Discovery of Data Sources and Attributes: Contextual Analysis to Identify Patterns and Connections: What sets AI apart from generic automation tools is its ability to think and analyze. An example is interaction with large language models (LLMs) like ChatGPT or Gemini. These LLMs can understand the context and tailor their responses accordingly. Similarly, AI-powered data mapping solutions can analyze and interpret the data fields to intelligently identify and establish patterns and relationships. This significantly reduces the technical knowledge requirement, allowing even beginners to use data management solutions with little expertise. Contextual Analysis to Identify Patterns and Connections: What sets AI apart from generic automation tools is its ability to think and analyze. An example is interaction with large language models (LLMs) like ChatGPT or Gemini. These LLMs can understand the context and tailor their responses accordingly. Similarly, AI-powered data mapping solutions can analyze and interpret the data fields to intelligently identify and establish patterns and relationships. This significantly reduces the technical knowledge requirement, allowing even beginners to use data management solutions with little expertise. Contextual Analysis to Identify Patterns and Connections: think analyze. Simplified Schema Mapping: Data mapping algorithms also use pattern recognition to identify semantic relationships. This simplifies schema mapping as AI can find similarities between seemingly unrelated schemas. In short, AI-assisted field and schema mapping ensure smooth data integration, reducing complexity for end-users. Simplified Schema Mapping: Data mapping algorithms also use pattern recognition to identify semantic relationships. This simplifies schema mapping as AI can find similarities between seemingly unrelated schemas. In short, AI-assisted field and schema mapping ensure smooth data integration, reducing complexity for end-users. Simplified Schema Mapping: AI and Data Mapping: Why It’s a Good Combination Data mapping is a crucial step, but it can get repetitive and taxing quickly. By incorporating AI, data management platforms can streamline, speed up, and simplify the entire process for their end-users. Moreover, by cutting the requirement for technical knowledge, software vendors and organizations alike can promote data literacy among their internal and external stakeholders. As a result, organizations can promote a more efficient and effective use of data across their functions. For instance, marketers without coding experience can gather actionable campaign insights. Similarly, the Research and Development team can leverage data from Customer Support to improve their offerings. Similarly, software vendors can cater to a larger customer base by customizing their offerings for non-technical users. They can empower their customers to move beyond the traditional approach, democratizing data management across all relevant functions. This win-win proposition should encourage AI adoption for data mapping among all stakeholders. Conclusion Combining data mapping and AI is a logical step to meet the evolving needs of data management for all stakeholders. For businesses, it democratizes data management, simplifies the data mapping process, and saves time and costs. For software vendors, this integration provides access to a larger audience, increasing profitability and reach. For end users, the AI and data mapping combination makes their day-to-day work easier, faster, and more effective.

How AI-Powered Data Mapping is Democratizing Data Management 

What Does It Take to Break Into the Global B2C eCommerce Market in 2024?

2024 সালে গ্লোবাল B2C ইকমার্স মার্কেটে প্রবেশ করতে কী লাগবে?

Was braucht man, um im Jahr 2024 in den globalen B2C-E-Commerce-Markt einzusteigen?

¿Qué se necesita para ingresar al mercado global de comercio electrónico B2C en 2024?

Que faut-il pour percer sur le marché mondial du commerce électronique B2C en 2024 ?

2024 में वैश्विक B2C ईकॉमर्स बाज़ार में प्रवेश करने के लिए क्या करना होगा?

2024 年にグローバル B2C 電子商取引市場に参入するには何が必要ですか?

2024년 글로벌 B2C 전자상거래 시장에 진출하려면 무엇이 필요합니까?

O que é necessário para entrar no mercado global de comércio eletrônico B2C em 2024?

Что нужно, чтобы выйти на глобальный рынок электронной коммерции B2C в 2024 году?

2024'te Küresel B2C e-Ticaret Pazarına Girmek İçin Ne Gerekiyor?

Cần điều gì để thâm nhập thị trường thương mại điện tử B2C toàn cầu vào năm 2024?

2024 年如何才能打入全球 B2C 电子商务市场？

Microsoft WordPad, launched in 1995 as a word processor for basic file editing and formatting, is finally being removed from all editions of Windows, starting with Windows 11, version 24H2, and Windows Server 2025. The exact reason behind this removal is unclear, but Microsoft stated that most of its features, including new ones, have been added to  Notepad, which is more feature-rich than WordPad and allows users to transition seamlessly. However, many users didn’t agree, given the fact that WordPad offers more features than any plain text editor, including support for ODF and RTF file formats without requiring additional installation. Look, there could be many more reasons why users might need the WordPad back, but if the built-in support for ODF and RTF file formats is one reason, then note that you can open and edit these files using Microsoft Word, LibreOffice, or OnlyOffice. Moreover, if there is any other reason you want the original WordPad  back on your Windows 11 and 10 system, then read the entire article to  learn how to install WordPad on Windows 11 and 10 in the right way. How to Install WordPad on Windows 11, 10 Winaero  is a popular website that focuses on providing high-quality free apps,  themes, and tutorials for Windows. It’s a trusted site that has been serving millions of users since 2011. It offers the original WordPad package without any tampering and  supports both 32-bit and 64-bit systems. If you dislike the app after  installation, you can quickly remove it using the uninstaller. I’ve tried and tested it on my Windows 11 system, and to be frank, it  ran just like any other Windows built-in app; to be honest, I kind of  liked it—it gives you a nostalgic, childlike feeling. To quickly install WordPad on Windows 11 and 10, follow these instructions. First, download the WordPad installer for Windows 11 and 10.


Once the download is complete, go to the download folder, extract the compressed file, and double-click the extracted file to open the setup wizard (approve the UAC prompt).


When the setup wizard opens, continue by clicking “Next.“ Next, it displays the default installation location; I recommend not changing it and continuing by clicking “Next.“ Here, it will ask whether to install WordPad for the current user or for all users. If you want to install it only for yourself, select the “For the current user only” option. Otherwise, leave the options unchanged, and continue by clicking “Next.“ Finally, click “Install” to start the WordPad installation. The installation will be completed within 3 to 4 seconds. Once the installation is complete, the final finish window will appear, where you can select the “Run WordPad” option to open WordPad immediately after clicking “Finish.“ You can now enjoy WordPad on your Windows 11 and 10 systems. How to Uninstall WordPad on Windows 11, 10 To uninstall WordPad, from Windows 11 and 10, open “Settings“, go to “Apps“, then “Installed apps“, find “WordPad” in the list, click the three dots next to it, and choose “Uninstall” from the menu. Wrap Up WordPad has been closest to the hearts of most of the Windows users, including myself. It was one of the first or second Windows apps  introduced to me during my childhood. Hearing about its removal left me unaffected, as I have since transitioned to many more advanced editors  over the years. However, while writing this article, I installed and used WordPad for a while, which sparked nostalgic memories from my childhood and created a heartwarming feeling. If you’re a WordPad enthusiast, I hope you found this article useful. Microsoft WordPad , launched in 1995 as a word processor for basic file editing and formatting, is finally being removed from all editions of Windows, starting with Windows 11, version 24H2, and Windows Server 2025. Microsoft WordPad The exact reason behind this removal is unclear, but Microsoft stated that most of its features, including new ones, have been added to  Notepad, which is more feature-rich than WordPad and allows users to transition seamlessly. However, many users didn’t agree, given the fact that WordPad offers more features than any plain text editor, including support for ODF and RTF file formats without requiring additional installation. Look, there could be many more reasons why users might need the WordPad back, but if the built-in support for ODF and RTF file formats is one reason, then note that you can open and edit these files using Microsoft Word , LibreOffice , or OnlyOffice . Microsoft Word LibreOffice OnlyOffice Moreover, if there is any other reason you want the original WordPad  back on your Windows 11 and 10 system, then read the entire article to  learn how to install WordPad on Windows 11 and 10 in the right way. How to Install WordPad on Windows 11, 10 Winaero is a popular website that focuses on providing high-quality free apps,  themes, and tutorials for Windows. It’s a trusted site that has been serving millions of users since 2011. Winaero It offers the original WordPad package without any tampering and  supports both 32-bit and 64-bit systems. If you dislike the app after  installation, you can quickly remove it using the uninstaller. I’ve tried and tested it on my Windows 11 system, and to be frank, it  ran just like any other Windows built-in app; to be honest, I kind of  liked it—it gives you a nostalgic, childlike feeling. To quickly install WordPad on Windows 11 and 10, follow these instructions. First, download the WordPad installer for Windows 11 and 10. Once the download is complete, go to the download folder, extract the compressed file, and double-click the extracted file to open the setup wizard (approve the UAC prompt). When the setup wizard opens, continue by clicking “Next.“ First, download the WordPad installer for Windows 11 and 10. First, download the WordPad installer for Windows 11 and 10. download the WordPad installer Once the download is complete, go to the download folder, extract the compressed file, and double-click the extracted file to open the setup wizard (approve the UAC prompt). Once the download is complete, go to the download folder, extract the compressed file, and double-click the extracted file to open the setup wizard (approve the UAC prompt). When the setup wizard opens, continue by clicking “Next.“ When the setup wizard opens, continue by clicking “ Next. “ Next. Next, it displays the default installation location; I recommend not changing it and continuing by clicking “Next.“ Next, it displays the default installation location; I recommend not changing it and continuing by clicking “ Next. “ Next. Here, it will ask whether to install WordPad for the current user or for all users. If you want to install it only for yourself, select the “For the current user only” option. Otherwise, leave the options unchanged, and continue by clicking “Next.“ Here, it will ask whether to install WordPad for the current user or for all users. If you want to install it only for yourself, select the “ For the current user only ” option. Otherwise, leave the options unchanged, and continue by clicking “ Next. “ For the current user only Next. Finally, click “Install” to start the WordPad installation. Finally, click “ Install ” to start the WordPad installation. Install The installation will be completed within 3 to 4 seconds. Once the installation is complete, the final finish window will appear, where you can select the “Run WordPad” option to open WordPad immediately after clicking “Finish.“ Once the installation is complete, the final finish window will appear, where you can select the “ Run WordPad ” option to open WordPad immediately after clicking “ Finish. “ Run WordPad Finish. You can now enjoy WordPad on your Windows 11 and 10 systems. You can now enjoy WordPad on your Windows 11 and 10 systems. How to Uninstall WordPad on Windows 11, 10 To uninstall WordPad, from Windows 11 and 10, open “ Settings “, go to “ Apps “, then “ Installed apps “, find “ WordPad ” in the list, click the three dots next to it, and choose “ Uninstall ” from the menu. Settings Apps Installed apps WordPad Uninstall Wrap Up WordPad has been closest to the hearts of most of the Windows users, including myself. It was one of the first or second Windows apps  introduced to me during my childhood. Hearing about its removal left me unaffected, as I have since transitioned to many more advanced editors  over the years. However, while writing this article, I installed and used WordPad for a while, which sparked nostalgic memories from my childhood and created a heartwarming feeling. If you’re a WordPad enthusiast, I hope you found this article useful.

