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As cloud adoption grows and AI usage creates more threats, security blind spots increase. With Cato’s SASE Cloud Platform, FRP Advisory connected 30+ offices and onboarded new companies in hours. See how they strengthened their network security painlessly.

Cato Networks

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12,682,335 次观看 • 11 个月前 •via X (Twitter)

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Dear ICP community, the Internet Computer has now been running strong for 5 years 👏👏👏 Here is a celebratory preview of ICP "cloud engines," the sovereign frontier cloud technology the network shall soon provide from Main points: — Cloud engines enable anyone to spin up their own sovereign frontier cloud. The technology involves an extraordinary inventive step, in which cloud is created from a mathematically secure network of nodes. The nodes run as part of the Internet Computer network ( but are selected and configured by the cloud engine's owner. — The frontier cloud provided by engines is strongly focused on enabling AI agents to build and update online applications and services for us. The world is changing fast, and nearly all new online apps and services are already being built with the help of AI, and thus cloud engines target the future of cloud. — Software hosted on cloud engines is tamperproof, which means that it is immune to infrastructure hacks, because it runs inside a mathematically secure network protocol, rather than on computers directly. This means that AI agents, and those building with them, don't need to have a security team in the loop, or to trust someone else's security team. This is crucial, because in the future, non technical people will demand the freedom to build with full automation — where they just need to issue instructions to AI about what to build, and don't need to worry about anything or anyone else. Of course, apps and services running on engines are also vastly safer from the new breed of hacker being enabled by frontier AI. (The cloud engines themselves are also "tamperproof." Even if a hacker gains physical access to some portion of a cloud engine's nodes, and can make arbitrary changes, the computations and data of the hosted apps and services cannot be corrupted or interrupted so long as the network's fault bounds aren't exceeded. The recent hack of Vercel, a major cloud platform, which gave hackers access to the apps it hosted, provides additional perspective on the importance of this advantage.) — Software hosted on cloud engines is guaranteed to run, so long as a sufficient number of the engine's nodes are running. This means that AI can build applications and services without the need to have a human systems admin team constantly tinkering with the underlying platform to keep it running, which is again crucial, because in the future, non technical people will expect the freedom to use AI to build without the support of others. — New frontier programming language technology, in the form of the Motoko language developed by Caffeine Labs, leverages seminal "orthogonal persistence" technology that unifies program logic and data to deliver further unlocks for AI (Motoko is the first computer language being developed that targets agents that are writing software rather than humans engineers per se). Nowadays, AI can build and update production apps at a prodigious rate, even at the speed of conversation. But it can also make mistakes, and there's a risk that an update it creates might be "lossy" in the sense it causes some transformed data to be lost. Again, in this new world, it's both undesirable and impractical for everyone to have to have a systems admin team on-hand to detect lossy updates and roll them back, but Motoko provides a solution: it can detect new software updates are lossy before they are applied, reducing potentially catastrophic errors by AI to harmless coding retries. — Software hosted on cloud engines is "serverless" but unlike traditional serverless software, directly it directly incorporates data through "orthogonal persistence." Another key purpose is simplify backend software logic and fuel the modeling power of AI by increasing abstraction (sorry for the technical language!!!). Put simply, this enables AI to produce more sophisticated backends, faster, and at dramatically lower costs, as measured by the number AI API tokens