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The performance limits in every field of engineering are determined by material properties Radical AI led by Joseph Krause is developing a closed-loop robotic system with AI foundation models for material science To drive humanity farther, faster, more durably than ever

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28,407 просмотров • 2 месяцев назад •via X (Twitter)

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We’re thrilled to announce that we've raised a $36M Series A led by martin_casado at a16z to advance the future of AI software engineering, bringing our total funding to $45 million. We’re also introducing functions — a flexible primitive for building with foundation models.
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We’re thrilled to announce that we've raised a $36M Series A led by martin_casado at a16z to advance the future of AI software engineering, bringing our total funding to $45 million. We’re also introducing functions — a flexible primitive for building with foundation models.

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Radical AI is redefining the boundaries of materials science. As we prepare to open a 45,000-square-foot lab in the Brooklyn Navy Yard, we’re set to even further accelerate the discovery of next-generation materials that will shape our future. Thank you Nathan Labenz for inviting Joseph Krause and JC to share how Radical is pursuing the holy grail of materials science intelligence.
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Radical AI is redefining the boundaries of materials science. As we prepare to open a 45,000-square-foot lab in the Brooklyn Navy Yard, we’re set to even further accelerate the discovery of next-generation materials that will shape our future. Thank you Nathan Labenz for inviting Joseph Krause and JC to share how Radical is pursuing the holy grail of materials science intelligence.

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Introducing DeepProve—Lagrange’s zkML Library—a breakthrough in verifiable AI inference. We can now verify AI decisions instead of blindly trusting black-box models. And we can do it up to 158x faster than ever before. The future of AI is ZK. The future of humanity is Lagrange: 🧵
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Introducing DeepProve—Lagrange’s zkML Library—a breakthrough in verifiable AI inference. We can now verify AI decisions instead of blindly trusting black-box models. And we can do it up to 158x faster than ever before. The future of AI is ZK. The future of humanity is Lagrange: 🧵

LAGRANGE

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$META is betting on $AMD for AI inference. As AI models become more commoditized, total cost of ownership for token generation matters more than ever. $AMD GPUs are far more cost-efficient than $NVDA for inference. With 3.5B daily users ready to use its AI models, $META is going all-in on $AMD
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$META is betting on $AMD for AI inference. As AI models become more commoditized, total cost of ownership for token generation matters more than ever. $AMD GPUs are far more cost-efficient than $NVDA for inference. With 3.5B daily users ready to use its AI models, $META is going all-in on $AMD

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20,558 просмотров • 5 месяцев назад

🚀 Introducing the AI Alliance: Shaping the Future of AI and Data Security We’re proud to unveil the AI Alliance, a collaboration of expert teams from ARC, DMAIL.AI and XAlpha AI Agent to name a few, who are working together to drive innovation in AI and data security. By leveraging the power of LLMs (Large Language Models), we’re building the foundation for future AI applications. 🌐✨ 💡 This is just the beginning! Stay tuned for more insights and updates from this recently held AI Alliance AMA. We’ll dive deeper into how these teams are helping to shape the future of AI.
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🚀 Introducing the AI Alliance: Shaping the Future of AI and Data Security We’re proud to unveil the AI Alliance, a collaboration of expert teams from ARC, DMAIL.AI and XAlpha AI Agent to name a few, who are working together to drive innovation in AI and data security. By leveraging the power of LLMs (Large Language Models), we’re building the foundation for future AI applications. 🌐✨ 💡 This is just the beginning! Stay tuned for more insights and updates from this recently held AI Alliance AMA. We’ll dive deeper into how these teams are helping to shape the future of AI.

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Hugging Face CEO Clément Delangue regrets that AI is less open, collaborative and science-driven than it was 3-4 years ago, with research and models becoming more closed and commercial, and he says this is hindering progress in the field
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We've reinvented computing... A thousand CUDA-X libraries help developers make breakthroughs in every field of science and engineering." — Jensen Huang From cuOpt for decision optimization to Parabricks for genomics, the foundation of every modern breakthrough is a "beautiful algorithm".
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We've reinvented computing... A thousand CUDA-X libraries help developers make breakthroughs in every field of science and engineering." — Jensen Huang From cuOpt for decision optimization to Parabricks for genomics, the foundation of every modern breakthrough is a "beautiful algorithm".

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Music is not a noun it is a verb. To music is to take part, in any capacity, in a musical performance, whether by performing, by listening…by providing material for performance (composing)—Christopher Small. You go ARR, keep providing for the concert halls of the world!
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Music is not a noun it is a verb. To music is to take part, in any capacity, in a musical performance, whether by performing, by listening…by providing material for performance (composing)—Christopher Small. You go ARR, keep providing for the concert halls of the world!