How to Install WordPad on Windows 11, 10 (in the Right Way)

Building a Blockchain From Scratch (kind of) with Polkadot SDK and Pop!

Build a Real-Time Crypto Tracker with CoinGecko API and React.js

Creating High-Performing CTA’s: The Ultimate Guide

Unlocking the Power of Crypto APIs: Transforming Data Into Insight and Opportunity

ক্রিপ্টো API-এর শক্তি আনলক করা: তথ্যকে অন্তর্দৃষ্টি এবং সুযোগে রূপান্তর করা

Die Leistungsfähigkeit von Krypto-APIs freisetzen: Daten in Erkenntnisse und Chancen umwandeln

Liberando el poder de las cripto API: transformando los datos en conocimientos y oportunidades

Libérer la puissance des API cryptographiques : transformer les données en informations et en opportunités

क्रिप्टो एपीआई की शक्ति को अनलॉक करना: डेटा को अंतर्दृष्टि और अवसर में बदलना

暗号 API のパワーを解き放つ: データを洞察と機会に変える

암호화 API의 힘 활용: 데이터를 통찰력과 기회로 전환

Desbloqueando o poder das APIs criptográficas: transformando dados em insights e oportunidades

Раскрытие возможностей криптографических API: преобразование данных в понимание и возможности

Kripto API'lerinin Gücünün Kilidini Açmak: Verileri İçgörüye ve Fırsata Dönüştürmek

Khai phá sức mạnh của API tiền điện tử: Chuyển đổi dữ liệu thành thông tin chuyên sâu và cơ hội

