CureVac and GSK have been racing behind Moderna to try to get the first mRNA flu vaccine to market. But, now, the European partners have come up against the exact same problem as their U.S. | CureVac and GSK have been racing behind Moderna to try and get the first mRNA flu vaccine to market.

CureVac, chasing Moderna's mRNA flu vaccine, runs into the same B strain problems

WARMINSTER, Pa., April 04, 2024 (GLOBE NEWSWIRE) -- Arbutus Biopharma Corporation (Nasdaq: ABUS), a clinical-stage biopharmaceutical company leveraging its extensive virology expertise to develop a functional cure for people with chronic hepatitis B virus (cHBV) infection, today issued the ...

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MarketWatch provides the latest stock market, financial and business news. Get stock market quotes, personal finance advice, company news and more.

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Moderan

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How To Scrape Modern SPAs, PWAs, and AI-Driven Dynamic Sites

আধুনিক এসপিএ, পিডব্লিউএ এবং এআই-চালিত ডায়নামিক সাইটগুলি কীভাবে স্ক্র্যাপ করবেন

So scrapen Sie moderne SPAs, PWAs und KI-gesteuerte dynamische Sites

Cómo extraer datos de SPA modernas, PWA y sitios dinámicos impulsados por IA

Comment récupérer les SPA, PWA et sites dynamiques pilotés par l'IA modernes

आधुनिक एसपीए, पीडब्ल्यूए और एआई-संचालित गतिशील साइटों को कैसे स्क्रैप करें

Como raspar SPAs modernos, PWAs e sites dinâmicos baseados em IA

Как парсить современные SPA, PWA и динамические сайты на базе искусственного интеллекта

Modern SPA'lar, PWA'lar ve AI Destekli Dinamik Siteler Nasıl Kazınır

Cách thu thập SPA hiện đại, PWA và các trang web động do AI điều khiển

如何抓取现代 SPA、PWA 和 AI 驱动的动态网站

Why AI-Powered Image Hosting APIs Are Essential for Modern Businesses

Waarom AI-aangedrewe beeldgasheer-API's noodsaaklik is vir moderne besighede

Proč jsou rozhraní API pro hostování obrázků s umělou inteligencí nezbytná pro moderní podniky

Warum KI-gestützte Bildhosting-APIs für moderne Unternehmen unverzichtbar sind

Por qué las API de alojamiento de imágenes basadas en IA son esenciales para las empresas modernas

Miért nélkülözhetetlenek az AI-alapú képtárhely API-k a modern vállalkozások számára?

AI を活用した画像ホスティング API が現代のビジネスに不可欠な理由

Неліктен AI-мен жұмыс істейтін кескін хостинг API интерфейстері қазіргі заманғы бизнес үшін өте маңызды?

Kāpēc ar AI darbināmas attēlu mitināšanas API ir būtiskas mūsdienu uzņēmumiem

Ke ka baka la’ng di-API tša go Amogela Diswantšho tšeo di Matlafatšwago ke AI di le Bohlokwa bakeng sa Dikgwebo tša Sebjalebjale

Почему API-интерфейсы хостинга изображений на базе искусственного интеллекта необходимы современному бизнесу

නවීන ව්‍යාපාර සඳහා AI-බලවත් රූප සත්කාරක API අත්‍යවශ්‍ය වන්නේ ඇයි?

Tại sao API lưu trữ hình ảnh hỗ trợ AI lại cần thiết cho các doanh nghiệp hiện đại

For developers and those who frequently use command-line interfaces, navigating the terminal can sometimes feel like a repetitive task. Even though terminal commands are straightforward, they can become tedious, especially if you're not fully comfortable with every command’s syntax. In recent years, several tools have emerged to enhance the command-line experience, and Warp is one of the latest options aiming to streamline these processes with a more user-friendly interface. Warp positions itself as a reimagined terminal, aiming to simplify command entry and improve user feedback. Built with AI-driven features and designed to be visually informative, it offers an experience that differs from standard terminals. While there are plenty of add-ons and plugins that can enhance the terminal, Warp's approach is more comprehensive, focusing on making the terminal environment itself more intuitive. A key feature that Warp brings to the table is the real-time contextual information it provides. For example, if you’re working with Git, a common task is to check the branch you're currently on. Traditionally, this requires you to enter git branch to display the branch name, adding a small but constant task for users who work with multiple branches. In a typical terminal, this branch check requires extra input, as the terminal does not automatically display branch information. Warp, however, includes this information in its UI, showing the branch directly within the main display without needing an additional command. This feature could be useful for developers who need quick context and want to minimize interruptions to their workflow. Warp’s interface includes several other features that might appeal to developers looking for a more modern terminal experience. For instance, Warp’s UI is designed to provide a clearer visual structure, potentially making command outputs easier to read compared to traditional terminal outputs. The interface highlights certain types of information, making it easier to parse logs or debug issues at a glance. This kind of layout can make it easier to identify errors or warnings without scanning through an extensive list of command outputs manually. Additionally, Warp has an AI-driven autocomplete feature, which may help users who occasionally forget command syntax or aren’t fully familiar with all command-line options. This feature aims to provide relevant suggestions as you type, potentially reducing the need to consult external documentation or search online for command references. For developers or users who frequently run into syntax uncertainties, Warp’s autocomplete might prove convenient. That said, Warp may not be a one-size-fits-all solution, and some users might find that they prefer traditional terminal environments or are already satisfied with the plugins and customization available in tools like iTerm2 or Hyper. Warp’s emphasis on visual feedback and autocomplete can be helpful for those who prefer a guided experience, but some seasoned command-line users may feel they don’t benefit as much from these features. Another factor to consider is that Warp’s approach could be more resource-intensive than minimalistic terminals. For users on systems where performance is a priority, or for those working in low-resource environments, this could be a trade-off. While Warp’s features provide a different experience, the system resources required may not suit everyone’s setup. In the end, whether Warp is the right fit depends largely on the individual’s workflow and terminal usage patterns. Those who find traditional terminals to be sufficient may not see a need for Warp’s added interface elements or AI-driven assistance. On the other hand, developers who are interested in a more visually supportive environment and would appreciate having contextual information readily available might find Warp to be a worthwhile addition. Overall, Warp represents a shift towards a more modern, user-friendly terminal experience that could help simplify command-line workflows. For users interested in testing out an alternative to the traditional terminal experience, Warp may be worth exploring to see if it complements their development habits and needs. Below is Warp’s interface, showing the current directory and the current branch I’m on, which is the main branch. I did not need to type git branch  to check the current branch, however, Warp showed me this already. In the image below, I have asked a question on how to make a directory. Look closely and see the response it gave. It all boils down to preference at the end of the day. Some may like the traditional look of terminal while others may like a more intuitive interface. For developers and those who frequently use command-line interfaces, navigating the terminal can sometimes feel like a repetitive task. Even though terminal commands are straightforward, they can become tedious, especially if you're not fully comfortable with every command’s syntax. In recent years, several tools have emerged to enhance the command-line experience, and Warp is one of the latest options aiming to streamline these processes with a more user-friendly interface. Warp positions itself as a reimagined terminal, aiming to simplify command entry and improve user feedback. Built with AI-driven features and designed to be visually informative, it offers an experience that differs from standard terminals. While there are plenty of add-ons and plugins that can enhance the terminal, Warp's approach is more comprehensive, focusing on making the terminal environment itself more intuitive. A key feature that Warp brings to the table is the real-time contextual information it provides. For example, if you’re working with Git, a common task is to check the branch you're currently on. Traditionally, this requires you to enter git branch to display the branch name, adding a small but constant task for users who work with multiple branches. In a typical terminal, this branch check requires extra input, as the terminal does not automatically display branch information. Warp, however, includes this information in its UI, showing the branch directly within the main display without needing an additional command. This feature could be useful for developers who need quick context and want to minimize interruptions to their workflow. git branch Warp’s interface includes several other features that might appeal to developers looking for a more modern terminal experience. For instance, Warp’s UI is designed to provide a clearer visual structure, potentially making command outputs easier to read compared to traditional terminal outputs. The interface highlights certain types of information, making it easier to parse logs or debug issues at a glance. This kind of layout can make it easier to identify errors or warnings without scanning through an extensive list of command outputs manually. Additionally, Warp has an AI-driven autocomplete feature, which may help users who occasionally forget command syntax or aren’t fully familiar with all command-line options. This feature aims to provide relevant suggestions as you type, potentially reducing the need to consult external documentation or search online for command references. For developers or users who frequently run into syntax uncertainties, Warp’s autocomplete might prove convenient. That said, Warp may not be a one-size-fits-all solution, and some users might find that they prefer traditional terminal environments or are already satisfied with the plugins and customization available in tools like iTerm2 or Hyper. Warp’s emphasis on visual feedback and autocomplete can be helpful for those who prefer a guided experience, but some seasoned command-line users may feel they don’t benefit as much from these features. Another factor to consider is that Warp’s approach could be more resource-intensive than minimalistic terminals. For users on systems where performance is a priority, or for those working in low-resource environments, this could be a trade-off. While Warp’s features provide a different experience, the system resources required may not suit everyone’s setup. In the end, whether Warp is the right fit depends largely on the individual’s workflow and terminal usage patterns. Those who find traditional terminals to be sufficient may not see a need for Warp’s added interface elements or AI-driven assistance. On the other hand, developers who are interested in a more visually supportive environment and would appreciate having contextual information readily available might find Warp to be a worthwhile addition. Overall, Warp represents a shift towards a more modern, user-friendly terminal experience that could help simplify command-line workflows. For users interested in testing out an alternative to the traditional terminal experience, Warp may be worth exploring to see if it complements their development habits and needs. Below is Warp’s interface, showing the current directory and the current branch I’m on, which is the main branch. I did not need to type git branch to check the current branch, however, Warp showed me this already. git branch In the image below, I have asked a question on how to make a directory. Look closely and see the response it gave. It all boils down to preference at the end of the day. Some may like the traditional look of terminal while others may like a more intuitive interface.