consumed during coding. (Tip for the technical: orthogonal persistence is a new paradigm where "the program is the database," and data lives inside program variables, which is possible because it's as if hosted software runs forever in persistent memory). — An expanding database of skills at shall make it possible to develop and directly deploy apps and services to your cloud engines directly from Claude Code, Perplexity, Codex and other AI platforms. Further, your account on can be connected, so that new apps and updates created through conversation automatically appear hosted from your cloud engine. In the future, R&D is going to be very seamless. You converse with AI, and your secure and unstoppable apps or services are created or updated. Cloud engines are designed to directly support this "self-writing cloud" future where we can work hands-free. — Tech sovereignty is becoming a huge issue worldwide, with governments and corporations seeking to create sovereign tech stacks owing to geopolitical tensions. Increasingly, people are realizing that tech provided by foreign nations can come with hidden backdoors and kills switches, from the base platform, right up through hosted apps and services. ICP technology is open source, and those building on ICP using AI own their own source code. When you have the source code, you can verify that there are no backdoors, and when you own the source code thanks to AI, you can update it at will, freeing you from vendor lock-in. But cloud engines take sovereignty much further... — You create a cloud engine by selecting the nodes that will be combined. You can choose the class of nodes used, and their number, but more importantly, you can choose who operates the nodes, and where they are located. Almost any configuration is possible, because the Internet Computer scales the security privileges afforded to hosted software within the network according to configuration (software hosted on cloud engines can directly interoperate with software on other engines and traditional subnets, but base restrictions are applied according to security rules). A cloud engine can be created within a region such as Europe, to comply with regs such as GDPR, or completely within a sovereign state like Switzerland or Pakistan. But cloud engines go further still... — Sovereignty is also about freedom from vendor lock-in. Cloud engines are essentially ICP (Internet Computer Protocol) network configurations, and this means the underlying compute nodes they combine can be swapped out without interrupting their hosted apps and services. This is a big deal. In addition, cloud engines now support nodes that are instances running on Big Tech's clouds, in addition to nodes that are dedicated specialized hardware, as per the Gen I and Gen II nodes that dominate the Internet Computer today. For example, it is possible to have an engine running across different AWS data centers, say, and then reconfigure the engine to run across a mixture of AWS, Google, Azure and Hetzner for even more resilience, without the users of hosted apps and services noticing a thing. That's true freedom. — Sovereign AI is becoming increasingly important too, and cloud engines allow special "AI nodes" to be added to them, so that hosted software can perform inference on hardware provisioned by the owner from a location the owner has selected. Even though the AI nodes are only accessible within the cloud engine, they can still benefit from the forthcoming Internet Intelligence Gateway (IG), which will make it possible to validate inference performed on key frontier open weights LLMs, even when the inference is performed on completely independent AI clouds. When the results of inference are received, this technology can verify that neither the prompt+context (input) nor the inference result (output) have been modified, and that the results were produced by the precise LLM expected. This ensures that AI clouds don't cheat by running inference on cheaper models than are being paid for, and bad actors aren't modifying the inputs or outputs to surreptitiously insert advertising into results, say, or change facts, or insert malware when code is being generated. What's super cool about this technology is the cost of the verification is scalable. A very valuable additional security can be achieved with only 1-2% of extra cost. — Scaling apps and services when they hit capacity limits