释放加密 API 的力量：将数据转化为洞察力和机遇

Businesses today face the challenges of external threats, but internal threats are not left out either. An organization can suffer from dangers within; it could be through devious goals or carelessness. Insider threats can cause noticeable damage to the operation, finances, and reputation of a company. A Cybersecurity Insiders report reveals that 74% of companies are at least moderately vulnerable to insider threats. This piece analyzes practical steps to protect your business against these inward threats safeguarding an organization's security position and strength. Internal Threats Awareness Businesses need to be highly concerned about insider threats, as they exploit the security from within. Understanding insider threats is important as there is no one-size-fits-all definition of "insider threat," but rather several different forms in which it can manifest. Types of Insider Threats - Malicious Insiders: This is a threat that is caused by dishonest insiders who try to harm the organization on purpose by leaking confidential information, stealing data, infiltrating systems for their benefit, or causing extensive damage to the company. - Negligent Insiders: Careless insiders inadvertently harm as a subset of this type causes damage due to being unaware and faulty. They might manage sensitive data poorly, become prey to phishing scams, or simply fail to follow security procedures leading to unintended data breaches. - Compromised Insiders: These are valuable (and exploitable) employees whose credentials have been disclosed by predators on the web. Since the threat actors have already got their access to do potential damage, there is no need for a direct connection! Understanding Motives and Triggers Behind Insider Threats - Financial Gain: Your employees may even be tempted to sell sensitive information out of financial gains and other similar fraudulent activities. - Retaliation: Disgruntled employees who are unhappy in their employment, or perceive themselves as being treated unfairly might seek to retaliate. - Ideological Beliefs: An actor launches an insider attack as a result of ideological beliefs (e.g., to affect company X in order that it endorse position Y). - Lack of Awareness: Insiders who just do not know are a different matter, needless breaches caused simply by lack of awareness and training. - Outside Threat: Cyber criminals can blackmail or force employees to collude with them in their plans. Employees can be blackmailed or forced to assist cyber attackers with their malicious activities. Identifying Potential Insider Threats You need to be able to identify what these insider threats look like; this way, you can take the necessary steps to prevent them within your business. Here is how to spot the signs and make it right before it's too late. Insider threat-susceptible employees have various behavioral changes that raise flags. Look out for recurring arguments with co-workers, increased stress, and immediate financial issues accompanied by mysterious loyalty shifts. These behaviors might point to someone likely to be a threat due to external influences or personal problems. There are indications that the work may be facing a new threat. If you detect anything which may include logging in at odd hours of the day or using authorized devices as needed to access critical data, such irregular trends can help locate trouble before it even becomes a hurdle. Observation is key in the identification of insider threats. Using watchdog tools monitors the movement of files, emails, and odd activities. Maintaining employee confidentiality is key, but as long as monitoring practices are fair and transparent they can end up serving both the employees' mutual interests as well as those of the company. Operational data analytics and machine learning are advanced technologies that can search through a mass depository of data, allowing for the identification of anomalous activities above what any number of human observers could ever locate. Regularly training the models on new data is likely to make them more effective at identifying potential risks. Implementing Effective Security Policies To ensure the protection of sensitive data and continuity in business, establishing an effective security policy is essential. You can implement these policies efficiently through: 1. Creating a Sophisticated Insider Threat Detection Program Develop a comprehensive insider threat detection program. This has to do with monitoring the activities of employees by using advanced analytics to identify irregularities and set up alarms for suspicious activities. Being proactive will recognize threats before they cause danger. 2. Establishing Clear Policies and Procedures for Handling Sensitive Data It is important to have clear policies and methods for managing sensitive information. Specify what makes a piece of information sensitive and make rules for its entry, storage, and transfer. Ensure all employees understand these rules and the importance of complying with them. 3. The Importance of Background Checks and Vetting Processes Carrying out thorough checks and examination processes is important when it comes to cybersecurity for small businesses and big organizations too. Before hiring, perform a thorough background check, and verify the integrity and reliability of potential employees. Review these checks regularly to ensure continuous loyalty. 4. Regularly Updating and Enforcing Security Protocols Safety measures should be flexible, not static. Update your safety measures often to cater to new threats and vulnerabilities. A periodic training session should be conducted to keep employees updated on the latest security practices and ensure compliance with standard procedures. Employee Education and Training Consistent cybersecurity awareness training sessions keep employees updated on new threats and best practices to avoid them. These sessions should be very engaging and updated frequently to address new security challenges. Employees must understand why cybersecurity and data protection are vital. By highlighting the potential risks and impacts of data breaches, you can foster a sense of responsibility and vigilance among your staff. Encourage a sense of responsibility and caution among your employees by making employees understand the importance of data protection and cyber security, and also enlighten them on the consequences that come with cyber threats. Establishing a culture of security involves incorporating cybersecurity practices into day-to-day routine. There should be open discussions with employees about security and good practices, ensuring that everyone from the top to entry-level employees stays committed to maintaining a secure workspace. Technological Solutions to Mitigate Insider Threats Leveraging these advanced cybersecurity tools and software can help protect your business from cyber threats. 1. Utilizing Advanced Cybersecurity Tools and Software For identifying and getting rid of insider threats, advanced cybersecurity tools are integral to providing comprehensive protection by observing, identifying, and responding to questionable activities within your network. 2. Intrusion Detection Systems (IDS) IDS monitors network traffic for irregular activities and keeps you alert to potential insider threats. By finding anomalies, IDS facilitates fast response to prevent damage. 3. Data Loss Prevention (DLP) Solutions DLP solutions protect sensitive information from being accessed or shared inappropriately. It monitors data transfers and ensures that critical information remains secure, reducing the risk of insider threats. 4. User and Entity Behavior Analytics (UEBA) User and Entity Behavior Analytics tools examine the behavior of users and entities within your network. By establishing baseline behavior patterns, UEBA can detect deviations from normal behaviors that may indicate insider threats; this proactive approach allows you to address issues before they escalate. Response and Recovery Strategies Here’s a simple guide to developing effective response and recovery strategies for insider threats. 1. Developing an Incident Response Plan Creating a customized incident response plan specific to insider threats is essential. This plan should outline clear steps and assign roles to team members to ensure a swift and organized response. 2. Immediate Steps After Identifying an Insider Threat After detecting an insider threat, act fast; isolate affected systems, change access credentials, and begin an internal investigation. Quick action can prevent further damage and loss. 3. Communicating With Affected Parties In this situation, effective communication is very important. Bring it to the attention of both customers and employees and be transparent about the incident immediately. Addressing the issue without avoidance can help manage public relations and maintain trust. 4. Post-Incident Analysis and Future Defense After finding a solution to the incident, carry out a post-incident analysis to identify the root cause and security vulnerabilities. Use these insights to strengthen your defenses and update your incident response plan to protect your business in the future. Safeguarding Your Business From Insider Threats To ensure the security of your business from insider threats you need a proactive approach that should also be an adequate mix of tough policies, advanced technologies, and constant employee treason. Insight into the various forms of insider threats, combined with robustly executed security and a vigilant culture can significantly mitigate those risks. Be vigilant, prioritize security, and continually update your approaches to ensure that your business is well-protected inside as well as outside. Feature image source Businesses today face the challenges of external threats, but internal threats are not left out either. An organization can suffer from dangers within; it could be through devious goals or carelessness. Insider threats can cause noticeable damage to the operation, finances, and reputation of a company. A Cybersecurity Insiders report reveals that 74% of companies are at least moderately vulnerable to insider threats. This piece analyzes practical steps to protect your business against these inward threats safeguarding an organization's security position and strength. 74% of companies Internal Threats Awareness Businesses need to be highly concerned about insider threats, as they exploit the security from within. Understanding insider threats is important as there is no one-size-fits-all definition of "insider threat," but rather several different forms in which it can manifest. Types of Insider Threats - Malicious Insiders : This is a threat that is caused by dishonest insiders who try to harm the organization on purpose by leaking confidential information, stealing data, infiltrating systems for their benefit, or causing extensive damage to the company. - Malicious Insiders - Negligent Insiders : Careless insiders inadvertently harm as a subset of this type causes damage due to being unaware and faulty. They might manage sensitive data poorly, become prey to phishing scams, or simply fail to follow security procedures leading to unintended data breaches. - Negligent Insiders - Compromised Insiders : These are valuable (and exploitable) employees whose credentials have been disclosed by predators on the web. Since the threat actors have already got their access to do potential damage, there is no need for a direct connection! - Compromised Insiders Understanding Motives and Triggers Behind Insider Threats - Financial Gain : Your employees may even be tempted to sell sensitive information out of financial gains and other similar fraudulent activities. - Financial Gain - Retaliation: Disgruntled employees who are unhappy in their employment, or perceive themselves as being treated unfairly might seek to retaliate. - Retaliation: - Ideological Beliefs : An actor launches an insider attack as a result of ideological beliefs (e.g., to affect company X in order that it endorse position Y). - Ideological Beliefs - Lack of Awareness: Insiders who just do not know are a different matter, needless breaches caused simply by lack of awareness and training. - Lack of Awareness: - Outside Threat : Cyber criminals can blackmail or force employees to collude with them in their plans. Employees can be blackmailed or forced to assist cyber attackers with their malicious activities. - Outside Threat Identifying Potential Insider Threats Identifying Potential Insider Threats You need to be able to identify what these insider threats look like; this way, you can take the necessary steps to prevent them within your business. Here is how to spot the signs and make it right before it's too late. Insider threat-susceptible employees have various behavioral changes that raise flags. Look out for recurring arguments with co-workers, increased stress, and immediate financial issues accompanied by mysterious loyalty shifts. These behaviors might point to someone likely to be a threat due to external influences or personal problems. There are indications that the work may be facing a new threat. If you detect anything which may include logging in at odd hours of the day or using authorized devices as needed to access critical data, such irregular trends can help locate trouble before it even becomes a hurdle. Observation is key in the identification of insider threats. Using watchdog tools monitors the movement of files, emails, and odd activities. Maintaining employee confidentiality is key, but as long as monitoring practices are fair and transparent they can end up serving both the employees' mutual interests as well as those of the company. Operational data analytics and machine learning are advanced technologies that can search through a mass depository of data, allowing for the identification of anomalous activities above what any number of human observers could ever locate. Regularly training the models on new data is likely to make them more effective at identifying potential risks. Implementing Effective Security Policies To ensure the protection of sensitive data and continuity in business, establishing an effective security policy is essential. You can implement these policies efficiently through: 1. Creating a Sophisticated Insider Threat Detection Program Develop a comprehensive insider threat detection program. This has to do with monitoring the activities of employees by using advanced analytics to identify irregularities and set up alarms for suspicious activities. Being proactive will recognize threats before they cause danger. 2. Establishing Clear Policies and Procedures for Handling Sensitive Data It is important to have clear policies and methods for managing sensitive information. Specify what makes a piece of information sensitive and make rules for its entry, storage, and transfer. Ensure all employees understand these rules and the importance of complying with them. 3. The Importance of Background Checks and Vetting Processes Carrying out thorough checks and examination processes is important when it comes to cybersecurity for small businesses and big organizations too. Before hiring, perform a thorough background check, and verify the integrity and reliability of potential employees. Review these checks regularly to ensure continuous loyalty. cybersecurity for small businesses 4. Regularly Updating and Enforcing Security Protocols Safety measures should be flexible, not static. Update your safety measures often to cater to new threats and vulnerabilities. A periodic training session should be conducted to keep employees updated on the latest security practices and ensure compliance with standard procedures. Employee Education and Training Consistent cybersecurity awareness training sessions keep employees updated on new threats and best practices to avoid them. These sessions should be very engaging and updated frequently to address new security challenges. Employees must understand why cybersecurity and data protection are vital. By highlighting the potential risks and impacts of data breaches, you can foster a sense of responsibility and vigilance among your staff. Encourage a sense of responsibility and caution among your employees by making employees understand the importance of data protection and cyber security, and also enlighten them on the consequences that come with cyber threats. Establishing a culture of security involves incorporating cybersecurity practices into day-to-day routine. There should be open discussions with employees about security and good practices, ensuring that everyone from the top to entry-level employees stays committed to maintaining a secure workspace. Technological Solutions to Mitigate Insider Threats Leveraging these advanced cybersecurity tools and software can help protect your business from cyber threats. 1. Utilizing Advanced Cybersecurity Tools and Software For identifying and getting rid of insider threats, advanced cybersecurity tools are integral to providing comprehensive protection by observing, identifying, and responding to questionable activities within your network. 2. Intrusion Detection Systems (IDS) IDS monitors network traffic for irregular activities and keeps you alert to potential insider threats. By finding anomalies, IDS facilitates fast response to prevent damage. 3. Data Loss Prevention (DLP) Solutions DLP solutions protect sensitive information from being accessed or shared inappropriately. It monitors data transfers and ensures that critical information remains secure, reducing the risk of insider threats. 4. User and Entity Behavior Analytics (UEBA) User and Entity Behavior Analytics (UEBA) User and Entity Behavior Analytics tools examine the behavior of users and entities within your network. By establishing baseline behavior patterns, UEBA can detect deviations from normal behaviors that may indicate insider threats; this proactive approach allows you to address issues before they escalate. Response and Recovery Strategies Here’s a simple guide to developing effective response and recovery strategies for insider threats. 1. Developing an Incident Response Plan Creating a customized incident response plan specific to insider threats is essential. This plan should outline clear steps and assign roles to team members to ensure a swift and organized response. 2. Immediate Steps After Identifying an Insider Threat After detecting an insider threat, act fast; isolate affected systems, change access credentials, and begin an internal investigation. Quick action can prevent further damage and loss. 3. Communicating With Affected Parties In this situation, effective communication is very important. Bring it to the attention of both customers and employees and be transparent about the incident immediately. Addressing the issue without avoidance can help manage public relations and maintain trust. 4. Post-Incident Analysis and Future Defense After finding a solution to the incident, carry out a post-incident analysis to identify the root cause and security vulnerabilities. Use these insights to strengthen your defenses and update your incident response plan to protect your business in the future. Safeguarding Your Business From Insider Threats To ensure the security of your business from insider threats you need a proactive approach that should also be an adequate mix of tough policies, advanced technologies, and constant employee treason. Insight into the various forms of insider threats, combined with robustly executed security and a vigilant culture can significantly mitigate those risks. Be vigilant, prioritize security, and continually update your approaches to ensure that your business is well-protected inside as well as outside. Feature image source Feature image source source

How to Protect Your Business From Insider Threats

The Snowflake Hack and Its Domino Effect

স্নোফ্লেক হ্যাক এবং এর ডমিনো প্রভাব

Der Snowflake-Hack und sein Dominoeffekt

El truco del copo de nieve y su efecto dominó

Le Snowflake Hack et son effet domino

स्नोफ्लेक हैक और इसका डोमिनो प्रभाव

スノーフレークハッキングとそのドミノ効果

눈송이 해킹과 도미노 효과

O truque do floco de neve e seu efeito dominó

Взлом Snowflake и его эффект домино

Kar Tanesi Hilesi ve Domino Etkisi

Hack bông tuyết và hiệu ứng Domino của nó

雪花黑客及其多米诺骨牌效应

Make Sure Your QR Code Works: A Detailed QR Code Test Guide

আপনার QR কোড কাজ করে তা নিশ্চিত করুন: একটি বিস্তারিত QR কোড পরীক্ষার নির্দেশিকা

Stellen Sie sicher, dass Ihr QR-Code funktioniert: Ein ausführlicher QR-Code-Testleitfaden