A Modern Take on the Terminal Experience

As a Senior BI Architect at Safeguard Products International LLC, Sreenivasarao Amirineni has made a name for himself in the insurance and data analytics industries. His path from earning a master's degree in computer science from the University of Madras in 2001 to spearheading essential advancements in the insurance sector is evidence of his commitment and competence. Amirineni's career journey began with overseeing the family business and exploring Asian financial markets, a period that provided him with invaluable insights into the global financial and technical landscape. His return to software programming in 2005 as a middleware integration developer at NTT Data Services (previously Keane, Inc.) laid the foundation for his subsequent achievements. His pivotal role in the AUD 1.9 billion project for the Australian state government of Victoria, which transitioned the state's ticketing system to a smart card-based platform, showcased his early commitment and competence. Amirineni relocated to Australia in 2008, quickly establishing himself as an essential member of the Transport Domain Center of Excellence (COE). Here, he managed the deployment of SQL Lite and BizTalk to create a centralized master data platform. This platform demonstrated his capacity to manage intricate, large-scale projects, which is essential in changing the fare processing rules for 20,000 machines. Numerous honors and certificates also adorn Amirineni's career path. He is certified as a Microsoft Data Analyst and Snowflake Cloud user and is a member of IEEE and BCS. Safeguard Products LLC and NTT Data Services have recognized his exceptional work as a star performer and best motivator. At Safeguard Products International, one of Amirineni's most notable efforts was creating a strong data platform for analytics and fraud detection. He oversaw the development of proprietary algorithms and a mobile app for submitting claims as part of his quest to decrease the reliance on humans in the claims process. This invention improved the company's loss ratio for its tire and wheel product from 100% to 95% while streamlining processes and drastically cutting expenses, saving $1 million a year. Amirineni's contributions to the insurance industry have been significant. His work on the development of modules for fraud detection and claim filing and their integration into a master platform, has notably improved the overall efficiency and accuracy of claims handling. This has streamlined procedures for dealer locations and direct clients, demonstrating his deep understanding of the industry and its needs. Addressing the elevated loss rates in the tire and wheel warranty market was pivotal in Amirineni's professional journey. He carried out several strategic initiatives with the Risk and CAS teams, including creating a mobile app for submitting claims, implementing auto-approval procedures, and integrating extensive data for claims analysis. The significant savings and stable loss ratios that followed his initiatives demonstrated his technical prowess and strategic vision. Amirineni's leadership style is marked by his ability to inspire teams to embrace innovation and strive for excellence. His role as a mentor and leader has improved prediction skills by creating machine learning algorithms and including external datasets. He has also fostered a culture of ongoing learning and development within the organization, which is a testament to his strategic vision and technical prowess. As a Senior BI Architect at Safeguard Products International LLC, Sreenivasarao Amirineni has made a name for himself in the insurance and data analytics industries. His path from earning a master's degree in computer science from the University of Madras in 2001 to spearheading essential advancements in the insurance sector is evidence of his commitment and competence. Amirineni's career journey began with overseeing the family business and exploring Asian financial markets, a period that provided him with invaluable insights into the global financial and technical landscape. His return to software programming in 2005 as a middleware integration developer at NTT Data Services (previously Keane, Inc.) laid the foundation for his subsequent achievements. His pivotal role in the AUD 1.9 billion project for the Australian state government of Victoria, which transitioned the state's ticketing system to a smart card-based platform, showcased his early commitment and competence. Amirineni relocated to Australia in 2008, quickly establishing himself as an essential member of the Transport Domain Center of Excellence (COE). Here, he managed the deployment of SQL Lite and BizTalk to create a centralized master data platform. This platform demonstrated his capacity to manage intricate, large-scale projects, which is essential in changing the fare processing rules for 20,000 machines. Numerous honors and certificates also adorn Amirineni's career path. He is certified as a Microsoft Data Analyst and Snowflake Cloud user and is a member of IEEE and BCS. Safeguard Products LLC and NTT Data Services have recognized his exceptional work as a star performer and best motivator. At Safeguard Products International, one of Amirineni's most notable efforts was creating a strong data platform for analytics and fraud detection. He oversaw the development of proprietary algorithms and a mobile app for submitting claims as part of his quest to decrease the reliance on humans in the claims process. This invention improved the company's loss ratio for its tire and wheel product from 100% to 95% while streamlining processes and drastically cutting expenses, saving $1 million a year. Amirineni's contributions to the insurance industry have been significant. His work on the development of modules for fraud detection and claim filing and their integration into a master platform, has notably improved the overall efficiency and accuracy of claims handling. This has streamlined procedures for dealer locations and direct clients, demonstrating his deep understanding of the industry and its needs. Addressing the elevated loss rates in the tire and wheel warranty market was pivotal in Amirineni's professional journey. He carried out several strategic initiatives with the Risk and CAS teams, including creating a mobile app for submitting claims, implementing auto-approval procedures, and integrating extensive data for claims analysis. The significant savings and stable loss ratios that followed his initiatives demonstrated his technical prowess and strategic vision. Amirineni's leadership style is marked by his ability to inspire teams to embrace innovation and strive for excellence. His role as a mentor and leader has improved prediction skills by creating machine learning algorithms and including external datasets. He has also fostered a culture of ongoing learning and development within the organization, which is a testament to his strategic vision and technical prowess.

Sreenivasarao Amirineni: How Machine Learning Contributes to Modern Business Efficiency

Sreenivasarao Amirineni: Hvordan maskinlæring bidrager til moderne forretningseffektivitet

Sreenivasarao Amirineni: Cómo el aprendizaje automático contribuye a la eficiencia empresarial moderna

Sreenivasarao Amirineni: چگونه یادگیری ماشین به کارایی کسب و کار مدرن کمک می کند

Sreenivasarao Amirineni : Comment l'apprentissage automatique contribue à l'efficacité des entreprises modernes

श्रीनिवासराव अमीरिनेनी: मशीन लर्निंग आधुनिक व्यावसायिक दक्षता में कैसे योगदान देता है

Sreenivasarao Amirineni: Ki jan aprantisaj machin kontribye nan efikasite biznis modèn

Sreenivasarao Amirineni: 機械学習が現代のビジネス効率にどのように貢献するか

Sreenivasarao Amirineni: Kamoo Thuto ya Motšhene e Kgathago Seabe go Bokgoni bja Kgwebo ya Sebjalebjale

سرینیواساراو امیرینیني: د ماشین زده کړه څنګه د عصري سوداګرۍ موثریت کې مرسته کوي

Sreenivasarao Amirineni: Ako strojové učenie prispieva k efektívnosti moderného podnikania

Срінівасарао Амірінені: Як машинне навчання сприяє ефективності сучасного бізнесу

Sreenivasarao Amirineni: Học máy đóng góp như thế nào vào hiệu quả kinh doanh hiện đại