is another thorny problem that cloud engines help the world address. Engines make scaling possible without rewriting or reconfiguring software. The query workload capacity of hosted software can be horizontally scaled simply by adding new nodes to an engine, and nodes can also be added in geographical proximity to demand. Meanwhile, update workload capacity can first be scaled-up by swapping an engine's nodes out for the next class up, and then when no larger class of node is available, horizontally scaled-out by "splitting" the engine into two, which doubles available capacity. (Technical tip: horizontally scaling update capacity by splitting engines requires multi-canister architectures). — For those who have been following how Caffeine builds apps that can efficiently store large numbers of files, I should mention that apps built on cloud engines will also support the new ICP Blob Storage cloud network (since cloud engines currently have up to about 3 TB of memory, which apps storing large amounts of files can easily exceed). We are also working on allowing blob storage nodes to be added to cloud engines, to enable sovereign mass blob storage within an engine, similarly to how AI nodes can be added currently. — Lastly, but certainly not least, I should mention that cloud engines are multi-blockchain capable, and ready for digital assets, thanks to the clever math at their core. For example, an e-commerce service built on a cloud engine can securely accept and custody stablecoin payments, or a multi-chain DEX could be hosted. Further, engines can support software autonomy (software orchestrated and controlled by other autonomous software, in a decentralized way) and can themselves be orchestrated by SNS technology, and thus run autonomously too. Today, though, the focus is on *mainstream* cloud. This year, the cloud industry will generate approximately one trillion dollars in revenue. That number is already huge, but is expected to grow to two trillion dollars by 2030. After years of continuous development, which have seen more than $500m spent on R&D, the Internet Computer network is now tacking directly toward this mainstream cloud market with cloud engine technology. In their first version, cloud engines are not meant to be a cloud panacea. For example, currently they are not ideal for working with big data. You should use something like DataBricks for that. Cloud engines are carefully targeted at enabling AI to produce traditional online applications and services, including SaaS, in a safer and more productive way, which represents a new market segment with tremendous potential. Of course, DFINITY will continue to work relentlessly to push forward ICP's capabilities, so expect further developments. It's worth mentioning that this cloud segment isn't just about creating new apps and services using AI, it's also about replacing legacy systems and apps built on super expensive SaaS services. Caffeine Labs is working to produce technology (Caffeine Snorkel) that can study an enterprise's legacy systems and app built on SaaS, create replacement systems and apps, and migrate the data, while supporting key stakeholders through the process over email and chat, with full automation. Thus the legacy systems and SaaS markets shall also be addressed by cloud engines. Zooming out, and reasoning in a more metaphysical way, we believe, as we always have, that there is room for a new kind of cloud created by mathematical networks, that provides seminal advances in the fields of security and resilience, as well as true sovereignty and freedom from lock-in. That this same technology, with the help of additional technologies like orthogonal persistence and Motoko, enables AI to build for us without the need for so much oversight, and to create more backend sophistication while consuming fewer AI API tokens, enables ICP to bring game-changing advances to the world. Cloud engines will work synergistically with the Intelligence Gateway, which will enable apps and services running on engines to seamlessly leverage AI, wherever that AI is running, while providing verifiability at extremely low cost for open weights frontier models. We believe that cloud engines represent an inflection point in the storied history of the Internet Computer project, and I'm very proud to be sharing the details with you on the network's fifth birthday 💪 I'll be back with more news soon!!