Asegúrese de que su código QR funcione: una guía detallada de prueba de códigos QR

Assurez-vous que votre code QR fonctionne : un guide de test de code QR détaillé

सुनिश्चित करें कि आपका QR कोड काम करता है: एक विस्तृत QR कोड परीक्षण गाइड

QR コードが機能することを確認する: 詳細な QR コード テスト ガイド

QR 코드가 작동하는지 확인하세요: 자세한 QR 코드 테스트 가이드

Certifique-se de que seu código QR funciona: um guia detalhado de teste de código QR

Убедитесь, что ваш QR-код работает: подробное руководство по тестированию QR-кода

QR Kodunuzun Çalıştığından Emin Olun: Ayrıntılı QR Kodu Test Kılavuzu

Đảm bảo mã QR của bạn hoạt động: Hướng dẫn kiểm tra mã QR chi tiết

确保您的二维码有效：详细的二维码测试指南

Translating Business Needs into Technical Solutions

Why 'Leave Your Comfort Zone' Is Really Bad Advice (And What To Do Instead)

কেন 'আপনার কমফোর্ট জোন ছেড়ে দিন' সত্যিই খারাপ পরামর্শ (এবং পরিবর্তে কি করতে হবে)

Warum „Verlassen Sie Ihre Komfortzone“ wirklich ein schlechter Rat ist (und was Sie stattdessen tun sollten)

Por qué 'salir de tu zona de confort' es realmente un mal consejo (y qué hacer en su lugar)

Pourquoi « quitter votre zone de confort » est un très mauvais conseil (et que faire à la place)

'अपना कम्फर्ट जोन छोड़ो' वास्तव में बुरी सलाह क्यों है (और इसके बजाय क्या करें)

「自分の快適ゾーンから抜け出す」というのは本当に悪いアドバイスである理由（そして代わりに何をすべきか）

'편안함을 벗어나라'는 것이 정말 나쁜 조언인 이유(대신 해야 할 일)

Por que 'deixar sua zona de conforto' é um conselho realmente ruim (e o que fazer em vez disso)

Почему «выйти из зоны комфорта» — действительно плохой совет (и что делать вместо этого)

'Konfor Alanınızı Bırakın' Neden Gerçekten Kötü Bir Tavsiyedir (Ve Bunun Yerine Ne Yapmalı)

Tại sao 'Rời khỏi vùng thoải mái của bạn' là lời khuyên thực sự tồi tệ (và thay vào đó nên làm gì)