Traditionally speaking, the banking system works with the help of a vast network of reliable intermediaries. Despite its challenges and shortcomings, we continue to rely on it to protect our funds and valuables – primarily in the virtual safe deposit box. This trust has been built over the centuries by the traditional banking system. Meanwhile, in the non-traditional landscape of cryptocurrency, the idea of a self-custody wallet has continued to gain traction even though bad actors are constantly in the news for hacking exchanges. While the crypto industry has undergone significant development, it is still very much plagued by scams and hacks that undermine efforts to build trust among millions of potential users. Crypto has an image problem, despite the promises of a self-custody revolution, and this is only aggravated by the instances of “overnight millionaires”. As a technological innovation, self-custody, which moves the management of assets into the hands of customers, represents a paradigm shift. It eliminates third-party involvement—a feature that can be a lifesaver as many platforms such as Terra, Celsius, and FTX, to mention a few, have crumbled causing significant losses to the tune of $40 billion as per CoinDesk. Building Trust Over Time It has taken several years of legal framing and enhancing the security measures of the conventional banking systems for people to develop trust in those systems. For instance when Silicon Valley Bank went bust, requisite measures to deal with customer losses were instituted without any delay. Crypto business, conversely, is a rather ill-defined and continuously developing market that still has no set rules to follow. Trust in this space has often been lost due to several failures as well as fraud-related cases. Consequently, self-custody appears to be the most viable innovation in such an environment. We can own assets outright and decrease the risk associated with third parties, which makes the process free from their intervention. The Role of Technology in Enhancing Security In the future, as this industry develops, we should also see these self-custody technologies reach the same high levels of trust and reliability as the present-day banking sector. Currently, CCData reveals that over one hundred providers can be identified all over the world to provide custodial solutions to retail and institutional investors looking to invest in crypto assets. The consolidation of the industry is foreseeable, as it is borne out by the experiences of sectors such as banking and the internet when transitions are initiated to tighten up security and instill greater trust in the industry. Distrust of centralized infrastructure is another problem that might appear unfathomable for retail users, but self-custody is imperative. The self-custody market remains to be developing, providing better and more consumer-friendly solutions that handle assets on the user‘s behalf. Additionally, self-custody is not only about transitioning between one technological paradigm and another – but a paradigm shift in thought. That is an indication of a shift towards self-organization and one’s faith in the financial systems. Unfortunately, self-custody will become one of the standards as crypto develops further for those who want their funds to be secure. Challenges Facing Web3 Wallet Management Currently, managing a Web3 wallet comes with the following challenges: Seed Phrases A Web3 wallet most importantly comprises the seed phrase recognized as a recovery phrase. It serves the purpose of becoming a unique identifier, allowing users to restore their wallets on various gadgets. It is a 12-24 random word phrase, and losing such a phrase will result in permanent loss of wallet and any of the funds stored in it. Unfortunately, there is no organized service to recover the phrase, and the total burden lies on the user. The problem lies in the question of how to safely store this seed phrase securely at the same time. It is too long and random that users cannot memorize it easily, and when they write it down or store it in an informatics device, there are some dangers involved. If the physical copy is lost, damaged, or stolen — or if a digital copy of the information is cracked — the user’s wallet could leak or could be locked away forever. Generating and Remembering Strong Passwords The majority of Web3 wallets also force users to set essential passwords to enhance the application’s protection. Such passwords must be used so that one is long and different from those used in the other accounts and contains symbols that cannot be subjected to hacking or brute force. However, this creates a significant challenge: how to achieve the best password creation to meet the standard of secularity while, at the same time be okay with the user to remember it. The reality is that there is no one server that a person can turn to get help, and as such, if the password is gone, so is the wallet. Worse still, fundamental password reset strategies such as receiving password reset links via email are not feasible in Web 3. As a result, the wallet remains closed for all eternity if the user forgets or loses the password to the wallet. This password is only with the user, so password insecurity is still an issue when managing Web3 wallets. Protecting Against Phishing Scams and Malware Crypto phishing scams are one of the most common types of scams actively used in the Web3 ecosystem. The attackers continue hiding behind the replica of any type of service or person, using techniques ranging from private keys to passwords from the user. As pointed out it has been noted that this kind of scam has evolved in a way that when the individual clicks on the links to the sites involved, these look almost like the real site, putting even the intelligent users at the mercy of the con-men. Malware is another huge problem because it is easy to spread an infected file or program into an organization's network. This can be acquired through downloads or by clicking on links in ads and will surreptitiously steal wallet details. For example, some malware may keep track of the clipboard of the user to replace the copied wallet address with a fake one, so as to guarantee that users deposit their cash into the wrong wallet. That is why pointing interest from the user and awareness of threats in the information space is needed to prevent these forms of attacks. Remaining Cautious of Unknown Links and Downloads Among the most used attack methods in Web3 is using links or downloads, which sound familiar or unknown to the user. If the user clicks on a fraudulent link, then the wallet becomes vulnerable to phishing sites, or the user's device is infected with malware. These are attacks with the intent of capturing the private key or otherwise phishing users into signing up for fraudulent transactions. Given the fact that Web3 is a decentralized network system, there is effectively no protection, and users are their self-defense line. This challenge is especially challenging because links can be disguised in several different ways, shapes, and forms. It comes from emails pretending to be from customer support or alert services on social media sites. One can compromise their account easily simply by downloading a well-known wallet plugin from untrusted sources. It makes every exchange that occurs through the platforms a potential risk that needs to be avoided. How GRVT Is Challenging The Notion of Private Key The GRVT Wallet simplifies the user experience through Web Authentication (WebAuthn), which allows users to create and access their wallet using a password and passkeys, avoiding the complexities associated with traditional crypto wallets. The integration of Dfns technology allows users to access their wallets via fingerprint or facial recognition, offering quick and secure authentication similar to traditional online banking. And it blends the user-friendliness of Web2 with the security of self-custody, protecting assets without the technical burdens. By leveraging off-chain, peer-to-peer networks with multi-party computation (MPC) and public key infrastructure, it is able to guarantee: No Single Point of Failure: GRVT Wallet supports multiple devices, creating multiple security layers to prevent breaches. Responsive Recovery: Recovery wallets and backup codes provide fail-safes if credentials are lost. Uninterrupted Transactions: Linking new devices doesn’t affect public key, allowing continuous transfers. Conclusion The question of why the conventional banking system continues to thrive despite its shortcomings and the revolutionary advantage of the self-custody system boils down to trust. Millions around the world still feel safe to keep their money and other valuables in the banks and the incidence of crypto scams and losses has increasingly overshadowed the prospects of a generational transition from modern banking to cryptocurrency and self-custody wallet. This problem is further aggravated by the technical complexities surrounding the use of a smart contract wallet, which requires a level of skill to operate. Nonetheless, the possibility for both systems to exist side-by-side in the future is worth considering. Traditionally speaking, the banking system works with the help of a vast network of reliable intermediaries. Despite its challenges and shortcomings, we continue to rely on it to protect our funds and valuables – primarily in the virtual safe deposit box. This trust has been built over the centuries by the traditional banking system. Meanwhile, in the non-traditional landscape of cryptocurrency, the idea of a self-custody wallet has continued to gain traction even though bad actors are constantly in the news for hacking exchanges. While the crypto industry has undergone significant development, it is still very much plagued by scams and hacks that undermine efforts to build trust among millions of potential users. Crypto has an image problem, despite the promises of a self-custody revolution, and this is only aggravated by the instances of “overnight millionaires”. As a technological innovation, self-custody, which moves the management of assets into the hands of customers, represents a paradigm shift. It eliminates third-party involvement—a feature that can be a lifesaver as many platforms such as Terra, Celsius, and FTX, to mention a few, have crumbled causing significant losses to the tune of $40 billion as per CoinDesk . Crypto CoinDesk Building Trust Over Time It has taken several years of legal framing and enhancing the security measures of the conventional banking systems for people to develop trust in those systems. For instance when Silicon Valley Bank went bust, requisite measures to deal with customer losses were instituted without any delay. Silicon Valley Bank Crypto business, conversely, is a rather ill-defined and continuously developing market that still has no set rules to follow. Trust in this space has often been lost due to several failures as well as fraud-related cases. Consequently, self-custody appears to be the most viable innovation in such an environment. We can own assets outright and decrease the risk associated with third parties, which makes the process free from their intervention. The Role of Technology in Enhancing Security In the future, as this industry develops, we should also see these self-custody technologies reach the same high levels of trust and reliability as the present-day banking sector. Currently, CCData reveals that over one hundred providers can be identified all over the world to provide custodial solutions to retail and institutional investors looking to invest in crypto assets. The consolidation of the industry is foreseeable, as it is borne out by the experiences of sectors such as banking and the internet when transitions are initiated to tighten up security and instill greater trust in the industry. Distrust of centralized infrastructure is another problem that might appear unfathomable for retail users, but self-custody is imperative. The self-custody market remains to be developing, providing better and more consumer-friendly solutions that handle assets on the user‘s behalf. Additionally, self-custody is not only about transitioning between one technological paradigm and another – but a paradigm shift in thought. That is an indication of a shift towards self-organization and one’s faith in the financial systems. Unfortunately, self-custody will become one of the standards as crypto develops further for those who want their funds to be secure. Challenges Facing Web3 Wallet Management Currently, managing a Web3 wallet comes with the following challenges: Seed Phrases A Web3 wallet most importantly comprises the seed phrase recognized as a recovery phrase. It serves the purpose of becoming a unique identifier, allowing users to restore their wallets on various gadgets. It is a 12-24 random word phrase, and losing such a phrase will result in permanent loss of wallet and any of the funds stored in it. Unfortunately, there is no organized service to recover the phrase, and the total burden lies on the user. The problem lies in the question of how to safely store this seed phrase securely at the same time. It is too long and random that users cannot memorize it easily, and when they write it down or store it in an informatics device, there are some dangers involved. If the physical copy is lost, damaged, or stolen — or if a digital copy of the information is cracked — the user’s wallet could leak or could be locked away forever. Generating and Remembering Strong Passwords The majority of Web3 wallets also force users to set essential passwords to enhance the application’s protection. Such passwords must be used so that one is long and different from those used in the other accounts and contains symbols that cannot be subjected to hacking or brute force. However, this creates a significant challenge: how to achieve the best password creation to meet the standard of secularity while, at the same time be okay with the user to remember it. The reality is that there is no one server that a person can turn to get help, and as such, if the password is gone, so is the wallet. Worse still, fundamental password reset strategies such as receiving password reset links via email are not feasible in Web 3. As a result, the wallet remains closed for all eternity if the user forgets or loses the password to the wallet. This password is only with the user, so password insecurity is still an issue when managing Web3 wallets. Protecting Against Phishing Scams and Malware Crypto phishing scams are one of the most common types of scams actively used in the Web3 ecosystem. The attackers continue hiding behind the replica of any type of service or person, using techniques ranging from private keys to passwords from the user. As pointed out it has been noted that this kind of scam has evolved in a way that when the individual clicks on the links to the sites involved, these look almost like the real site, putting even the intelligent users at the mercy of the con-men. Malware is another huge problem because it is easy to spread an infected file or program into an organization's network. This can be acquired through downloads or by clicking on links in ads and will surreptitiously steal wallet details. For example, some malware may keep track of the clipboard of the user to replace the copied wallet address with a fake one, so as to guarantee that users deposit their cash into the wrong wallet. That is why pointing interest from the user and awareness of threats in the information space is needed to prevent these forms of attacks. Remaining Cautious of Unknown Links and Downloads Among the most used attack methods in Web3 is using links or downloads, which sound familiar or unknown to the user. If the user clicks on a fraudulent link, then the wallet becomes vulnerable to phishing sites, or the user's device is infected with malware. These are attacks with the intent of capturing the private key or otherwise phishing users into signing up for fraudulent transactions. Given the fact that Web3 is a decentralized network system, there is effectively no protection, and users are their self-defense line. This challenge is especially challenging because links can be disguised in several different ways, shapes, and forms. It comes from emails pretending to be from customer support or alert services on social media sites. One can compromise their account easily simply by downloading a well-known wallet plugin from untrusted sources. It makes every exchange that occurs through the platforms a potential risk that needs to be avoided. How GRVT Is Challenging The Notion of Private Key How GRVT Is Challenging The Notion of Private Key The GRVT Wallet simplifies the user experience through Web Authentication (WebAuthn), which allows users to create and access their wallet using a password and passkeys, avoiding the complexities associated with traditional crypto wallets. The integration of Dfns technology allows users to access their wallets via fingerprint or facial recognition, offering quick and secure authentication similar to traditional online banking. And it blends the user-friendliness of Web2 with the security of self-custody, protecting assets without the technical burdens. By leveraging off-chain, peer-to-peer networks with multi-party computation (MPC) and public key infrastructure, it is able to guarantee: No Single Point of Failure: GRVT Wallet supports multiple devices, creating multiple security layers to prevent breaches. Responsive Recovery: Recovery wallets and backup codes provide fail-safes if credentials are lost. Uninterrupted Transactions: Linking new devices doesn’t affect public key, allowing continuous transfers. Conclusion The question of why the conventional banking system continues to thrive despite its shortcomings and the revolutionary advantage of the self-custody system boils down to trust. Millions around the world still feel safe to keep their money and other valuables in the banks and the incidence of crypto scams and losses has increasingly overshadowed the prospects of a generational transition from modern banking to cryptocurrency and self-custody wallet. This problem is further aggravated by the technical complexities surrounding the use of a smart contract wallet, which requires a level of skill to operate. Nonetheless, the possibility for both systems to exist side-by-side in the future is worth considering.