Dear ICP community, the Internet Computer has now been running strong for 5 years 👏👏👏 Here is a celebratory preview of ICP "cloud engines," the sovereign frontier cloud technology the network shall soon provide from Main points: — Cloud engines enable anyone to spin up their own sovereign frontier cloud. The technology involves an extraordinary inventive step, in which cloud is created from a mathematically secure network of nodes. The nodes run as part of the Internet Computer network ( but are selected and configured by the cloud engine's owner. — The frontier cloud provided by engines is strongly focused on enabling AI agents to build and update online applications and services for us. The world is changing fast, and nearly all new online apps and services are already being built with the help of AI, and thus cloud engines target the future of cloud. — Software hosted on cloud engines is tamperproof, which means that it is immune to infrastructure hacks, because it runs inside a mathematically secure network protocol, rather than on computers directly. This means that AI agents, and those building with them, don't need to have a security team in the loop, or to trust someone else's security team. This is crucial, because in the future, non technical people will demand the freedom to build with full automation — where they just need to issue instructions to AI about what to build, and don't need to worry about anything or anyone else. Of course, apps and services running on engines are also vastly safer from the new breed of hacker being enabled by frontier AI. (The cloud engines themselves are also "tamperproof." Even if a hacker gains physical access to some portion of a cloud engine's nodes, and can make arbitrary changes, the computations and data of the hosted apps and services cannot be corrupted or interrupted so long as the network's fault bounds aren't exceeded. The recent hack of Vercel, a major cloud platform, which gave hackers access to the apps it hosted, provides additional perspective on the importance of this advantage.) — Software hosted on cloud engines is guaranteed to run, so long as a sufficient number of the engine's nodes are running. This means that AI can build applications and services without the need to have a human systems admin team constantly tinkering with the underlying platform to keep it running, which is again crucial, because in the future, non technical people will expect the freedom to use AI to build without the support of others. — New frontier programming language technology, in the form of the Motoko language developed by Caffeine Labs, leverages seminal "orthogonal persistence" technology that unifies program logic and data to deliver further unlocks for AI (Motoko is the first computer language being developed that targets agents that are writing software rather than humans engineers per se). Nowadays, AI can build and update production apps at a prodigious rate, even at the speed of conversation. But it can also make mistakes, and there's a risk that an update it creates might be "lossy" in the sense it causes some transformed data to be lost. Again, in this new world, it's both undesirable and impractical for everyone to have to have a systems admin team on-hand to detect lossy updates and roll them back, but Motoko provides a solution: it can detect new software updates are lossy before they are applied, reducing potentially catastrophic errors by AI to harmless coding retries. — Software hosted on cloud engines is "serverless" but unlike traditional serverless software, directly it directly incorporates data through "orthogonal persistence." Another key purpose is simplify backend software logic and fuel the modeling power of AI by increasing abstraction (sorry for the technical language!!!). Put simply, this enables AI to produce more sophisticated backends, faster, and at dramatically lower costs, as measured by the number AI API tokens consumed during coding. (Tip for the technical: orthogonal persistence is a new paradigm where "the program is the database," and data lives inside program variables, which is possible because it's as if hosted software runs forever in persistent memory). — An expanding database of skills at shall make it possible to develop and directly deploy apps and services to your cloud engines directly from Claude Code, Perplexity, Codex and other AI platforms. Further, your account on can be connected, so that new apps and updates created through conversation automatically appear hosted from your cloud engine. In the future, R&D is going to be very seamless. You converse with AI, and your secure and unstoppable apps or services are created or updated. Cloud engines are designed to directly support this "self-writing cloud" future where we can work hands-free. — Tech sovereignty is becoming a huge issue worldwide, with governments and corporations seeking to create sovereign tech stacks owing to geopolitical tensions. Increasingly, people are realizing that tech provided by foreign nations can come with hidden backdoors and kills switches, from the base platform, right up through hosted apps and services. ICP technology is open source, and those building on ICP using AI own their own source code. When you have the source code, you can verify that there are no backdoors, and when you own the source code thanks to AI, you can update it at will, freeing you from vendor lock-in. But cloud engines take sovereignty much further... — You create a cloud engine by selecting the nodes that will be combined. You can choose the class of nodes used, and their number, but more importantly, you can choose who operates the nodes, and where they are located. Almost any configuration is possible, because the Internet Computer scales the security privileges afforded to hosted software within the network according to configuration (software hosted on cloud engines can directly interoperate with software on other engines and traditional subnets, but base restrictions are applied according to security rules). A cloud engine can be created within a region such as Europe, to comply with regs such as GDPR, or completely within a sovereign state like Switzerland or Pakistan. But cloud engines go further still... — Sovereignty is also about freedom from vendor lock-in. Cloud engines are essentially ICP (Internet Computer Protocol) network