为什么“离开你的舒适区”是糟糕的建议（以及应该怎么做）

Generative AI is a type of machine learning and artificial intelligence (AI) that is garnering a lot of attention right now, and we want to help keep you a step ahead by sharing the latest training available from Google Cloud. In this blog, we have compiled resources to help you learn about generative AI, how it can impact your business, and how to use it. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. We have brand-new generative AI training options, and are constantly adding to our training catalog on Google Cloud Skills Boost. This includes two learning paths that each feature comprehensive content: one is for the non-technical audience (introductory) ‘Introduction to Generative AI learning path’, and the other is for technical practitioners (more advanced) ‘Generative AI for Developers learning path’. Prefer less of a time commitment? Opt for individual courses and labs with the topics that suit your specific interest. Powered by Google Cloud technology, generative AI is reimagining the way that organizations do business by leveraging data. The use cases are far-ranging, from having smarter conversations with and creating rich experiences for customers, to enhancing business processes, to helping developers write code, and more. Google Cloud has been working for decades to bring AI technology solutions to organizations, and our tools make it easier to build experiences across our cloud portfolio. Whether you’re executive-level, an IT decision maker, in a non-technical role, or a technical practitioner, we have videos, courses and labs to help you learn about the power of generative AI. Plus, labs give you direct access to Generative AI Studio and Vertex AI (Google Cloud’s machine learning platform) to get hands-on, technical experience. Get started with our training list below. No-cost foundational courses: no technical experience needed Don’t have a lot of time but want to learn the basics? Our no-cost Introduction to Generative AI course is a great place to start. It takes about 45 minutes to finish. If getting started has you hungry to learn more, continue your no-cost learning to earn the Generative AI Fundamentals skill badge. It includes the course above, plus two other courses: ‘Introduction to Large Language Models’ and ‘Introduction to Responsible AI’. In total, this takes about two hours to complete and you’ll earn a digital skill badge to share on your resume and social channels to validate your foundational understanding of Google Cloud generative AI technology. Dig in deeper with our generative AI learning paths For a more comprehensive learning experience, choose from our two new gen AI learning paths — a mix of courses, labs and skill badges. Please note: we plan to add new trainings to this list, so keep checking back for more. Introduction to Generative AI - this path includes no-cost video courses. Content is non-technical, introductory, and designed for the tech-adjacent audience: roles like sales, HR, marketing and operations. Here is a look at the content: Introduction to Generative AI - course
Introduction to Large Language Models - course
Introduction to Responsible AI - course
Generative AI Fundamentals - earn a skill badge
Responsible AI: Applying AI Principals with Google Cloud - course Generative AI for Developers - this path includes a combination of technical hands-on labs and courses and requires Google Cloud credits to complete. It is designed for technical developers who work with gen AI, and includes the introductory training as a prerequisite. Content includes: Responsible AI for Developers - course
Introduction to Image Generation - course
Attention Mechanism - course
Encoder-Decoder Architecture - course
Transformer Models and BERT Model - course
Create Image Captioning Models - course
Introduction to Generative AI Studio - course
Generative AI Explorer: Vertex AI - earn a skill badge
Explore and Evaluate Models Using Model Garden - lab
Prompt Design Using PaLM - lab Gain technical experience with labs We currently offer these generative AI labs for anyone looking to get some hands-on experience by working directly in Google Cloud: Get Started with Generative AI Studio (requires one credit) - introductory, 60 minutes
Generative AI with Vertex AI: Getting Started (requires one credit) - introductory, 90 minutes
Generative AI with Vertex AI: Prompt Design (requires one credit) - introductory, 90 minutes
Vertex AI PaLM API: Qwik Start (requires one credit) - introductory, 60 minutes
Integrate Search in Applications Using Gen AI App Builder (requires five credits) - introductory, 90 minutes
Prompt Design using PaLM (requires one credit)  - intermediate, 90 minutes
Explore and Evaluate Models using Model Garden (requires five credits) - intermediate, 60 minutes Text embeddings with DeepLearning.AI and Andrew Ng We have brand new content built in collaboration with DeepLearning.AI, taught by Andrew Ng, founder of DeepLearning.AI and a globally recognized leader on the topic. Enroll for no-cost in “Understanding and Applying Text Embeddings with Vertex AI” to learn various tasks like classification, outlier detection, text clustering, and semantic search. You’ll also learn to integrate them into LLM applications. Check out the video below to hear about these exciting opportunities found within text embeddings and generative AI. https://youtu.be/9SYpG_tFT38?si=BqFxnCisV2z5Xs2h&embedable=true New for technical practitioners: Intro to AI and ML Learn the big picture of how Google supports the data-to-AI journey and how generative AI is embedded in the AI development platform in our new course, Introduction to AI and Machine Learning on Google Cloud, designed mainly for technical practitioners — AI developers, data scientists, and ML engineers. The course covers the technologies, products and tools used to build an ML model, an ML pipeline, and a gen AI project based on the goals of data and AI practitioners. Made up of four primary modules that include labs and quizzes, this introductory course takes about six hours to complete and requires 12 credits. Stay on the cloud fast track with Innovators Plus Generative AI is  constantly evolving, and we’re developing new training materials to help you keep your career knowledge and skills up to date. An Innovators Plus subscription gives you access not only to generative AI content, but the full Google Cloud Skills Boost catalog of on-demand training for a whole year. You get $1,500 in developer benefits for only $299, including up to $1,000 in Google Cloud credits. Considering getting certified? You’ll also get an exam voucher, plus special access to Google Cloud experts and execs, live learning events, and more to round out your knowledge. Check out the details and sign up here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. Originally published here. Contributed by: Google Cloud Generative AI is a type of machine learning and artificial intelligence (AI) that is garnering a lot of attention right now, and we want to help keep you a step ahead by sharing the latest training available from Google Cloud. In this blog, we have compiled resources to help you learn about generative AI, how it can impact your business, and how to use it. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here . here We have brand-new generative AI training options, and are constantly adding to our training catalog on Google Cloud Skills Boost . This includes two learning paths that each feature comprehensive content: one is for the non-technical audience (introductory) ‘ Introduction to Generative AI learning path ’, and the other is for technical practitioners (more advanced) ‘ Generative AI for Developers learning path ’. Prefer less of a time commitment? Opt for individual courses and labs with the topics that suit your specific interest. brand-new generative AI training options, and are constantly adding to our training catalog on Google Cloud Skills Boost Introduction to Generative AI learning path Introduction to Generative AI learning path Generative AI for Developers learning path Generative AI for Developers learning path Powered by Google Cloud technology, generative AI is reimagining the way that organizations do business by leveraging data. The use cases are far-ranging , from having smarter conversations with and creating rich experiences for customers, to enhancing business processes, to helping developers write code, and more. use cases are far-ranging use cases are far-ranging Google Cloud has been working for decades to bring AI technology solutions to organizations, and our tools make it easier to build experiences across our cloud portfolio. Whether you’re executive-level, an IT decision maker, in a non-technical role, or a technical practitioner, we have videos, courses and labs to help you learn about the power of generative AI . Plus, labs give you direct access to Generative AI Studio and Vertex AI (Google Cloud’s machine learning platform) to get hands-on, technical experience. Get started with our training list below. Whether you’re executive-level, an IT decision maker, in a non-technical role, or a technical practitioner, we have videos, courses and labs to help you learn about the power of generative AI No-cost foundational courses: no technical experience needed Don’t have a lot of time but want to learn the basics? Our no-cost Introduction to Generative AI course is a great place to start. It takes about 45 minutes to finish. Our no-cost Introduction to Generative AI course is a great place to start. It takes about 45 minutes to finish. Introduction to Generative AI Introduction to Generative AI If getting started has you hungry to learn more, continue your no-cost learning to earn the Generative AI Fundamentals skill badge . It includes the course above, plus two other courses: ‘Introduction to Large Language Models’ and ‘Introduction to Responsible AI’. In total, this takes about two hours to complete and you’ll earn a digital skill badge to share on your resume and social channels to validate your foundational understanding of Google Cloud generative AI technology. continue your no-cost learning Generative AI Fundamentals skill badge Generative AI Fundamentals skill badge two hours to complete Dig in deeper with our generative AI learning paths For a more comprehensive learning experience, choose from our two new gen AI learning paths — a mix of courses, labs and skill badges. Please note: we plan to add new trainings to this list, so keep checking back for more. Introduction to Generative AI - this path includes no-cost video courses . Content is non-technical, introductory, and designed for the tech-adjacent audience: roles like sales, HR, marketing and operations. Here is a look at the content: Introduction to Generative AI Introduction to Generative AI Introduction to Generative AI this path includes no-cost video courses Introduction to Generative AI - course Introduction to Large Language Models - course Introduction to Responsible AI - course Generative AI Fundamentals - earn a skill badge Responsible AI: Applying AI Principals with Google Cloud - course Introduction to Generative AI - course Introduction to Large Language Models - course Introduction to Responsible AI - course Generative AI Fundamentals - earn a skill badge Responsible AI: Applying AI Principals with Google Cloud - course Generative AI for Developers - this path includes a combination of technical hands-on labs and courses and requires Google Cloud credits to complete. It is designed for technical developers who work with gen AI, and includes the introductory training as a prerequisite. Content includes: Generative AI for Developers Generative AI for Developers Generative AI for Developers Responsible AI for Developers - course Introduction to Image Generation - course Attention Mechanism - course Encoder-Decoder Architecture - course Transformer Models and BERT Model - course Create Image Captioning Models - course Introduction to Generative AI Studio - course Generative AI Explorer: Vertex AI - earn a skill badge Explore and Evaluate Models Using Model Garden - lab Prompt Design Using PaLM - lab Responsible AI for Developers - course Introduction to Image Generation - course Attention Mechanism - course Encoder-Decoder Architecture - course Transformer Models and BERT Model - course Create Image Captioning Models - course Introduction to Generative AI Studio - course Generative AI Explorer: Vertex AI - earn a skill badge Explore and Evaluate Models Using Model Garden - lab Prompt Design Using PaLM - lab Gain technical experience with labs We currently offer these generative AI labs for anyone looking to get some hands-on experience by working directly in Google Cloud: Get Started with Generative AI Studio (requires one credit) - introductory, 60 minutes Generative AI with Vertex AI: Getting Started (requires one credit) - introductory, 90 minutes Generative AI with Vertex AI: Prompt Design (requires one credit) - introductory, 90 minutes Vertex AI PaLM API: Qwik Start (requires one credit) - introductory, 60 minutes Integrate Search in Applications Using Gen AI App Builder (requires five credits) - introductory, 90 minutes Prompt Design using PaLM (requires one credit)  - intermediate, 90 minutes Explore and Evaluate Models using Model Garden (requires five credits) - intermediate, 60 minutes Get Started with Generative AI Studio (requires one credit) - introductory, 60 minutes Get Started with Generative AI Studio Get Started with Generative AI Studio Generative AI with Vertex AI: Getting Started (requires one credit) - introductory, 90 minutes Generative AI with Vertex AI: Getting Started Generative AI with Vertex AI: Getting Started Generative AI with Vertex AI: Prompt Design (requires one credit) - introductory, 90 minutes Generative AI with Vertex AI: Prompt Design Generative AI with Vertex AI: Prompt Design Vertex AI PaLM API: Qwik Start (requires one credit) - introductory, 60 minutes Vertex AI PaLM API: Qwik Start Vertex AI PaLM API: Qwik Start Integrate Search in Applications Using Gen AI App Builder (requires five credits) - introductory, 90 minutes Integrate Search in Applications Using Gen AI App Builder Integrate Search in Applications Using Gen AI App Builder Prompt Design using PaLM (requires one credit)  - intermediate, 90 minutes Prompt Design using PaLM Prompt Design using PaLM Explore and Evaluate Models using Model Garden (requires five credits) - intermediate, 60 minutes Explore and Evaluate Models using Model Garden Explore and Evaluate Models using Model Garden Text embeddings with DeepLearning.AI and Andrew Ng We have brand new content built in collaboration with DeepLearning.AI , taught by Andrew Ng, founder of DeepLearning.AI and a globally recognized leader on the topic. Enroll for no-cost in “Understanding and Applying Text Embeddings with Vertex AI” to learn various tasks like classification, outlier detection, text clustering, and semantic search. You’ll also learn to integrate them into LLM applications. Check out the video below to hear about these exciting opportunities found within text embeddings and generative AI. DeepLearning.AI DeepLearning.AI DeepLearning.AI DeepLearning.AI Enroll for no-cost in “Understanding and Applying Text Embeddings with Vertex AI” “Understanding and Applying Text Embeddings with Vertex AI” “Understanding and Applying Text Embeddings with Vertex AI” https://youtu.be/9SYpG_tFT38?si=BqFxnCisV2z5Xs2h&embedable=true https://youtu.be/9SYpG_tFT38?si=BqFxnCisV2z5Xs2h&embedable=true New for technical practitioners: Intro to AI and ML Learn the big picture of how Google supports the data-to-AI journey and how generative AI is embedded in the AI development platform in our new course, Introduction to AI and Machine Learning on Google Cloud , designed mainly for technical practitioners — AI developers, data scientists, and ML engineers. The course covers the technologies, products and tools used to build an ML model, an ML pipeline, and a gen AI project based on the goals of data and AI practitioners. Made up of four primary modules that include labs and quizzes, this introductory course takes about six hours to complete and requires 12 credits. Introduction to AI and Machine Learning on Google Cloud Introduction to AI and Machine Learning on Google Cloud this introductory course takes about six hours to complete and requires 12 credits. Stay on the cloud fast track with Innovators Plus Generative AI is  constantly evolving, and we’re developing new training materials to help you keep your career knowledge and skills up to date. An Innovators Plus subscription gives you access not only to generative AI content, but the full Google Cloud Skills Boost catalog of on-demand training for a whole year. You get $1,500 in developer benefits for only $299, including up to $1,000 in Google Cloud credits. Considering getting certified? You’ll also get an exam voucher, plus special access to Google Cloud experts and execs, live learning events, and more to round out your knowledge. Check out the details and sign up here . sign up here sign up here New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here . here Originally published here . here Contributed by: Google Cloud

Learn Generative AI with Google Cloud: New Courses from Introductory to Advanced Level

SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 19 of 26. B. Liquid Staking Pool Providers: Lido and Rocket Pool 238. Lido and Rocket Pool have each created and maintained respective staking programs, designed to capture the staking rewards described above. 239. Lido and Rocket Pool each call their program a “liquid staking” program because— as described below—investors are issued a tradable token in exchange for depositing funds into the program. This token represents the investor’s interest in the program. The token issued in exchange is referred to as a “liquid staking token” or “LST” and the LST can be traded on the secondary market. 240. In Lido, the LST is called stETH; in Rocket Pool, the LST is called rETH. 241. The amount of LST an investor receives is proportional to the amount of ETH they deposit. 242. These staking programs allow investors to both obtain the rewards of staking and also purportedly retain the ability to redeem the value of their investment at any time. i. The Lido Staking Program Is An Investment Contract. 243. Lido launched its liquid staking platform in December 2020. 244. To participate, investors deposit ETH with Lido. 245. In return, Lido issues the investor another crypto asset, “stETH,” representing the investor’s pro rata interest in Lido’s staking program, including the investor’s original deposit of ETH plus any accumulated returns. 246. Lido then uses investors’ deposited ETH in the Ethereum consensus mechanism to earn staking rewards—the financial returns for investors. 247. Specifically, Lido pools the ETH deposited by investors into a Lido smart contract, which initiates the creation of a validator by depositing a 32 ETH bundle to the Ethereum validator deposit contract. 248. As of June 25, 2024, over 28% of all staked ETH on Ethereum is staked in Lido’s staking program. 249. Lido takes, as a fee, 10% of the staking rewards earned. 250. The remaining rewards are accrued, pro rata, by stETH token holders. 251. Lido markets its staking program as an investment opportunity. 252. Lido also leads investors to reasonably expect that investors’ profits will come from Lido’s efforts. 253. According to Lido’s website, from December 2020 to February 2024, Lido’s staking program returned an annualized percentage gain of 3% to 9%. 254. In a blog post dated December 28, 2020, Lido stated: “Lido allows users to stake any amount of ETH – without the need to maintain complex infrastructure.” 255. From at least June 2021 to June 2024, in a “Help” article on its website, Lido stated that staking “requires expert knowledge and complex and costly infrastructure” and that through Lido “users can eliminate these inconveniences.” 256. Lido claimed in an October 2020 document posted to its website that it is “more profitable” than other staking pool providers because of its fee model and the quality of its node operators. 257. From at least February 2023 to June 2024, another “Help” article on Lido’s website claims to allocate investors’ staked ETH across multiple, high-quality validator node operators (that is, participants in the Ethereum network consensus mechanism), minimizing the risks associated with staking ETH. 258. In the same Help article, Lido states that it elects “professional and reputable node operators” and that the penalty and slashing risks are reduced “given the quality of the Lido validator set and its proven track record.” 259. In short, Lido purportedly offers investors a “simplified participation in staking”— deploying its resources and expertise to achieve staking rewards that individual investors typically would not be able to achieve on their own. 260. The holder of any stETH—whether issued directly from Lido or purchased in the secondary market—has the right to deliver the stETH to Lido to get back the pro-rata staked ETH plus accrued rewards. 261. Lido treats all investors’ deposited ETH as fungible. It does not purport to segregate investor funds. 262. In light of the above, Lido offered and sold its staking program as an investment contract. ii. The Rocket Pool Staking Program Is An Investment Contract 263. Rocket Pool launched its platform in October 2021. 264. To participate, investors deposit ETH with Rocket Pool. 265. In return, Rocket Pool issues another crypto asset, “rETH,” representing the investor’s pro rata interest in Rocket Pool’s staking program, including the investor’s original deposit of ETH plus any accumulated returns. 266. Rocket Pool then uses investors’ deposited ETH in the Ethereum consensus mechanism to earn staking rewards—the financial returns for investors. 267. Specifically, Rocket Pool pools the ETH deposited by investors into a Rocket Pool smart contract, which initiates the creation of a validator by depositing a 32-ETH bundle to the Ethereum validator deposit contract. 268. Rocket Pool takes a 0.05% fee of the staking rewards it earns. 269. The remaining staking rewards accrue, pro-rata, to investors. 270. Rocket Pool also markets its staking program as an investment opportunity. 271. According to Rocket Pool’s website, rETH “accrues value over time.” 272. Rocket Pool also leads investors to reasonably expect that investors’ profits will come from the efforts of Rocket Pool. 273. As of June 2024, Rocket Pool advertised on its website an annual percentage return of approximately 3.11%. 274. In an FAQ available on its website, Rocket Pool notes that its staking service makes staking available to investors who might not otherwise have the technical expertise necessary to interact with smart contracts or keep a node running 24/7. 275. Indeed, according to Rocket Pool’s FAQ, its program “removes several high barriers to entry that exist with Proof of Stake on Ethereum.” 276. In a January 22, 2021, Medium Post, Rocket Pool stated that its program was “an easy and permissionless way to engage in staking without needing to run any staking infrastructure or even have 32 ETH.” 277. The Rocket Pool FAQ states that it will “allow anyone to earn rewards on deposits as small as 0.01 ETH.” 278. On its website, Rocket Pool also attempts to differentiate itself from other staking pool providers, claiming that “Rocket Pool is the only staking platform with a perfect score on ethereum.org.” 279. According to Rocket Pool’s website, its protocol is highly secure and its “smart contracts have been extensively audited, multiple times, by some of the best auditors in the Ethereum ecosystem.” 280. Rocket Pool also touts other reasons for investors to stake their ETH with Rocket Pool. 281. In the January 2021 Medium post, Rocket Pool notes that the value of rETH is “protected against node slashing and downtime by several built in insurance mechanisms.” 282. Specifically, Rocket Pool requires individuals that run Rocket Pool validator nodes to put up collateral to protect against losses that may result from penalties and slashing. 283. Rocket Pool’s website states that “every rETH token is exactly the same, you will automatically receive the benefits of staking just by holding the token!” (Emphasis in original.) 284. In light of the above, Rocket Pool offered and sold its staking program as an investment contract. 285. Neither Lido nor Rocket Pool have ever filed registration statements with the SEC for the offer and sale of their respective staking program investment contracts. 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 June 28, 2024, storage.courtlistener.com 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. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 19 of 26. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 19 of 26. HackerNoon’s Legal PDF Series here B. Liquid Staking Pool Providers: Lido and Rocket Pool 238. Lido and Rocket Pool have each created and maintained respective staking programs, designed to capture the staking rewards described above. 239. Lido and Rocket Pool each call their program a “liquid staking” program because— as described below—investors are issued a tradable token in exchange for depositing funds into the program. This token represents the investor’s interest in the program. The token issued in exchange is referred to as a “liquid staking token” or “LST” and the LST can be traded on the secondary market. 240. In Lido, the LST is called stETH; in Rocket Pool, the LST is called rETH. 241. The amount of LST an investor receives is proportional to the amount of ETH they deposit. 242. These staking programs allow investors to both obtain the rewards of staking and also purportedly retain the ability to redeem the value of their investment at any time. i. The Lido Staking Program Is An Investment Contract. i. The Lido Staking Program Is An Investment Contract. 243. Lido launched its liquid staking platform in December 2020. 244. To participate, investors deposit ETH with Lido. 245. In return, Lido issues the investor another crypto asset, “stETH,” representing the investor’s pro rata interest in Lido’s staking program, including the investor’s original deposit of ETH plus any accumulated returns. 246. Lido then uses investors’ deposited ETH in the Ethereum consensus mechanism to earn staking rewards—the financial returns for investors. 247. Specifically, Lido pools the ETH deposited by investors into a Lido smart contract, which initiates the creation of a validator by depositing a 32 ETH bundle to the Ethereum validator deposit contract. 248. As of June 25, 2024, over 28% of all staked ETH on Ethereum is staked in Lido’s staking program. 249. Lido takes, as a fee, 10% of the staking rewards earned. 250. The remaining rewards are accrued, pro rata, by stETH token holders. 251. Lido markets its staking program as an investment opportunity. 252. Lido also leads investors to reasonably expect that investors’ profits will come from Lido’s efforts. 253. According to Lido’s website, from December 2020 to February 2024, Lido’s staking program returned an annualized percentage gain of 3% to 9%. 254. In a blog post dated December 28, 2020, Lido stated: “Lido allows users to stake any amount of ETH – without the need to maintain complex infrastructure.” 255. From at least June 2021 to June 2024, in a “Help” article on its website, Lido stated that staking “requires expert knowledge and complex and costly infrastructure” and that through Lido “users can eliminate these inconveniences.” 256. Lido claimed in an October 2020 document posted to its website that it is “more profitable” than other staking pool providers because of its fee model and the quality of its node operators. 257. From at least February 2023 to June 2024, another “Help” article on Lido’s website claims to allocate investors’ staked ETH across multiple, high-quality validator node operators (that is, participants in the Ethereum network consensus mechanism), minimizing the risks associated with staking ETH. 258. In the same Help article, Lido states that it elects “professional and reputable node operators” and that the penalty and slashing risks are reduced “given the quality of the Lido validator set and its proven track record.” 259. In short, Lido purportedly offers investors a “simplified participation in staking”— deploying its resources and expertise to achieve staking rewards that individual investors typically would not be able to achieve on their own. 260. The holder of any stETH—whether issued directly from Lido or purchased in the secondary market—has the right to deliver the stETH to Lido to get back the pro-rata staked ETH plus accrued rewards. 261. Lido treats all investors’ deposited ETH as fungible. It does not purport to segregate investor funds. 262. In light of the above, Lido offered and sold its staking program as an investment contract. ii. The Rocket Pool Staking Program Is An Investment Contract ii. The Rocket Pool Staking Program Is An Investment Contract 263. Rocket Pool launched its platform in October 2021. 264. To participate, investors deposit ETH with Rocket Pool. 265. In return, Rocket Pool issues another crypto asset, “rETH,” representing the investor’s pro rata interest in Rocket Pool’s staking program, including the investor’s original deposit of ETH plus any accumulated returns. 266. Rocket Pool then uses investors’ deposited ETH in the Ethereum consensus mechanism to earn staking rewards—the financial returns for investors. 267. Specifically, Rocket Pool pools the ETH deposited by investors into a Rocket Pool smart contract, which initiates the creation of a validator by depositing a 32-ETH bundle to the Ethereum validator deposit contract. 268. Rocket Pool takes a 0.05% fee of the staking rewards it earns. 269. The remaining staking rewards accrue, pro-rata, to investors. 270. Rocket Pool also markets its staking program as an investment opportunity. 271. According to Rocket Pool’s website, rETH “accrues value over time.” 272. Rocket Pool also leads investors to reasonably expect that investors’ profits will come from the efforts of Rocket Pool. 273. As of June 2024, Rocket Pool advertised on its website an annual percentage return of approximately 3.11%. 274. In an FAQ available on its website, Rocket Pool notes that its staking service makes staking available to investors who might not otherwise have the technical expertise necessary to interact with smart contracts or keep a node running 24/7. 275. Indeed, according to Rocket Pool’s FAQ, its program “removes several high barriers to entry that exist with Proof of Stake on Ethereum.” 276. In a January 22, 2021, Medium Post, Rocket Pool stated that its program was “an easy and permissionless way to engage in staking without needing to run any staking infrastructure or even have 32 ETH.” 277. The Rocket Pool FAQ states that it will “allow anyone to earn rewards on deposits as small as 0.01 ETH.” 278. On its website, Rocket Pool also attempts to differentiate itself from other staking pool providers, claiming that “Rocket Pool is the only staking platform with a perfect score on ethereum.org.” 279. According to Rocket Pool’s website, its protocol is highly secure and its “smart contracts have been extensively audited, multiple times, by some of the best auditors in the Ethereum ecosystem.” 280. Rocket Pool also touts other reasons for investors to stake their ETH with Rocket Pool. 281. In the January 2021 Medium post, Rocket Pool notes that the value of rETH is “protected against node slashing and downtime by several built in insurance mechanisms.” 282. Specifically, Rocket Pool requires individuals that run Rocket Pool validator nodes to put up collateral to protect against losses that may result from penalties and slashing. 283. Rocket Pool’s website states that “every rETH token is exactly the same, you will automatically receive the benefits of staking just by holding the token!” (Emphasis in original.) automatically receive the benefits of staking just by holding the token!” 284. In light of the above, Rocket Pool offered and sold its staking program as an investment contract. 285. Neither Lido nor Rocket Pool have ever filed registration statements with the SEC for the offer and sale of their respective staking program investment contracts. 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 June 28, 2024, storage.courtlistener.com 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 June 28, 2024, storage.courtlistener.com 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.com