The Vaults vs. Self-Custody: A Trust Revolution in Modern Finance

The Vaults vs Self-Custody: A Trust Revolution in Modern Finance

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Hey Hackers! Cropler has been nominated in HackerNoon's Startups of The Year 2024  awards in Warsaw, Poland under the Emerging Tech category and others. Please vote for us here: 1️⃣ https://hackernoon.com/startups/europe/europe-warsaw-poland 2️⃣ https://hackernoon.com/startups/industry/iot 3️⃣ https://hackernoon.com/startups/industry/hardware 4️⃣ https://hackernoon.com/startups/industry/climatetech Meet Cropler Cropler is the world’s first real-time remote photo plant monitoring technology that is about to become an AI-powered digital agronomical assistant. Cropler uses smart AI-powered mobile agricameras to help farmers and agribusinesses identify the key phenophases, diseases, and inputs efficiently to perform necessary agricultural operations in a timely manner. The Winning Team 1️⃣ Nik Bedunkevich
LinkedIn
Founder & CEO
With over 10 years in software and 7+ years in hardware development, Nik's leadership in precision agriculture, backed by his experience at OneSoil, where he co-founded and led hardware development, has been instrumental. His background in Radio Engineering and his ability to integrate data exchange and soil analysis sensors have enabled Cropler to push the boundaries of AI-driven agricultural solutions.2️⃣ Marie SinkovaLinkedIn
CMO
Marie’s 6+ years in marketing, including her impactful work at MEDvidi and EduDo, have significantly boosted our brand’s visibility. Her ability to develop engaging content and manage successful teams has increased revenue and brand recognition while minimizing negative reviews. Her strategic approach in various marketing areas has laid a solid foundation for Cropler development.3️⃣ Andrii ZbrytskyiLinkedIn
BDM
With over 17 years in the agritech area, Andri Zbrytskyi has witnessed firsthand the ins and outs of clients resulting in better client/corporate relations, sales and even more business development for the company. AI agriculture solutions have found strategic partnerships thanks to his efforts and these have increased expanding the market base.4️⃣ Xenia NiaborskayaLinkedIn
Head of Design
Xenia’s experience of more than 4 years in UX/UI design has played a key role in ensuring that our user interfaces work as expected and look good as well. Her capability in business-centered design and the process of user-centered design has improved the usability of our platform tremendously.5️⃣ Eugene VoronetsLinkedIn
Tech Adviser
Eugene’s 10+ years in backend development, particularly his expertise in high-load systems, ensures the robustness and scalability of our technology. His work at OneSoil, building APIs and fostering collaborations with industry leaders like John Deere and AWS, has played a critical role in shaping Cropler’s technical infrastructure. What Cropler does differently We aim to revolutionize agriculture with Cropler's global plant monitoring technology, which uses AI-powered agricameras and remote sensing data to provide farmers, agronomists, and agribusinesses with predictive field insights and global yield analytics for optimized crop production. Cropler’s unique, AI-powered plant health data allows farmers and agribusinesses to address issues before they escalate, unlike drones or weather stations, which often provide information only after problems have already progressed and plants experience severe damage. Early disease and crop stress detection ensures that farmers can act timely to maximize yields and optimize fertilizers and pesticides application. Cropler isn’t just about monitoring—it’s about driving actionable insights that make farming more efficient, sustainable, and profitable. Milestones and achievements 🏆 357 devices deployed
🏆 Revenue of $53k in 2024
🏆 AI disease & leaf damages integration
🏆 iOS & Android app release
🏆 10 dealer centers in multiple countries
🏆 16 countries (EU + USA) have chosen our devices
🏆 USA & EU issued certificates for our devices
🏆 EIT Food Test Farm winner Finalist of 2024
🏆 China Overseas Talents Innovation and Entrepreneurship Competition
🏆 Partnerships with key market players (Varda Field ID, AGRIVI, SAS Agro, Kalo, Basf (Xarvio), Bayer, Syngenta etc.) Lessons learned 1️⃣ This was quite a challenge in building AI tools that could accurately adapt to the vast complexities of agronomic data. Initial models developed were rather far from the precision that agronomists required, struggling with symptom and stage variability across different crops. However, we further invested in our AI capabilities, enhancing our models by adding extensive data sets and collaborations with agricultural experts. This achieved two things: it not only enhanced the precision of our AI but also made our tools an inseparable companion for any agronomist by providing them with second-to-none insights and recommendations. 2️⃣ Another challenge was to convince the highly practical and quite skeptical agronomists to adopt this high-tech tool called Cropler. So, we shifted strategy and focused our efforts on education and hands-on involvement, showing agronomists not only how but why our technology worked. 3️⃣ One of the most significant challenges of launching the international expansion of our solution was overcoming the many regulatory, environmental, and operational hurdles spanning across continents, which drastically changed from region to region. We learned flexibility and local partnerships. By aligning ourselves with local agronomic experts and adapting our technology to meet regional regulations and needs, the stage was set for global impact-development of preparations for a major rollout in Europe by 2025. 4️⃣ Last, but not least, was a technical and logistical challenge to scale our technology from pilot projects to widespread usage by agronomists. So, we invested in scalable architecture and robust systems, supporting high demand for real-time data processing and global access. Our platform is not a tool; it's a 24/7 digital agronomist turning that data into actionable and timely advice. What Startups of The Year means to us Entering into HackerNoon's Startups of the Year is not an opportunity for Cropler but rather a stage to revolutionize the agribusiness panorama. We come to introduce our pioneering AI agri-camera technology that's going to change the world and make agriculture more predictable and effective. This is a moment in the spotlight to galvanize an industry for the attention of global investors, tech enthusiasts, and potential partners who are committed to transforming agriculture through innovation as much as we are. To be present there is already a loud statement of the capability and vision that we have. More than that, we are not just in attendance; we are leading from the front in this charge into the future where technology and sustainability come together to remake the standard of agriculture around the world. The insights and feedback that we get here from this eclectic tech community are very critical; it fuels our drive toward the 2025 launch of our Global Analytics. For us, this is more than a competition; this is a launching pad toward growth, visibility, and impact. Join us while we lead the way to a more efficient, sustainable, and predictable agricultural future! Vote for us today: https://hackernoon.com/startups/europe/europe-warsaw-poland Hey Hackers! Cropler has been nominated in HackerNoon's Startups of The Year 2024 awards in Warsaw, Poland under the Emerging Tech category and others. Cropler Cropler HackerNoon's Startups of The Year 2024 HackerNoon's Startups of The Year 2024 HackerNoon's Startups of The Year 2024 Emerging Tech category and others. Emerging Tech Emerging Tech Please vote for us here: Please vote for us here: 1️⃣ https://hackernoon.com/startups/europe/europe-warsaw-poland https://hackernoon.com/startups/europe/europe-warsaw-poland https://hackernoon.com/startups/europe/europe-warsaw-poland 2️⃣ https://hackernoon.com/startups/industry/iot https://hackernoon.com/startups/industry/iot https://hackernoon.com/startups/industry/iot 3️⃣ https://hackernoon.com/startups/industry/hardware https://hackernoon.com/startups/industry/hardware 4️⃣ https://hackernoon.com/startups/industry/climatetech https://hackernoon.com/startups/industry/climatetech Meet Cropler Cropler is the world’s first real-time remote photo plant monitoring technology that is about to become an AI-powered digital agronomical assistant. Cropler uses smart AI-powered mobile agricameras to help farmers and agribusinesses identify the key phenophases, diseases, and inputs efficiently to perform necessary agricultural operations in a timely manner. Cropler is the world’s first real-time remote photo plant monitoring technology that is about to become an AI-powered digital agronomical assistant. Cropler uses smart AI-powered mobile agricameras to help farmers and agribusinesses identify the key phenophases, diseases, and inputs efficiently to perform necessary agricultural operations in a timely manner. Cropler Cropler agricameras The Winning Team 1️⃣ Nik Bedunkevich LinkedIn Founder & CEO With over 10 years in software and 7+ years in hardware development, Nik's leadership in precision agriculture, backed by his experience at OneSoil, where he co-founded and led hardware development, has been instrumental. His background in Radio Engineering and his ability to integrate data exchange and soil analysis sensors have enabled Cropler to push the boundaries of AI-driven agricultural solutions. 2️⃣ Marie Sinkova LinkedIn CMO Marie’s 6+ years in marketing, including her impactful work at MEDvidi and EduDo, have significantly boosted our brand’s visibility. Her ability to develop engaging content and manage successful teams has increased revenue and brand recognition while minimizing negative reviews. Her strategic approach in various marketing areas has laid a solid foundation for Cropler development. 3️⃣ Andrii Zbrytskyi LinkedIn BDM With over 17 years in the agritech area, Andri Zbrytskyi has witnessed firsthand the ins and outs of clients resulting in better client/corporate relations, sales and even more business development for the company. AI agriculture solutions have found strategic partnerships thanks to his efforts and these have increased expanding the market base. 4️⃣ Xenia Niaborskaya LinkedIn Head of Design Xenia’s experience of more than 4 years in UX/UI design has played a key role in ensuring that our user interfaces work as expected and look good as well. Her capability in business-centered design and the process of user-centered design has improved the usability of our platform tremendously. 5️⃣ Eugene Voronets LinkedIn Tech Adviser Eugene’s 10+ years in backend development, particularly his expertise in high-load systems, ensures the robustness and scalability of our technology. His work at OneSoil, building APIs and fostering collaborations with industry leaders like John Deere and AWS, has played a critical role in shaping Cropler’s technical infrastructure. 1️⃣ Nik Bedunkevich Nik Bedunkevich LinkedIn LinkedIn LinkedIn LinkedIn Founder & CEO Founder & CEO With over 10 years in software and 7+ years in hardware development, Nik's leadership in precision agriculture, backed by his experience at OneSoil, where he co-founded and led hardware development, has been instrumental. His background in Radio Engineering and his ability to integrate data exchange and soil analysis sensors have enabled Cropler to push the boundaries of AI-driven agricultural solutions. 2️⃣ Marie Sinkova Marie Sinkova LinkedIn LinkedIn LinkedIn LinkedIn CMO CMO Marie’s 6+ years in marketing, including her impactful work at MEDvidi and EduDo, have significantly boosted our brand’s visibility. Her ability to develop engaging content and manage successful teams has increased revenue and brand recognition while minimizing negative reviews. Her strategic approach in various marketing areas has laid a solid foundation for Cropler development. 3️⃣ Andrii Zbrytskyi Andrii Zbrytskyi LinkedIn LinkedIn LinkedIn LinkedIn BDM BDM With over 17 years in the agritech area, Andri Zbrytskyi has witnessed firsthand the ins and outs of clients resulting in better client/corporate relations, sales and even more business development for the company. AI agriculture solutions have found strategic partnerships thanks to his efforts and these have increased expanding the market base. 4️⃣ Xenia Niaborskaya Xenia Niaborskaya LinkedIn LinkedIn LinkedIn LinkedIn Head of Design Head of Design Xenia’s experience of more than 4 years in UX/UI design has played a key role in ensuring that our user interfaces work as expected and look good as well. Her capability in business-centered design and the process of user-centered design has improved the usability of our platform tremendously. 5️⃣ Eugene Voronets Eugene Voronets LinkedIn LinkedIn LinkedIn LinkedIn Tech Adviser Tech Adviser Eugene’s 10+ years in backend development, particularly his expertise in high-load systems, ensures the robustness and scalability of our technology. His work at OneSoil, building APIs and fostering collaborations with industry leaders like John Deere and AWS, has played a critical role in shaping Cropler’s technical infrastructure. What Cropler does differently We aim to revolutionize agriculture with Cropler's global plant monitoring technology, which uses AI-powered agricameras and remote sensing data to provide farmers, agronomists, and agribusinesses with predictive field insights and global yield analytics for optimized crop production. global plant monitoring technology, Cropler’s unique, AI-powered plant health data allows farmers and agribusinesses to address issues before they escalate, unlike drones or weather stations, which often provide information only after problems have already progressed and plants experience severe damage. Early disease and crop stress detection ensures that farmers can act timely to maximize yields and optimize fertilizers and pesticides application. Cropler isn’t just about monitoring—it’s about driving actionable insights that make farming more efficient, sustainable, and profitable. Cropler isn’t just about monitoring—it’s about driving actionable insights that make farming more efficient, sustainable, and profitable. Milestones and achievements 🏆 357 devices deployed 🏆 Revenue of $53k in 2024 🏆 AI disease & leaf damages integration 🏆 iOS & Android app release 🏆 10 dealer centers in multiple countries 🏆 16 countries (EU + USA) have chosen our devices 🏆 USA & EU issued certificates for our devices 🏆 EIT Food Test Farm winner Finalist of 2024 🏆 China Overseas Talents Innovation and Entrepreneurship Competition 🏆 Partnerships with key market players (Varda Field ID, AGRIVI, SAS Agro, Kalo, Basf (Xarvio), Bayer, Syngenta etc.) 🏆 357 devices deployed 🏆 Revenue of $53k in 2024 🏆 AI disease & leaf damages integration 🏆 iOS & Android app release 🏆 10 dealer centers in multiple countries 🏆 16 countries (EU + USA) have chosen our devices 🏆 USA & EU issued certificates for our devices 🏆 EIT Food Test Farm winner Finalist of 2024 🏆 China Overseas Talents Innovation and Entrepreneurship Competition 🏆 Partnerships with key market players (Varda Field ID, AGRIVI, SAS Agro, Kalo, Basf (Xarvio), Bayer, Syngenta etc.) Lessons learned 1️⃣ This was quite a challenge in building AI tools that could accurately adapt to the vast complexities of agronomic data. Initial models developed were rather far from the precision that agronomists required, struggling with symptom and stage variability across different crops. However, we further invested in our AI capabilities, enhancing our models by adding extensive data sets and collaborations with agricultural experts. This achieved two things: it not only enhanced the precision of our AI but also made our tools an inseparable companion for any agronomist by providing them with second-to-none insights and recommendations. 2️⃣ Another challenge was to convince the highly practical and quite skeptical agronomists to adopt this high-tech tool called Cropler. So, we shifted strategy and focused our efforts on education and hands-on involvement, showing agronomists not only how but why our technology worked. agronomists 3️⃣ One of the most significant challenges of launching the international expansion of our solution was overcoming the many regulatory, environmental, and operational hurdles spanning across continents, which drastically changed from region to region. We learned flexibility and local partnerships. By aligning ourselves with local agronomic experts and adapting our technology to meet regional regulations and needs, the stage was set for global impact-development of preparations for a major rollout in Europe by 2025. global impact-development 4️⃣ Last, but not least, was a technical and logistical challenge to scale our technology from pilot projects to widespread usage by agronomists. So, we invested in scalable architecture and robust systems, supporting high demand for real-time data processing and global access. Our platform is not a tool; it's a 24/7 digital agronomist turning that data into actionable and timely advice. Our platform is not a tool; it's a 24/7 digital agronomist turning that data into actionable and timely advice. Our platform is not a tool; it's a 24/7 digital agronomist turning that data into actionable and timely advice. What Startups of The Year means to us Entering into HackerNoon's Startups of the Year is not an opportunity for Cropler but rather a stage to revolutionize the agribusiness panorama. We come to introduce our pioneering AI agri-camera technology that's going to change the world and make agriculture more predictable and effective. This is a moment in the spotlight to galvanize an industry for the attention of global investors, tech enthusiasts, and potential partners who are committed to transforming agriculture through innovation as much as we are. revolutionize the agribusiness To be present there is already a loud statement of the capability and vision that we have. To be present there is already a loud statement of the capability and vision that we have. More than that, we are not just in attendance; we are leading from the front in this charge into the future where technology and sustainability come together to remake the standard of agriculture around the world. The insights and feedback that we get here from this eclectic tech community are very critical; it fuels our drive toward the 2025 launch of our Global Analytics. For us, this is more than a competition; this is a launching pad toward growth, visibility, and impact. For us, this is more than a competition; this is a launching pad toward growth, visibility, and impact. Join us while we lead the way to a more efficient, sustainable, and predictable agricultural future! Vote for us today: https://hackernoon.com/startups/europe/europe-warsaw-poland Vote for us today: https://hackernoon.com/startups/europe/europe-warsaw-poland Vote for us today: https://hackernoon.com/startups/europe/europe-warsaw-poland