configurations, and this means the underlying compute nodes they combine can be swapped out without interrupting their hosted apps and services. This is a big deal. In addition, cloud engines now support nodes that are instances running on Big Tech's clouds, in addition to nodes that are dedicated specialized hardware, as per the Gen I and Gen II nodes that dominate the Internet Computer today. For example, it is possible to have an engine running across different AWS data centers, say, and then reconfigure the engine to run across a mixture of AWS, Google, Azure and Hetzner for even more resilience, without the users of hosted apps and services noticing a thing. That's true freedom. — Sovereign AI is becoming increasingly important too, and cloud engines allow special "AI nodes" to be added to them, so that hosted software can perform inference on hardware provisioned by the owner from a location the owner has selected. Even though the AI nodes are only accessible within the cloud engine, they can still benefit from the forthcoming Internet Intelligence Gateway (IG), which will make it possible to validate inference performed on key frontier open weights LLMs, even when the inference is performed on completely independent AI clouds. When the results of inference are received, this technology can verify that neither the prompt+context (input) nor the inference result (output) have been modified, and that the results were produced by the precise LLM expected. This ensures that AI clouds don't cheat by running inference on cheaper models than are being paid for, and bad actors aren't modifying the inputs or outputs to surreptitiously insert advertising into results, say, or change facts, or insert malware when code is being generated. What's super cool about this technology is the cost of the verification is scalable. A very valuable additional security can be achieved with only 1-2% of extra cost. — Scaling apps and services when they hit capacity limits is another thorny problem that cloud engines help the world address. Engines make scaling possible without rewriting or reconfiguring software. The query workload capacity of hosted software can be horizontally scaled simply by adding new nodes to an engine, and nodes can also be added in geographical proximity to demand. Meanwhile, update workload capacity can first be scaled-up by swapping an engine's nodes out for the next class up, and then when no larger class of node is available, horizontally scaled-out by "splitting" the engine into two, which doubles available capacity. (Technical tip: horizontally scaling update capacity by splitting engines requires multi-canister architectures). — For those who have been following how Caffeine builds apps that can efficiently store large numbers of files, I should mention that apps built on cloud engines will also support the new ICP Blob Storage cloud network (since cloud engines currently have up to about 3 TB of memory, which apps storing large amounts of files can easily exceed). We are also working on allowing blob storage nodes to be added to cloud engines, to enable sovereign mass blob storage within an engine, similarly to how AI nodes can be added currently. — Lastly, but certainly not least, I should mention that cloud engines are multi-blockchain capable, and ready for digital assets, thanks to the clever math at their core. For example, an e-commerce service built on a cloud engine can securely accept and custody stablecoin payments, or a multi-chain DEX could be hosted. Further, engines can support software autonomy (software orchestrated and controlled by other autonomous software, in a decentralized way) and can themselves be orchestrated by SNS technology, and thus run autonomously too. Today, though, the focus is on mainstream cloud. This year, the cloud industry will generate approximately one trillion dollars in revenue. That number is already huge, but is expected to grow to two trillion dollars by 2030. After years of continuous development, which have seen more than $500m spent on R&D, the Internet Computer network is now tacking directly toward this mainstream cloud market with cloud engine technology. In their first version, cloud engines are not meant to be a cloud panacea. For example, currently they are not ideal for working with big data. You should use something like DataBricks for that. Cloud engines are carefully targeted at enabling AI to produce traditional online applications and services, including SaaS, in a safer and more productive way, which represents a new market segment with tremendous potential. Of course, DFINITY will continue to work relentlessly to push forward ICP's capabilities, so expect further developments. It's worth mentioning that this cloud segment isn't just about creating new apps and services using AI, it's also about replacing legacy systems and apps built on super expensive SaaS services. Caffeine Labs is working to produce technology (Caffeine Snorkel) that can study an enterprise's legacy systems and app built on SaaS, create replacement systems and apps, and migrate the data, while supporting key stakeholders through the process over email and chat, with full automation. Thus the legacy systems and SaaS markets shall also be addressed by cloud engines. Zooming out, and reasoning in a more metaphysical way, we believe, as we always have, that there is room for a new kind of cloud created by mathematical networks, that provides seminal advances in the fields of security and resilience, as well as true sovereignty and freedom from lock-in. That this same technology, with the help of additional technologies like orthogonal persistence and Motoko, enables AI to build for us without the need for so much oversight, and to create more backend sophistication while consuming fewer AI API tokens, enables ICP to bring game-changing advances to the world. Cloud engines will work synergistically with the Intelligence Gateway, which will enable apps and services running on engines to seamlessly leverage AI, wherever that AI is running, while providing verifiability at extremely low cost for open weights frontier models. We believe that cloud engines represent an inflection point in the storied history of the Internet Computer project, and I'm very proud to be sharing the details with you on the network's fifth birthday 💪 I'll be back with more news soon!!