Crypto Giants Lido and Rocket Pool Face SEC Scrutiny Over Staking Programs

ChatGPT is an advanced generative AI model developed by OpenAI that is capable of generating human-like responses, summarizing thousands of lines of text, and producing functional programming code in hundreds of languages. So far, you can access ChatGPT through its official website, third-party apps, or by installing its Android and iOS apps on your mobile devices. However, there is no indication of a native desktop app for Windows devices. Fortunately, Progressive Web App (PWA) technology is available in modern web browsers like Chrome, Edge, or Firefox, allowing you to run supported websites that implement PWA functionalities (which ChatGPT does) to run natively like a desktop app on Windows. In this guide, I'll show you how you can install and use ChatGPT as an app on your Windows 11 and 10 devices using the Chrome and Firefox browsers. Method 1: Install ChatGPT as an App on Windows 11, 10 From Chrome To install ChatGPT as an app on Windows 11 and 10 from Chrome, follow these instructions. Open the Chrome browser.
Visit the official ChatGPT website.
(Optional) Sign in with your existing account or proceed as a guest user.
Open the "menu" by clicking the three dots in the top right corner.
Select “Save and share” from the menu, and then select the “Install page as app…” option. Click on the "Install" button when the "Install this page as an app" prompt appears. The ChatGPT app will be launched as a Progressive Web App (PWA) with a shortcut icon on your desktop for easy access whenever you need it. Uninstall To uninstall the ChatGPT app from Chrome, follow these instructions. Open the Chrome browser.
Open "chrome://apps" settings page:
Click the ChatGPT app with the right mouse button, and choose "Uninstall" from the context menu. Method 2: Install ChatGPT as an App on Windows 11, 10 From Firefox Firefox does not have a direct method for installing PWAs, so you'll need to use an additional extension like Progressive Web Apps for Firefox, which is completely free, open-source, and recommended by Mozilla. To install ChatGPT as an app on Windows 11 and 10 from Firefox, follow these instructions. Open the Firefox browser.
Install the Progressive Web Apps for Firefox extension.
Follow the extension configuration instructions, and set up a suitable connector.
Visit the official ChatGPT website.
(Optional) Sign in with your existing account or proceed as a guest user.
Click the extension icon, and select "Install current site" from the dialog box. It redirects to another page where you need to enter some necessary details. Since the extension is launched from the tab with ChatGPT open, it will automatically pick the necessary details, and you just have to click on the "Install web app" button. That's it! You can now open the ChatGPT app from the extension dialog box. Well, this method allows you to install ChatGPT as an app from Firefox on Windows 11 and 10. However, as of writing this article, there is no straightforward way to create a desktop shortcut for the PWA app created using this method. Uninstall To uninstall the ChatGPT app from Firefox, follow these instructions. Open the Firefox browser.


Click the extension icon, and select the "trash" icon next to the ChatGPT app. Wrap Up Right now, the PWA is the only option to use ChatGPT as an almost-native app on Windows 11 and 10. However, OpenAI has claimed that a desktop app will be available soon, with macOS seemingly given higher priority despite Microsoft’s big chunk of investment. ChatGPT is an advanced generative AI model developed by OpenAI that is capable of generating human-like responses, summarizing thousands of lines of text, and producing functional programming code in hundreds of languages. So far, you can access ChatGPT through its official website, third-party apps, or by installing its Android and iOS apps on your mobile devices. However, there is no indication of a native desktop app for Windows devices. Fortunately, Progressive Web App (PWA) technology is available in modern web browsers like Chrome, Edge, or Firefox, allowing you to run supported websites that implement PWA functionalities (which ChatGPT does) to run natively like a desktop app on Windows. Progressive Web App (PWA) In this guide, I'll show you how you can install and use ChatGPT as an app on your Windows 11 and 10 devices using the Chrome and Firefox browsers. Method 1: Install ChatGPT as an App on Windows 11, 10 From Chrome To install ChatGPT as an app on Windows 11 and 10 from Chrome, follow these instructions. Open the Chrome browser. Visit the official ChatGPT website. (Optional) Sign in with your existing account or proceed as a guest user. Open the "menu" by clicking the three dots in the top right corner. Select “Save and share” from the menu, and then select the “Install page as app…” option. Open the Chrome browser. Visit the official ChatGPT website . official ChatGPT website (Optional) Sign in with your existing account or proceed as a guest user. Open the " menu " by clicking the three dots in the top right corner. menu Select “ Save and share ” from the menu, and then select the “ Install page as app… ” option. Save and share Install page as app… Click on the "Install" button when the "Install this page as an app" prompt appears. Click on the " Install " button when the " Install this page as an app " prompt appears. Install Install this page as an app The ChatGPT app will be launched as a Progressive Web App (PWA) with a shortcut icon on your desktop for easy access whenever you need it. The ChatGPT app will be launched as a Progressive Web App (PWA) with a shortcut icon on your desktop for easy access whenever you need it. Uninstall To uninstall the ChatGPT app from Chrome, follow these instructions. Open the Chrome browser. Open "chrome://apps" settings page: Click the ChatGPT app with the right mouse button, and choose "Uninstall" from the context menu. Open the Chrome browser. Open " chrome://apps " settings page: chrome://apps Click the ChatGPT app with the right mouse button, and choose " Uninstall " from the context menu. Uninstall Method 2: Install ChatGPT as an App on Windows 11, 10 From Firefox Firefox does not have a direct method for installing PWAs, so you'll need to use an additional extension like Progressive Web Apps for Firefox, which is completely free, open-source, and recommended by Mozilla. To install ChatGPT as an app on Windows 11 and 10 from Firefox, follow these instructions. Open the Firefox browser. Install the Progressive Web Apps for Firefox extension. Follow the extension configuration instructions, and set up a suitable connector. Visit the official ChatGPT website. (Optional) Sign in with your existing account or proceed as a guest user. Click the extension icon, and select "Install current site" from the dialog box. Open the Firefox browser. Install the Progressive Web Apps for Firefox extension. Progressive Web Apps for Firefox Follow the extension configuration instructions, and set up a suitable connector. Visit the official ChatGPT website . official ChatGPT website (Optional) Sign in with your existing account or proceed as a guest user. Click the extension icon, and select " Install current site " from the dialog box. Install current site It redirects to another page where you need to enter some necessary details. Since the extension is launched from the tab with ChatGPT open, it will automatically pick the necessary details, and you just have to click on the "Install web app" button. It redirects to another page where you need to enter some necessary details. Since the extension is launched from the tab with ChatGPT open, it will automatically pick the necessary details, and you just have to click on the " Install web app " button. Install web app That's it! You can now open the ChatGPT app from the extension dialog box. That's it! You can now open the ChatGPT app from the extension dialog box. Well, this method allows you to install ChatGPT as an app from Firefox on Windows 11 and 10. However, as of writing this article, there is no straightforward way to create a desktop shortcut for the PWA app created using this method. Uninstall To uninstall the ChatGPT app from Firefox, follow these instructions. Open the Firefox browser. Click the extension icon, and select the "trash" icon next to the ChatGPT app. Open the Firefox browser. Open the Firefox browser. Click the extension icon, and select the "trash" icon next to the ChatGPT app. Click the extension icon, and select the " trash " icon next to the ChatGPT app. trash Wrap Up Right now, the PWA is the only option to use ChatGPT as an almost-native app on Windows 11 and 10. However, OpenAI has claimed that a desktop app will be available soon, with macOS seemingly given higher priority despite Microsoft’s big chunk of investment.