AI-Driven Solutions for Modern Agritech: Interview with SOTY 2024 Nominee, Cropler

From a young age, Vishwanadham Mandala had a keen interest in technology, setting the stage for a distinguished career in the IT sector. Growing up in India, he earned a BTech and MTech in Computer Science & Engineering, fueled by a passion to harness the power of data. His dedication to academia and a relentless quest for knowledge led him to Indiana University in the United States, where he completed an MS in Data Science. He continues to push the envelope by pursuing a PhD in AI & ML. Currently, Vishwanadham is a prominent leader in the field of data engineering. Known for his leadership mantra, "Consistent work, each day, every day," he blends strategic foresight with unwavering persistence. His expertise as an AI & ML leader in critical automotive applications has advanced automotive manufacturing processes and safety standards, enhancing public safety. As a mentor and speaker, Vishwanadham is committed to developing the next generation of technology professionals, ensuring that his legacy of excellence leaves a lasting impact on the industry. Additionally, he has been a member of the Forbes Technology Council since May 2024. Path to Big Data Fascination with the transformative power of data ignited Vishwanadham’s pursuit of a career in Big Data and data engineering. His journey through critical roles at IBM, Oracle, Sierra-Cedar, and Ciena allowed him to work globally, gaining diverse experiences and honing his skills. Reflecting on his career progression, Vishwanadham notes how these experiences shaped his expertise and paved the way to his current role at Cummins, where he spearheads significant projects and integrates AI/ML technologies to drive the company's future direction. Vishwanadham's academic background has been instrumental in his professional success. With degrees from prestigious institutions in India and the United States, he notes, "My diverse educational background gave me a solid foundation in technical knowledge and critical thinking skills." This exposure to different academic environments and perspectives has enriched his understanding of global technological trends and best practices, enabling him to excel in his career and make meaningful contributions to the IT industry. "The exposure to different academic environments and perspectives enriched my understanding of global technological trends and best practices," he explains. This comprehensive background not only allowed him to grow professionally but also equipped him with the skills necessary to drive innovation and efficiency at Cummins, solidifying his role as a leader in the integration of AI and ML technologies. Game-changing Projects Across Industries Vishwanadham led a groundbreaking project that significantly impacted Ciena’s strategic direction in the data space. His innovative approach and strategic leadership were instrumental in shaping Ciena's technology roadmap, highlighting his ability to drive impactful change and foster innovation within the organization. His work showcased his expertise in data engineering and his vision for future technological advancements. Vishwanadham's experience spans various industries, including manufacturing and healthcare, where he has successfully integrated AI and ML solutions to address unique challenges. He explains that his approach involves focusing on both fundamental and superficial facets of data. By adapting to each sector's unique challenges and nuances, he tailors his solutions to best match the environment. This method of integrating AI and ML solutions has enabled Vishwanadham to continuously learn and grow with each encounter. "This method has enriched my expertise, allowing me to tackle various challenges effectively and continuously learn and grow with each encounter," he notes. By leveraging his diverse experience and innovative approach, Vishwanadham has been able to make significant contributions to the fields of manufacturing and healthcare, demonstrating his versatility and proficiency in AI and data engineering. Innovative IoT Patents for Rural Healthcare One of Vishwanadham’s most notable patents involves a groundbreaking IoT solution for medical devices, specifically designed to enhance healthcare in rural areas. This innovative patent focuses on leveraging telemetry data processing to provide real-time health insights, which can significantly improve patient outcomes in remote locations. By utilizing AI and ML, the solution aims to deliver instantaneous and accurate health data, allowing for timely medical interventions. Vishwanadham explains that this technology "enables timely medical interventions and improves access to quality healthcare for rural populations." This IoT innovation has the potential to transform rural healthcare by bridging the gap between remote patients and advanced medical care. "By leveraging AI/ML, this innovation aims to offer instantaneous and accurate health data," says Vishwanadham, highlighting the critical role of advanced technology in improving healthcare accessibility and quality in underserved areas. This patent exemplifies his commitment to using technology to create impactful solutions that address real-world challenges. Leading and Mentoring in AI Vishwanadham emphasizes that leading successful AI and ML initiatives requires a strong foundation in data science, strategic vision, and a commitment to continuous learning. He believes that a disciplined work ethic, cooperative teamwork, and innovative thinking are essential qualities for driving progress in these fields. Additionally, "Effective communication and inspiring and guiding teams are also essential for driving innovation," Vishwanadham states, highlighting the multifaceted nature of leadership in AI and ML. In addition to his leadership skills, Vishwanadham is deeply committed to mentoring and teaching in the AI and ML fields. He actively shares his extensive knowledge and experience with aspiring professionals. "Mentoring helps individuals grow and contributes to the industry's evolution by fostering a culture of continuous learning and innovation," he explains. By guiding the next generation of AI and ML experts, Vishwanadham aims to create a robust talent pool capable of tackling future challenges and driving technological advancements. This dual focus on leadership and mentorship highlights Vishwanadham's holistic approach to advancing the AI and ML fields. He understands that the future of technology depends not only on current innovations but also on preparing the next generation to continue pushing the boundaries of what is possible. AI Innovations for Safety and Supply Chains Looking to the future, Vishwanadham aspires to leverage AI and ML to significantly advance citizen safety and improve supply chains by implementing cutting-edge technologies and innovative solutions. He is particularly excited about the potential of Edge AI/ML, which he describes as "a revolutionary approach to telemetry data processing that can provide instantaneous and accurate insights." One of his current projects focuses on integrating this technology into the automotive industry to enhance vehicle safety and protect citizens. "By staying ahead of the competition through constant learning and innovation, I aim to drive transformative change," he asserts. His commitment to using advanced AI and ML technologies to solve real-world problems highlights his vision for a safer and more efficient future, where technology plays a crucial role in protecting lives and optimizing operations. In a world becoming increasingly data-centric, Vishwanadham’s expertise serves as a beacon for those navigating the complexities of modern business landscapes. His journey reminds us that mastering data is not just about understanding technology but also about leveraging it to make remarkable contributions to society. As he continues to mentor the next generation of tech professionals, his influence extends beyond projects and patents, fostering a culture of continuous learning and innovation in the industry. From a young age, Vishwanadham Mandala had a keen interest in technology, setting the stage for a distinguished career in the IT sector. Growing up in India, he earned a BTech and MTech in Computer Science & Engineering, fueled by a passion to harness the power of data. His dedication to academia and a relentless quest for knowledge led him to Indiana University in the United States, where he completed an MS in Data Science. He continues to push the envelope by pursuing a PhD in AI & ML. Currently, Vishwanadham is a prominent leader in the field of data engineering. Known for his leadership mantra, "Consistent work, each day, every day," he blends strategic foresight with unwavering persistence. His expertise as an AI & ML leader in critical automotive applications has advanced automotive manufacturing processes and safety standards, enhancing public safety. As a mentor and speaker, Vishwanadham is committed to developing the next generation of technology professionals, ensuring that his legacy of excellence leaves a lasting impact on the industry. Additionally, he has been a member of the Forbes Technology Council since May 2024. Path to Big Data Fascination with the transformative power of data ignited Vishwanadham’s pursuit of a career in Big Data and data engineering. His journey through critical roles at IBM, Oracle, Sierra-Cedar, and Ciena allowed him to work globally, gaining diverse experiences and honing his skills. Reflecting on his career progression, Vishwanadham notes how these experiences shaped his expertise and paved the way to his current role at Cummins, where he spearheads significant projects and integrates AI/ML technologies to drive the company's future direction. Vishwanadham's academic background has been instrumental in his professional success. With degrees from prestigious institutions in India and the United States, he notes, "My diverse educational background gave me a solid foundation in technical knowledge and critical thinking skills." This exposure to different academic environments and perspectives has enriched his understanding of global technological trends and best practices, enabling him to excel in his career and make meaningful contributions to the IT industry. "The exposure to different academic environments and perspectives enriched my understanding of global technological trends and best practices," he explains. This comprehensive background not only allowed him to grow professionally but also equipped him with the skills necessary to drive innovation and efficiency at Cummins, solidifying his role as a leader in the integration of AI and ML technologies. Game-changing Projects Across Industries Vishwanadham led a groundbreaking project that significantly impacted Ciena’s strategic direction in the data space. His innovative approach and strategic leadership were instrumental in shaping Ciena's technology roadmap, highlighting his ability to drive impactful change and foster innovation within the organization. His work showcased his expertise in data engineering and his vision for future technological advancements. Vishwanadham's experience spans various industries, including manufacturing and healthcare, where he has successfully integrated AI and ML solutions to address unique challenges. He explains that his approach involves focusing on both fundamental and superficial facets of data. By adapting to each sector's unique challenges and nuances, he tailors his solutions to best match the environment. This method of integrating AI and ML solutions has enabled Vishwanadham to continuously learn and grow with each encounter. "This method has enriched my expertise, allowing me to tackle various challenges effectively and continuously learn and grow with each encounter," he notes. By leveraging his diverse experience and innovative approach, Vishwanadham has been able to make significant contributions to the fields of manufacturing and healthcare, demonstrating his versatility and proficiency in AI and data engineering. Innovative IoT Patents for Rural Healthcare One of Vishwanadham’s most notable patents involves a groundbreaking IoT solution for medical devices, specifically designed to enhance healthcare in rural areas. This innovative patent focuses on leveraging telemetry data processing to provide real-time health insights, which can significantly improve patient outcomes in remote locations. By utilizing AI and ML, the solution aims to deliver instantaneous and accurate health data, allowing for timely medical interventions. Vishwanadham explains that this technology "enables timely medical interventions and improves access to quality healthcare for rural populations." This IoT innovation has the potential to transform rural healthcare by bridging the gap between remote patients and advanced medical care. "By leveraging AI/ML, this innovation aims to offer instantaneous and accurate health data," says Vishwanadham, highlighting the critical role of advanced technology in improving healthcare accessibility and quality in underserved areas. This patent exemplifies his commitment to using technology to create impactful solutions that address real-world challenges. Leading and Mentoring in AI Vishwanadham emphasizes that leading successful AI and ML initiatives requires a strong foundation in data science, strategic vision, and a commitment to continuous learning. He believes that a disciplined work ethic, cooperative teamwork, and innovative thinking are essential qualities for driving progress in these fields. Additionally, "Effective communication and inspiring and guiding teams are also essential for driving innovation," Vishwanadham states, highlighting the multifaceted nature of leadership in AI and ML. In addition to his leadership skills, Vishwanadham is deeply committed to mentoring and teaching in the AI and ML fields. He actively shares his extensive knowledge and experience with aspiring professionals. "Mentoring helps individuals grow and contributes to the industry's evolution by fostering a culture of continuous learning and innovation," he explains. By guiding the next generation of AI and ML experts, Vishwanadham aims to create a robust talent pool capable of tackling future challenges and driving technological advancements. This dual focus on leadership and mentorship highlights Vishwanadham's holistic approach to advancing the AI and ML fields. He understands that the future of technology depends not only on current innovations but also on preparing the next generation to continue pushing the boundaries of what is possible. AI Innovations for Safety and Supply Chains Looking to the future, Vishwanadham aspires to leverage AI and ML to significantly advance citizen safety and improve supply chains by implementing cutting-edge technologies and innovative solutions. He is particularly excited about the potential of Edge AI/ML, which he describes as "a revolutionary approach to telemetry data processing that can provide instantaneous and accurate insights." One of his current projects focuses on integrating this technology into the automotive industry to enhance vehicle safety and protect citizens. "By staying ahead of the competition through constant learning and innovation, I aim to drive transformative change," he asserts. His commitment to using advanced AI and ML technologies to solve real-world problems highlights his vision for a safer and more efficient future, where technology plays a crucial role in protecting lives and optimizing operations. In a world becoming increasingly data-centric, Vishwanadham’s expertise serves as a beacon for those navigating the complexities of modern business landscapes. His journey reminds us that mastering data is not just about understanding technology but also about leveraging it to make remarkable contributions to society. As he continues to mentor the next generation of tech professionals, his influence extends beyond projects and patents, fostering a culture of continuous learning and innovation in the industry.