dom | icp

308,176 次观看 • 4 个月前

20 companies that will dominate the next decade: 1/ Nebius $NBIS is redefining cloud computing for the age of AI, offering an infrastructure platform designed specifically for building and running AI models. Nebius services will help both large and small AI companies build innovative AI solutions in robotics, healthcare, finance, military, agriculture, drug discovery, material sciences, and many more. The company just signed a massive 5-year $17.4B contract with Microsoft. It is currently expanding the data center business in: - Finland - Iceland - New Jersey - Alabama - UK - France - Israel

20 companies that will dominate the next decade: 1/ Nebius $NBIS is redefining cloud computing for the age of AI, offering an infrastructure platform designed specifically for building and running AI models. Nebius services will help both large and small AI companies build innovative AI solutions in robotics, healthcare, finance, military, agriculture, drug discovery, material sciences, and many more. The company just signed a massive 5-year $17.4B contract with Microsoft. It is currently expanding the data center business in: - Finland - Iceland - New Jersey - Alabama - UK - France - Israel

Ray Myers

125,954 次观看 • 11 个月前

Over the past fiscal year, our customers and partners have driven pragmatic outcomes by implementing AI-first strategies across their organizations. With AI Transformation as their framework, we helped them reinvent employee experiences, reinvent customer engagement, reshape business processes, and bend the curve on innovation for their people, businesses and industries. Check out my latest blog to read several customer and partner stories from the past quarter reflecting the success we have seen broadly in FY25, and what we can achieve together with an approach grounded in AI business solutions, cloud and AI platforms, and security.

Over the past fiscal year, our customers and partners have driven pragmatic outcomes by implementing AI-first strategies across their organizations. With AI Transformation as their framework, we helped them reinvent employee experiences, reinvent customer engagement, reshape business processes, and bend the curve on innovation for their people, businesses and industries. Check out my latest blog to read several customer and partner stories from the past quarter reflecting the success we have seen broadly in FY25, and what we can achieve together with an approach grounded in AI business solutions, cloud and AI platforms, and security.

Judson Althoff

53,517 次观看 • 1 年前

Shachar Hirshberg and Dan Shiebler make offers to new hires within 48 hours of their first conversation. They’re building an AI-native security company, Artemis Security, that battles threats that move at machine speed (which, for AI-driven attacks, is often in seconds). So speed is naturally an important operating principle for them. They’ve assembled a team of 30 people in NYC in under seven months, which they’ve done by front-loading references, bringing candidates in for lunch with the full team, and managing most of the recruiting process directly themselves. Engineering velocity is often a hiring problem in this market, and these guys have figured out a system that lets their recruiting process move as fast as their product. Their engineers run multiple Claude Code instances simultaneously to ship features in parallel, nearly all of their code is AI-generated, and they’ve outrun their original product roadmap by seven months. But they still haven’t managed to find any candidates who use AI as heavily as the Artemis team does. That isn’t a dealbreaker for them, though — they’re only looking for people who want to learn, and they train everyone who joins to ship as fast as the founders do. Fresh off their $70M fundraise and launch out of stealth, I sat down with Shachar and Dan on In Depth to find out how they’re pulling all of this off. We also dig into: -Why they’re on a texting basis with every CISO they sign -Why AI is a death knell for legacy security platforms -How they maintain decision-making velocity in their relationship as co-founders

Shachar Hirshberg and Dan Shiebler make offers to new hires within 48 hours of their first conversation. They’re building an AI-native security company, Artemis Security, that battles threats that move at machine speed (which, for AI-driven attacks, is often in seconds). So speed is naturally an important operating principle for them. They’ve assembled a team of 30 people in NYC in under seven months, which they’ve done by front-loading references, bringing candidates in for lunch with the full team, and managing most of the recruiting process directly themselves. Engineering velocity is often a hiring problem in this market, and these guys have figured out a system that lets their recruiting process move as fast as their product. Their engineers run multiple Claude Code instances simultaneously to ship features in parallel, nearly all of their code is AI-generated, and they’ve outrun their original product roadmap by seven months. But they still haven’t managed to find any candidates who use AI as heavily as the Artemis team does. That isn’t a dealbreaker for them, though — they’re only looking for people who want to learn, and they train everyone who joins to ship as fast as the founders do. Fresh off their $70M fundraise and launch out of stealth, I sat down with Shachar and Dan on In Depth to find out how they’re pulling all of this off. We also dig into: -Why they’re on a texting basis with every CISO they sign -Why AI is a death knell for legacy security platforms -How they maintain decision-making velocity in their relationship as co-founders