How to Install ChatGPT as an App on Windows 11 and 10

Transforming Mobile Maps with Jetpack Compose: Insights from Google I/O for Developers

জেটপ্যাক কম্পোজের সাহায্যে মোবাইল মানচিত্র রূপান্তর: বিকাশকারীদের জন্য Google I/O থেকে অন্তর্দৃষ্টি

Mobile Karten mit Jetpack Compose transformieren: Erkenntnisse von Google I/O für Entwickler

Transformando mapas móviles con Jetpack Compose: información de Google I/O para desarrolladores

Transformer les cartes mobiles avec Jetpack Compose : informations de Google I/O pour les développeurs

जेटपैक कंपोज के साथ मोबाइल मैप्स को बदलना: डेवलपर्स के लिए Google I/O से जानकारी

Jetpack Compose でモバイル マップを変革: 開発者向け Google I/O からの洞察

Jetpack Compose로 모바일 지도 혁신: 개발자를 위한 Google I/O의 유용한 정보

Transformando mapas móveis com Jetpack Compose: insights do Google I/O para desenvolvedores

Преобразование мобильных карт с помощью Jetpack Compose: выводы Google I/O для разработчиков

Jetpack Compose ile Mobil Haritaları Dönüştürme: Geliştiriciler için Google I/O'dan Analizler

Chuyển đổi bản đồ di động bằng Jetpack Compose: Thông tin chi tiết từ Google I/O dành cho nhà phát triển

使用 Jetpack Compose 改造移动地图：Google I/O 开发者大会上的见解

Building Your AI Radiologist: A Fun Guide to Creating a Pneumonia Detector with VGG16

আপনার এআই রেডিওলজিস্ট তৈরি করা: VGG16 দিয়ে নিউমোনিয়া ডিটেক্টর তৈরির জন্য একটি মজার গাইড

Aufbau Ihres KI-Radiologen: Eine unterhaltsame Anleitung zum Erstellen eines Lungenentzündungsdetektors mit VGG16

Construyendo su radiólogo con IA: una guía divertida para crear un detector de neumonía con VGG16

Construire votre radiologue IA : un guide amusant pour créer un détecteur de pneumonie avec VGG16

अपना AI रेडियोलॉजिस्ट तैयार करें: VGG16 के साथ न्यूमोनिया डिटेक्टर बनाने के लिए एक मजेदार गाइड

AI 放射線科医の育成: VGG16 を使った肺炎検出器の作成ガイド

AI 방사선 전문의 구축: VGG16을 사용하여 폐렴 감지기 생성을 위한 재미있는 가이드

Construindo seu radiologista de IA: um guia divertido para criar um detector de pneumonia com VGG16

Создание вашего искусственного радиолога: забавное руководство по созданию детектора пневмонии с помощью VGG16

Yapay Zeka Radyoloğunuzu Oluşturma: VGG16 ile Pnömoni Dedektörü Oluşturmak İçin Eğlenceli Bir Kılavuz

Xây dựng bác sĩ X quang AI của bạn: Hướng dẫn thú vị để tạo máy phát hiện bệnh viêm phổi với VGG16

打造你的 AI 放射科医生：使用 VGG16 创建肺炎检测器的有趣指南

LM Studio is a popular GUI application that allows users with basic computer knowledge to easily download, install, and run large language models (LLMs) locally on their Linux machines. Popular LLM models such as Llama 3, Phi3, Falcon, Mistral, StarCoder, Gemma, and many more can be easily installed, set up, and accessed using the LM Studio chat interfaces. This way, you won't be stuck with proprietary cloud-based AI like OpenAI's ChatGPT and can easily run your own LLM privately offline without paying any extra money for the full features. In this article, I'll show you how to install LM Studio on Linux, set it up, and use the GPT-3 model. System Requirements Running LLM models locally on a PC requires meeting certain minimum requirements to ensure a decent experience. Make sure you have at least... An NVIDIA or AMD graphics card with at least 8 GB of VRAM.
20 GB of free storage (SSD would be a better option).
16 GB of DDR4 RAM. Installing LM Studio on Linux First, visit the official LM Studio website, and download the LM Studio AppImage by clicking "Download LM Studio for Linux." Once the download is complete, open your terminal, navigate to the downloads directory, and assign executable permissions to the LM Studio AppImage. $ cd ~/Downloads/
$ chmod u+x LM_Studio-*.AppImage Next, unpack the contents of the AppImage using the command below, which will create a new directory named "squashfs-root." $ ./LM_Studio-*.AppImage --appimage-extract Now, navigate to the extracted "squashfs-root" directory and assign appropriate permissions and ownership to the "chrome-sandbox" file. $ cd squashfs-root/
$ sudo chown root:root chrome-sandbox
$ sudo chmod 4755 chrome-sandbox Finally, run the LM Studio application within the same directory using this command: $ ./lm-studio That's it! You can now search, download, and access your favorite open-source LLMs with LM Studio. For instructions on setting up and accessing GPT-3, see the next section. Accessing the GPT-3 Model in LM Studio To access the GPT-3 model, you need to first download it. To achieve this, click on the search icon in the left panel, type "GPT-3" as the model name, and select the appropriate model size based on your system specifications. The download process will begin, and you can track the progress by clicking on the bottom panel. Once the download is complete, click the chat icon on the left panel, select the GPT-3 model from the top dropdown, and start chatting with the GPT-3 model by typing your message in the bottom input field. That's it! You can now ask any question locally on the GPT-3 model. The response time could vary depending on your system specifications. For example, I've got a decent GPU with 8 GB of VRAM and 16 GB of DDR4 RAM, for which it took around 45 seconds to generate 150–200 words. If the response is too poor in your case, you can try using a different LLM model. I would recommend using the Meta Llama 3 and making sure to choose the smallest size for the model to start with. Wrap Up In this article, you’ve learned how to use LM Studio to download and access open-source LLM models like GPT-3 and Llama 3 on your local PC. Now, before you transition from cloud services to using your PC for LLMs, keep in mind that it uses a GPU, which consumes electricity and affects GPU lifespan. So, if you're an AI enthusiast and privacy advocate, it won't bother you, but if you're concerned about electricity bills or have a less powerful PC, unfortunately, cloud-based AI may be your only option. LM Studio is a popular GUI application that allows users with basic computer knowledge to easily download, install, and run large language models (LLMs) locally on their Linux machines. large language models Popular LLM models such as Llama 3, Phi3, Falcon, Mistral, StarCoder, Gemma, and many more can be easily installed, set up, and accessed using the LM Studio chat interfaces. This way, you won't be stuck with proprietary cloud-based AI like OpenAI's ChatGPT and can easily run your own LLM privately offline without paying any extra money for the full features. OpenAI's ChatGPT In this article, I'll show you how to install LM Studio on Linux, set it up, and use the GPT-3 model. System Requirements Running LLM models locally on a PC requires meeting certain minimum requirements to ensure a decent experience. Make sure you have at least... An NVIDIA or AMD graphics card with at least 8 GB of VRAM. 20 GB of free storage (SSD would be a better option). 16 GB of DDR4 RAM. An NVIDIA or AMD graphics card with at least 8 GB of VRAM. 20 GB of free storage (SSD would be a better option). 16 GB of DDR4 RAM. Installing LM Studio on Linux First, visit the official LM Studio website , and download the LM Studio AppImage by clicking " Download LM Studio for Linux. " official LM Studio website Download LM Studio for Linux. Once the download is complete, open your terminal, navigate to the downloads directory, and assign executable permissions to the LM Studio AppImage. $ cd ~/Downloads/
$ chmod u+x LM_Studio-*.AppImage $ cd ~/Downloads/
$ chmod u+x LM_Studio-*.AppImage Next, unpack the contents of the AppImage using the command below, which will create a new directory named " squashfs-root. " squashfs-root. $ ./LM_Studio-*.AppImage --appimage-extract $ ./LM_Studio-*.AppImage --appimage-extract Now, navigate to the extracted " squashfs-root " directory and assign appropriate permissions and ownership to the " chrome-sandbox " file. squashfs-root chrome-sandbox $ cd squashfs-root/
$ sudo chown root:root chrome-sandbox
$ sudo chmod 4755 chrome-sandbox $ cd squashfs-root/
$ sudo chown root:root chrome-sandbox
$ sudo chmod 4755 chrome-sandbox Finally, run the LM Studio application within the same directory using this command: $ ./lm-studio $ ./lm-studio That's it! You can now search, download, and access your favorite open-source LLMs with LM Studio. For instructions on setting up and accessing GPT-3, see the next section. open-source LLMs Accessing the GPT-3 Model in LM Studio To access the GPT-3 model, you need to first download it. To achieve this, click on the search icon in the left panel, type " GPT-3 " as the model name, and select the appropriate model size based on your system specifications. GPT-3 The download process will begin, and you can track the progress by clicking on the bottom panel. Once the download is complete, click the chat icon on the left panel, select the GPT-3 model from the top dropdown, and start chatting with the GPT-3 model by typing your message in the bottom input field. That's it! You can now ask any question locally on the GPT-3 model. The response time could vary depending on your system specifications. For example, I've got a decent GPU with 8 GB of VRAM and 16 GB of DDR4 RAM, for which it took around 45 seconds to generate 150–200 words. If the response is too poor in your case, you can try using a different LLM model. I would recommend using the Meta Llama 3 and making sure to choose the smallest size for the model to start with. Wrap Up In this article, you’ve learned how to use LM Studio to download and access open-source LLM models like GPT-3 and Llama 3 on your local PC. Now, before you transition from cloud services to using your PC for LLMs, keep in mind that it uses a GPU, which consumes electricity and affects GPU lifespan. So, if you're an AI enthusiast and privacy advocate, it won't bother you, but if you're concerned about electricity bills or have a less powerful PC, unfortunately, cloud-based AI may be your only option.

How to Run LLMs Using LM Studio in Linux (for Beginners)

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