Mastering Data in the Modern Age with Vishwanadham Mandala

Авалоданне дадзенымі ў сучасную эпоху з Vishwanadham Mandala

বিশ্বধাম মন্ডালার সাথে আধুনিক যুগে ডেটা আয়ত্ত করা

Dominar les dades a l'Edat Moderna amb Vishwanadham Mandala

Mestring af data i den moderne tidsalder med Vishwanadham Mandala

Dominando los datos en la era moderna con Vishwanadham Mandala

שליטה בנתונים בעידן המודרני עם Vishwanadham Mandala

Padroneggiare i dati nell'era moderna con Vishwanadham Mandala

ヴィシュワナダム・マンダラによる現代のデータ活用

Vishwanadham Mandala로 현대의 데이터 마스터링

Menguasai Data di Zaman Moden dengan Vishwanadham Mandala

Opanowanie danych w erze nowoczesności z Vishwanadham Mandala

Освоение данных в современную эпоху с помощью Vishwanadham Mandala

Using AWS Rekognition to Power Object Detection for Recommendations and Content Moderation

I had a chance to learn more about the up-to-date comparison of data warehouses lately working on my side projects. It's hard to do benchmarks for databases, but it's harder to do comparisons on their pricing. There are 3 major things you need to consider: Considerations Storage Cost Often providers such as Redshift and Snowflake use their proprietary database formats. While the pricing is based on the data volume, it's hard to estimate how much data space you will need before actually using them. However; looking at the storage pricing for Snowflake, S3, and BigQuery the margin is pretty small for the storage. From Snowflake, we know that the storage cost is usually < 10% of the total cost of data warehouses. Also, the compaction for the files doesn't make a huge difference (~30%) in the storage according to Clickbench. If you use Iceberg Tables, you can use the same table in all the data warehouses. Compute Cost Some charge based on the data your query processed, and some charge based on the compute units you use under the hood (warehouse, slot, etc.) The performance for specific operations such as ingestion, transformation, querying small tables vs big tables, and the use of specific SQL syntax such as WINDOW functions has a huge impact on the cost due to the way underlying engines implement them. Also, the performance/cost changes over time with the software updates. Decoupling storage from computing is important because unless you have an anti-pattern use case, the most expensive pillar (> 90%) is the computing cost in all the data warehouses. While For compute, here is the terminology they use for compute: Compute Capacity / Minimum cost of unit

Data Processing / Price per TB



Snowflake

Warehouse ($2 / hour)

-



AWS Athena

DPU ($3.6 / hour)

Data scanned ($5)



AWS Redshift Serverless

RPUs( $3.65 / hour)

-



Google BigQuery

Slots ($2 / hour)

Data scanned ($6.25)



Databricks

DBU ($2.8 / hour)