Josh Kopelman

12,595 次观看 • 4 个月前

🔍 We're entering a new era of vulnerability discovery, where AI and human ingenuity come together to unlock new possibilities. Over the past five months, AI hasn’t replaced researchers—it’s amplified them. Together, we’re achieving new levels of speed, scale, and precision in offensive security. With these changes, HackerOne is reshaping how collaboration drives impact in security testing. 📽️ Hear from our co-founder Michiel Prins on what this means for the future of our platform and our community. 🔗 Read Michiel's blog for more: #OffensiveSecurity #AIinCybersecurity #togetherwehitharder #AI #cybersecurity

🔍 We're entering a new era of vulnerability discovery, where AI and human ingenuity come together to unlock new possibilities. Over the past five months, AI hasn’t replaced researchers—it’s amplified them. Together, we’re achieving new levels of speed, scale, and precision in offensive security. With these changes, HackerOne is reshaping how collaboration drives impact in security testing. 📽️ Hear from our co-founder Michiel Prins on what this means for the future of our platform and our community. 🔗 Read Michiel's blog for more: #OffensiveSecurity #AIinCybersecurity #togetherwehitharder #AI #cybersecurity

HackerOne

26,357 次观看 • 1 年前

🚨 EXCITING News! Typeless is now officially HIPAA compliant! 🎉 🔒 Privacy isn’t just a feature for #Typeless; it’s their foundation. With zero data retention in the cloud, no AI training on user data, and history stored purely on-device, Typeless is setting the highest standard for data security. Why does HIPAA (Health Insurance Portability and Accountability Act) compliance matter? — It means Typeless has passed one of the strictest data protection standards in the U.S., ensuring that they handle protected health information (PHI) with the highest standards of privacy and security required in the healthcare industry. And this is just the beginning! They are also working towards SOC 2, ISO 27001, and GDPR compliance. 🔗 Visit to learn more about their commitment to privacy and security at their Trust Center. Watch as I used Typeless ask anything feature to enquire everything about HIPAA compliance. 👇

🚨 EXCITING News! Typeless is now officially HIPAA compliant! 🎉 🔒 Privacy isn’t just a feature for #Typeless; it’s their foundation. With zero data retention in the cloud, no AI training on user data, and history stored purely on-device, Typeless is setting the highest standard for data security. Why does HIPAA (Health Insurance Portability and Accountability Act) compliance matter? — It means Typeless has passed one of the strictest data protection standards in the U.S., ensuring that they handle protected health information (PHI) with the highest standards of privacy and security required in the healthcare industry. And this is just the beginning! They are also working towards SOC 2, ISO 27001, and GDPR compliance. 🔗 Visit to learn more about their commitment to privacy and security at their Trust Center. Watch as I used Typeless ask anything feature to enquire everything about HIPAA compliance. 👇

Wesley

227,596 次观看 • 6 个月前

Here’s No Moat, my roguelike deckbuilding game created with Astra in 2 hours. Basically, you’re an AI founder and your job is to recruit teammates, build your deck, and fight everything from copycats to bugs to massive cloud bills. It has 3 full stages and boss battles too! 📌 Play it here: See how I built it and 3 other games in my new tutorial:

Here’s No Moat, my roguelike deckbuilding game created with Astra in 2 hours. Basically, you’re an AI founder and your job is to recruit teammates, build your deck, and fight everything from copycats to bugs to massive cloud bills. It has 3 full stages and boss battles too! 📌 Play it here: See how I built it and 3 other games in my new tutorial:

Peter Yang

34,463 次观看 • 4 天前