- Data Transfer Considering you use a cloud provider already and store your data there, they incur egress/ingress if you're transferring the data between different regions. If you don't use compression or row-oriented formats such as CSV, JSON instead of columnar formats such as Parquet or ORC, both storage and data transfer costs will be significantly higher. However, the native data formats in data warehouses use columnar formats which are more efficient in terms of storage and data transfer. Performance Impact on Query Engine Also, keep in mind that the recent findings show that the compute performance highly varies based on the workloads. It's easier to get the data into Snowflake but the transformation is expensive. Snowflake and Redshift have both published representative samples of real-world queries, and the way people actually use these systems is INTERESTING. The main workload is ingest and transformation! pic.twitter.com/GgnYOfxVtO
— George Fraser (@frasergeorgew) September 17, 2024 Snowflake Warehouse Snowflake uses Warehouses for hardware abstraction. They are mapped to EC2 instances on AWS, VM machines on GCP, and Azure. They scale both horizontally and vertically as you run queries on these warehouses and auto-start & auto-suspend based on your configuration. While one warehouse can run multiple queries simultaneously, queries try to use the resources as much as possible. The cost is fairly predictable because the warehouse concept lets you tune in between latency and performance. If you want to run queries 2x efficiently, just switch to a bigger warehouse (ex: from x-small to small) On the flip side, you pay for the warehouse during auto-suspend, and your queries suffer 1-2 seconds of latency for the auto-start. Even if you run a query that takes 5 seconds to run, you pay for a warehouse 60 seconds at a minimum, so you often need to optimize your warehouse as you scale. This work is non-trivial if you're not familiar with Snowflake, and there are even startups (Select.dev, Keebola, etc.) that help you optimize your warehouse usage. Snowflake charges based on credits, which cost $2 today. (2024-09) You can scale in or out (multi-clusters) by giving you the flexibility to tune your workload. Here are Snowflake warehouse types: Snowflake has Streams and Tasks, which let you create workflows based on event and time-based triggers. For incremental processing, you have these options: Snowflake doesn't offer any discount for the reserved capacity but offers a discount for the credits you buy in advance depending on your negotiation. You can use your AWS, Azure, and GCP credits to pay for Snowflake. Snowflake Serverless Tasks Snowflake has a Serverless Tasks feature, which automatically provisions warehouses under the hood for you to scale as your query gets more expensive. It costs 0.9x of the warehouse cost for the same duration. Keep in mind that a single warehouse can run multiple queries concurrently on Snowflake, so it's indeed more expensive than using warehouses. In order to use Serverless Tasks, you need to create a task, using CREATE TASK syntax. Tasks are suitable if you would like to run the same query based on an internal as a workflow but Snowflake doesn't support a serverless model for typical SELECT queries. I believe soon enough they will release such a feature to keep up with the competition. AWS Redshift Serverless Redshift Serverless is AWS's new product, superseding Redshift we know of. It decouples storage from compute and has native integration with S3. I didn't include AWS Athena in the comparison because Redshift Serverless seems to outperform Athena. You need to create a workspace, defining base capacity RPUs based on your allocations. The minimum for base is 8, which costs and the RPU price is $0.467, which makes $3.65 per hour. While it's serverless, Redshift charges you a minimum of 60 seconds when you start using the compute. It's similar to Snowflake in that sense. It scales to zero when you don't query the tables. AWS Athena AWS Athena is a Headless Data Warehouse, using Glue as the Data Catalog and S3 as the data lake. It charges you based on the data scanned for the query by default, but you can use provisioned capacity to manage the workloads in a serverless way. The minimum cost is $3.6 per DPU per hour. Databricks Databricks uses the BYOC (Bring-your-cloud) model. You install Databricks in your cloud provider, and it provisions a Kubernetes cluster for you. It runs a minimum of 4 nodes in the cluster even if you don't use it so it doesn't scale to zero, unlike all the other options. The pricing is based on DBU, Databricks Unit. The minimum cost is $0.07 per DBU, which makes $2.8 per hour. Google BigQuery BigQuery has two pricing models; by default, it's demand-based pricing, which is simply TBs scanned for the query. While you can get a great performance, it comes at a cost. Your innocent query select * from fact_table limit 1 can end up processing TBs of data if you're not careful, but luckily, the BigQuery console provides you with some stats before running the query. With Capacity-based pricing, you can allocate slots for your BigQuery project, and they threshold the CPU time used at a given interval. I would like to think of slots at the CPU units. It's cost-efficient compared to Snowflake, due to BigQuery's autoscaler. The minimum reservation is 50 slots, with the current price (2024-09, $0.04), the minimum cost unit is $2/hour if you run it a full hour. You don't need to worry about things like cold start performance issues or optimizing warehouse usage. Each query consumes the capacity defined for the project you have the reservation. It perfectly scales to zero when the tables are not queried. Related Work This VM did not have enough memory to run all queries.
How do people use Snowflake and Redshift? So What? The pricing and storage are not much of a difference between the data warehouses. The compute cost is the most expensive part of the data warehouses. The performance of the queries highly varies based on the workloads and where the data is, so it's usually best to do discovery with all these solutions and pick the tech that your team thinks is the best. Next up, we are: Part 2: Comparing features of data warehouses Would you like to comment? Reach me out @bu7emba! GitHub|Twitter I had a chance to learn more about the up-to-date comparison of data warehouses lately working on my side projects. It's hard to do benchmarks for databases, but it's harder to do comparisons on their pricing. There are 3 major things you need to consider: Considerations Storage Cost Often providers such as Redshift and Snowflake use their proprietary database formats. While the pricing is based on the data volume, it's hard to estimate how much data space you will need before actually using them. However; looking at the storage pricing for Snowflake , S3 , and BigQuery the margin is pretty small for the storage. Snowflake S3 BigQuery From Snowflake, we know that the storage cost is usually < 10% of the total cost of data warehouses. Also, the compaction for the files doesn't make a huge difference (~30%) in the storage according to Clickbench . Clickbench If you use Iceberg Tables, you can use the same table in all the data warehouses. If you use Iceberg Tables, you can use the same table in all the data warehouses. Compute Cost Some charge based on the data your query processed, and some charge based on the compute units you use under the hood (warehouse, slot, etc.) The performance for specific operations such as ingestion, transformation, querying small tables vs big tables, and the use of specific SQL syntax such as WINDOW functions has a huge impact on the cost due to the way underlying engines implement them. Also, the performance/cost changes over time with the software updates. Decoupling storage from computing is important because unless you have an anti-pattern use case, the most expensive pillar (> 90%) is the computing cost in all the data warehouses. While For compute, here is the terminology they use for compute: Compute Capacity / Minimum cost of unit

Data Processing / Price per TB



Snowflake

Warehouse ($2 / hour)

-



AWS Athena

DPU ($3.6 / hour)

Data scanned ($5)



AWS Redshift Serverless

RPUs( $3.65 / hour)

-



Google BigQuery

Slots ($2 / hour)

Data scanned ($6.25)



Databricks

DBU ($2.8 / hour)

- Compute Capacity / Minimum cost of unit

Data Processing / Price per TB Snowflake

Warehouse ($2 / hour)

- AWS Athena

DPU ($3.6 / hour)

Data scanned ($5) AWS Redshift Serverless

RPUs( $3.65 / hour)

- Google BigQuery

Slots ($2 / hour)

Data scanned ($6.25) Databricks

DBU ($2.8 / hour)

- Compute Capacity / Minimum cost of unit Data Processing / Price per TB Compute Capacity / Minimum cost of unit Compute Capacity / Minimum cost of unit Data Processing / Price per TB Data Processing / Price per TB Snowflake Warehouse ($2 / hour) - Snowflake Snowflake Snowflake Warehouse ($2 / hour) Warehouse ( $2 / hour ) $2 / hour - - AWS Athena DPU ($3.6 / hour) Data scanned ($5) AWS Athena AWS Athena AWS Athena DPU ($3.6 / hour) DPU ($3.6 / hour) DPU Data scanned ($5) Data scanned ($5) Data scanned AWS Redshift Serverless RPUs( $3.65 / hour) - AWS Redshift Serverless AWS Redshift Serverless AWS Redshift Serverless RPUs( $3.65 / hour) RPUs ( $3.65 / hour) RPUs - - Google BigQuery Slots ($2 / hour) Data scanned ($6.25) Google BigQuery Google BigQuery Google BigQuery Slots ($2 / hour) Slots ($2 / hour) Slots Data scanned ($6.25) Data scanned ($6.25) Databricks DBU ($2.8 / hour) - Databricks Databricks Databricks DBU ($2.8 / hour) DBU ($2.8 / hour) DBU - - Data Transfer Considering you use a cloud provider already and store your data there, they incur egress/ingress if you're transferring the data between different regions. If you don't use compression or row-oriented formats such as CSV, JSON instead of columnar formats such as Parquet or ORC, both storage and data transfer costs will be significantly higher. However, the native data formats in data warehouses use columnar formats which are more efficient in terms of storage and data transfer. Performance Impact on Query Engine Also, keep in mind that the recent findings show that the compute performance highly varies based on the workloads. It's easier to get the data into Snowflake but the transformation is expensive. Snowflake and Redshift have both published representative samples of real-world queries, and the way people actually use these systems is INTERESTING. The main workload is ingest and transformation! pic.twitter.com/GgnYOfxVtO — George Fraser (@frasergeorgew) September 17, 2024 Snowflake and Redshift have both published representative samples of real-world queries, and the way people actually use these systems is INTERESTING. The main workload is ingest and transformation! pic.twitter.com/GgnYOfxVtO pic.twitter.com/GgnYOfxVtO — George Fraser (@frasergeorgew) September 17, 2024 September 17, 2024 Snowflake Warehouse Snowflake uses Warehouses for hardware abstraction. They are mapped to EC2 instances on AWS, VM machines on GCP, and Azure. They scale both horizontally and vertically as you run queries on these warehouses and auto-start & auto-suspend based on your configuration. While one warehouse can run multiple queries simultaneously, queries try to use the resources as much as possible. The cost is fairly predictable because the warehouse concept lets you tune in between latency and performance. If you want to run queries 2x efficiently, just switch to a bigger warehouse (ex: from x-small to small ) x-small small On the flip side, you pay for the warehouse during auto-suspend, and your queries suffer 1-2 seconds of latency for the auto-start. Even if you run a query that takes 5 seconds to run, you pay for a warehouse 60 seconds at a minimum, so you often need to optimize your warehouse as you scale. This work is non-trivial if you're not familiar with Snowflake, and there are even startups (Select.dev, Keebola, etc.) that help you optimize your warehouse usage. Snowflake charges based on credits, which cost $2 today. (2024-09) You can scale in or out (multi-clusters) by giving you the flexibility to tune your workload. Here are Snowflake warehouse types : warehouse types Snowflake has Streams and Tasks , which let you create workflows based on event and time-based triggers. For incremental processing, you have these options: Streams Tasks Snowflake doesn't offer any discount for the reserved capacity but offers a discount for the credits you buy in advance depending on your negotiation. You can use your AWS, Azure, and GCP credits to pay for Snowflake. Snowflake doesn't offer any discount for the reserved capacity but offers a discount for the credits you buy in advance depending on your negotiation. You can use your AWS, Azure, and GCP credits to pay for Snowflake. Snowflake Serverless Tasks Snowflake has a Serverless Tasks feature, which automatically provisions warehouses under the hood for you to scale as your query gets more expensive. It costs 0.9x of the warehouse cost for the same duration. Keep in mind that a single warehouse can run multiple queries concurrently on Snowflake, so it's indeed more expensive than using warehouses. In order to use Serverless Tasks, you need to create a task, using CREATE TASK syntax. Tasks are suitable if you would like to run the same query based on an internal as a workflow but Snowflake doesn't support a serverless model for typical SELECT queries. I believe soon enough they will release such a feature to keep up with the competition. CREATE TASK SELECT AWS Redshift Serverless Redshift Serverless is AWS's new product, superseding Redshift we know of. It decouples storage from compute and has native integration with S3. I didn't include AWS Athena in the comparison because Redshift Serverless seems to outperform Athena. You need to create a workspace, defining base capacity RPUs based on your allocations. The minimum for base is 8, which costs and the RPU price is $0.467 , which makes $3.65 per hour. RPUs $0.467 While it's serverless, Redshift charges you a minimum of 60 seconds when you start using the compute. It's similar to Snowflake in that sense. It scales to zero when you don't query the tables. AWS Athena AWS Athena is a Headless Data Warehouse, using Glue as the Data Catalog and S3 as the data lake. It charges you based on the data scanned for the query by default, but you can use provisioned capacity to manage the workloads in a serverless way. The minimum cost is $3.6 per DPU per hour. $3.6 Databricks Databricks uses the BYOC (Bring-your-cloud) model. You install Databricks in your cloud provider, and it provisions a Kubernetes cluster for you. It runs a minimum of 4 nodes in the cluster even if you don't use it so it doesn't scale to zero, unlike all the other options. The pricing is based on DBU, Databricks Unit. The minimum cost is $0.07 per DBU, which makes $2.8 per hour. $0.07 Google BigQuery BigQuery has two pricing models; by default, it's demand-based pricing, which is simply TBs scanned for the query. While you can get a great performance, it comes at a cost. Your innocent query select * from fact_table limit 1 can end up processing TBs of data if you're not careful, but luckily, the BigQuery console provides you with some stats before running the query. select * from fact_table limit 1 With Capacity-based pricing , you can allocate slots for your BigQuery project, and they threshold the CPU time used at a given interval. I would like to think of slots at the CPU units. It's cost-efficient compared to Snowflake, due to BigQuery's autoscaler. Capacity-based pricing The minimum reservation is 50 slots, with the current price (2024-09, $0.04 ), the minimum cost unit is $2/hour if you run it a full hour. You don't need to worry about things like cold start performance issues or optimizing warehouse usage. Each query consumes the capacity defined for the project you have the reservation. It perfectly scales to zero when the tables are not queried. $0.04 $2/hour Related Work This VM did not have enough memory to run all queries. How do people use Snowflake and Redshift? This VM did not have enough memory to run all queries. This VM did not have enough memory to run all queries. How do people use Snowflake and Redshift? How do people use Snowflake and Redshift? So What? The pricing and storage are not much of a difference between the data warehouses. The compute cost is the most expensive part of the data warehouses. The performance of the queries highly varies based on the workloads and where the data is, so it's usually best to do discovery with all these solutions and pick the tech that your team thinks is the best. Next up, we are: Part 2: Comparing features of data warehouses Part 2: Comparing features of data warehouses Part 2: Comparing features of data warehouses Would you like to comment? Reach me out @bu7emba ! @bu7emba GitHub | Twitter GitHub Twitter

Part 1: A Comparison Between the Pricing Models of Modern Data Warehouses

HackerNoon: What is your company in 2–5 words? Dave Wreski: The open-source email security provider. Why is now the time for your company to exist? Email-borne risk has never been greater. Over 90% of modern cyberattacks begin with a phishing email. Attacks like spear phishing, fileless malware, and zero-day exploits are becoming increasingly difficult to detect and block. Basic email protection, like the security features provided in Microsoft 365 and Google Workspace, is no longer sufficient to make email safe for business. Advanced, multi-layered solutions capable of anticipating and blocking known and emerging threats before they reach the inbox are necessary in this modern threat environment. What do you love about your team, and why are you the ones to solve this problem? As users of and contributors to open-source development, we share the values of transparency and collaboration. Our unique use of open-source development in email security enables us to provide flexible, cost-efficient, and exceptionally secure solutions and offer real-time updates to keep our customers ahead of the latest threats. If you weren’t building your startup, what would you be doing? I would be contributing to Internet security in another way. Before starting Guardian Digital, I was a security engineer at UPS, which I enjoyed and found very rewarding. I also love cooking and writing, so I would likely pursue these passions. At the moment, how do you measure success? What are your metrics? I measure success in the number of malicious emails our solution blocks, protecting our clients from a potential cyberattack or data breach. I also take pride in retaining our clients, many of whom have been with us for decades, and continuing to acquire new clients worldwide. In a few sentences, what do you offer to whom? We offer threat-ready, fully supported protection against the latest and most advanced email threats for businesses of all sizes in all industries. Our multi-layered security system anticipates and blocks all threats before they reach the inbox, leveraging AI-based detection and expert around-the-clock system monitoring and support. Our managed services extend small businesses’ IT resources and enhance security, delivering a rapid return on investment (ROI). What’s most exciting about your traction to date? We have continued to grow our Product offering and client base over the past 2+ decades. We now offer Security Awareness Training and vCISO email security services. We have also developed an intuitive real-time Dashboard for our solution, giving businesses complete visibility and control over their email security. Where do you think your growth will be next year? We expect to continue acquiring new clients over the next year, as we are investing heavily in our marketing efforts and developing our solution. Our clients come to us for additional protection against today’s advanced threats that go unidentified by default cloud email security in Microsoft 365 and Google Workspace. Our clients are looking to reduce support overhead while bolstering cloud email protection to defend against threats like targeted spear phishing and business email compromise, making our solution ideal for their requirements. Tell us about your first paying customer and revenue expectations over the next year. Guardian Digital's roots are as an open-source Internet security company. It provides businesses of all sizes with solutions to common business security problems, such as user privacy solutions, firewalls, secure routers, and secure web servers. Our founder, Dave Wreski, started his infosec career at United Parcel Service when the commercial Internet was in its infancy. Dave found a way to use open source to build and install open source security solutions in local businesses that were equivalent to or exceeded the solutions UPS was paying hundreds of thousands of dollars per year for virtually the same protection provided by open source. Using this knowledge, his programming and development background, and the skills learned as the security architect for UPS, Dave built a company around this idea and started selling service and support solutions to small businesses—first in the local area to businesses that needed cheap but effective networking solutions, then online to thousands of businesses worldwide that needed a secure enterprise all-in-one server solution called EnGarde. EnGarde was our first business product, sold to tens of thousands of businesses worldwide, and set the foundation for Guardian Digital's current position. What’s your biggest threat? Our biggest threat is modern cyberattackers, who continue to try to outsmart the latest, most advanced security solutions. Cybersecurity is an ongoing “cat and mouse” game between threat actors and security providers. We are confident we can keep our clients ahead of the latest threats via advanced, layered open-source technology and expert system management, monitoring, and support. HackerNoon : What is your company in 2–5 words? HackerNoon Dave Wreski : The open-source email security provider. Dave Wreski Dave Wreski Why is now the time for your company to exist? Email-borne risk has never been greater. Over 90% of modern cyberattacks begin with a phishing email. Attacks like spear phishing, fileless malware, and zero-day exploits are becoming increasingly difficult to detect and block. Basic email protection, like the security features provided in Microsoft 365 and Google Workspace, is no longer sufficient to make email safe for business. Advanced, multi-layered solutions capable of anticipating and blocking known and emerging threats before they reach the inbox are necessary in this modern threat environment. What do you love about your team, and why are you the ones to solve this problem? As users of and contributors to open-source development, we share the values of transparency and collaboration. Our unique use of open-source development in email security enables us to provide flexible, cost-efficient, and exceptionally secure solutions and offer real-time updates to keep our customers ahead of the latest threats. If you weren’t building your startup, what would you be doing? I would be contributing to Internet security in another way. Before starting Guardian Digital , I was a security engineer at UPS, which I enjoyed and found very rewarding. I also love cooking and writing, so I would likely pursue these passions. Guardian Digital At the moment, how do you measure success? What are your metrics? I measure success in the number of malicious emails our solution blocks, protecting our clients from a potential cyberattack or data breach. I also take pride in retaining our clients, many of whom have been with us for decades, and continuing to acquire new clients worldwide. In a few sentences, what do you offer to whom? We offer threat-ready, fully supported protection against the latest and most advanced email threats for businesses of all sizes in all industries. Our multi-layered security system anticipates and blocks all threats before they reach the inbox, leveraging AI-based detection and expert around-the-clock system monitoring and support. Our managed services extend small businesses’ IT resources and enhance security, delivering a rapid return on investment (ROI). What’s most exciting about your traction to date? We have continued to grow our Product offering and client base over the past 2+ decades. We now offer Security Awareness Training and vCISO email security services. We have also developed an intuitive real-time Dashboard for our solution, giving businesses complete visibility and control over their email security. Where do you think your growth will be next year? We expect to continue acquiring new clients over the next year, as we are investing heavily in our marketing efforts and developing our solution. Our clients come to us for additional protection against today’s advanced threats that go unidentified by default cloud email security in Microsoft 365 and Google Workspace. Our clients are looking to reduce support overhead while bolstering cloud email protection to defend against threats like targeted spear phishing and business email compromise, making our solution ideal for their requirements. Tell us about your first paying customer and revenue expectations over the next year. Guardian Digital's roots are as an open-source Internet security company. It provides businesses of all sizes with solutions to common business security problems, such as user privacy solutions, firewalls, secure routers, and secure web servers. Our founder, Dave Wreski, started his infosec career at United Parcel Service when the commercial Internet was in its infancy. Dave found a way to use open source to build and install open source security solutions in local businesses that were equivalent to or exceeded the solutions UPS was paying hundreds of thousands of dollars per year for virtually the same protection provided by open source. Using this knowledge, his programming and development background, and the skills learned as the security architect for UPS, Dave built a company around this idea and started selling service and support solutions to small businesses—first in the local area to businesses that needed cheap but effective networking solutions, then online to thousands of businesses worldwide that needed a secure enterprise all-in-one server solution called EnGarde. EnGarde was our first business product, sold to tens of thousands of businesses worldwide, and set the foundation for Guardian Digital's current position. What’s your biggest threat? Our biggest threat is modern cyberattackers, who continue to try to outsmart the latest, most advanced security solutions. Cybersecurity is an ongoing “cat and mouse” game between threat actors and security providers. We are confident we can keep our clients ahead of the latest threats via advanced, layered open-source technology and expert system management, monitoring, and support.

"Over 90% of modern cyberattacks begin with a phishing email" says Guardian Digital CEO & Founder

"90% jila jichha pacha ciberataques ukax mä correo electrónico phishing ukampiw qalltawayi" sasaw Guardian Digital CEO & Founder jupax saraki

"Més del 90% dels ciberatacs moderns comencen amb un correu electrònic de pesca", diu el CEO i fundador de Guardian Digital.

„Über 90 % der modernen Cyberangriffe beginnen mit einer Phishing-E-Mail“, sagt CEO und Gründer von Guardian Digital

"Πάνω από το 90% των σύγχρονων επιθέσεων στον κυβερνοχώρο ξεκινούν με ένα ηλεκτρονικό "phishing" λέει ο Διευθύνων Σύμβουλος & Ιδρυτής της Guardian Digital

"Más del 90% de los ciberataques modernos comienzan con un correo electrónico de phishing", afirma el director ejecutivo y fundador de Guardian Digital

"Máis do 90% dos ciberataques modernos comezan cun correo electrónico de phishing", afirma o CEO e fundador de Guardian Digital.

「現代のサイバー攻撃の90%以上はフィッシングメールから始まる」とガーディアンデジタルのCEO兼創設者は語る

"Орчин үеийн кибер халдлагын 90 гаруй хувь нь фишинг цахим шуудангаар эхэлдэг" гэж Guardian Digital-ийн Гүйцэтгэх захирал, үүсгэн байгуулагч хэлэв.

"90% masnin kunan pacha ciberataques kaqmanta huk phishing correo electrónico kaqwan qallarinku" Guardian Digital CEO & Founder nin

„Viac ako 90 % moderných kybernetických útokov začína phishingovým e-mailom,“ hovorí generálny riaditeľ a zakladateľ Guardian Digital

“การโจมตีทางไซเบอร์ในยุคใหม่กว่า 90% เริ่มต้นจากอีเมลฟิชชิ่ง” CEO และผู้ก่อตั้ง Guardian Digital กล่าว

Guardian Digital CEO'su ve Kurucusu, "Modern siber saldırıların %90'ından fazlası kimlik avı e-postasıyla başlıyor" diyor

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