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Anthropic co-founder Jack Clark says the AI frontier is about to cross a much stranger line than coding assistants. "My prediction is by the end of 2028, it's more likely than not that we have an AI system where you would be able to say to it, 'Make a better version of yourself.' And it just goes off and does that completely autonomously." The reason: models have moved from basic coding into "the production of science itself" and the "unglamorous but fundamental engineering work" behind large-scale R&D. "An AI system that can build itself [has] big implications, and we'd like to start thinking about it now." That is the actual agent threshold: not demos, not chat UX, but AI becoming part of the loop that improves AI.
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“Members of Congress are generalists… you don’t have to understand every technical detail to legislate,” said Rep. Ted Lieu (D-CA), Vice Chair of the House Democratic Caucus, at The Hill’s AI in America Summit. He noted that his background in computer science helps him read technical material more easily and recognize a critical reality of AI systems today: their growing complexity and the limits of our understanding of how they reach decisions. Explore more: #TheHillTech #AIPolicy #TechLeadership
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“Members of Congress are generalists… you don’t have to understand every technical detail to legislate,” said Rep. Ted Lieu (D-CA), Vice Chair of the House Democratic Caucus, at The Hill’s AI in America Summit. He noted that his background in computer science helps him read technical material more easily and recognize a critical reality of AI systems today: their growing complexity and the limits of our understanding of how they reach decisions. Explore more: #TheHillTech #AIPolicy #TechLeadership

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Microsoft CEO, Satya Nadella: “At Microsoft, more than 60% of our code is already written by AI agents. We are planning to scale it to 2–20 million agents, all running in a loop.” In this 1-hour talk, Microsoft’s CEO discusses the future of agentic AI with the LinkedIn founder. Watch it today, then read how to build a self-improving agentic system in the article below.
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Microsoft CEO, Satya Nadella: “At Microsoft, more than 60% of our code is already written by AI agents. We are planning to scale it to 2–20 million agents, all running in a loop.” In this 1-hour talk, Microsoft’s CEO discusses the future of agentic AI with the LinkedIn founder. Watch it today, then read how to build a self-improving agentic system in the article below.

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Jensen Huang just said the most dangerous thing about AI that no one is sitting with. Huang: “AI basically does most of our coding. And yet we’re hiring more engineers than ever. We have more challenges than ever. We have bigger dreams than ever.” Every engineer at NVIDIA uses AI. AI writes most of their code. This is the company building the infrastructure behind every major AI system on Earth. Closer to this technology than any organization alive. They’re hiring more people. Not fewer. Every conversation about AI is built around subtraction. Fewer jobs. Fewer workers. Fewer humans in the loop. Jensen just told you the opposite is true. Huang: “Suppose we infused AI into this country, and as a result of that, we are doing things faster than ever before. Our ambition is greater than ever before. Our expectations are greater than ever before. How is that a bad condition for our country?” He’s not defending AI. He’s describing what happens inside the organizations that actually use it. It doesn’t make them leaner. It makes them hungrier. More ambition. More speed. More appetite for problems no one would have touched five years ago. The car didn’t make humans travel less. The internet didn’t make humans communicate less. No tool in human history has ever made humans want less. AI will not be the exception. Huang: “Prior to that, it’s been incredible but not useful. Now it’s useful and incredible.” Six months. That’s how fast AI crossed from impressive demo to daily weapon. The companies that adopted it didn’t shrink. They expanded. Compressed timelines. Started chasing problems they never would have attempted. The companies that ignored it stayed exactly where they were. That gap compounds. Every day a company uses AI to move faster, it learns something the one standing still never will. That knowledge stacks. That speed stacks. That ambition stacks. Jensen isn’t warning about a future where machines take your job. He’s describing a present where the companies using AI are becoming so fast and so hungry that standing still is already fatal. By the time you notice, it’s over. You were never going to be replaced by AI. You were going to be erased by someone it made hungrier than you.
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Jensen Huang just said the most dangerous thing about AI that no one is sitting with. Huang: “AI basically does most of our coding. And yet we’re hiring more engineers than ever. We have more challenges than ever. We have bigger dreams than ever.” Every engineer at NVIDIA uses AI. AI writes most of their code. This is the company building the infrastructure behind every major AI system on Earth. Closer to this technology than any organization alive. They’re hiring more people. Not fewer. Every conversation about AI is built around subtraction. Fewer jobs. Fewer workers. Fewer humans in the loop. Jensen just told you the opposite is true. Huang: “Suppose we infused AI into this country, and as a result of that, we are doing things faster than ever before. Our ambition is greater than ever before. Our expectations are greater than ever before. How is that a bad condition for our country?” He’s not defending AI. He’s describing what happens inside the organizations that actually use it. It doesn’t make them leaner. It makes them hungrier. More ambition. More speed. More appetite for problems no one would have touched five years ago. The car didn’t make humans travel less. The internet didn’t make humans communicate less. No tool in human history has ever made humans want less. AI will not be the exception. Huang: “Prior to that, it’s been incredible but not useful. Now it’s useful and incredible.” Six months. That’s how fast AI crossed from impressive demo to daily weapon. The companies that adopted it didn’t shrink. They expanded. Compressed timelines. Started chasing problems they never would have attempted. The companies that ignored it stayed exactly where they were. That gap compounds. Every day a company uses AI to move faster, it learns something the one standing still never will. That knowledge stacks. That speed stacks. That ambition stacks. Jensen isn’t warning about a future where machines take your job. He’s describing a present where the companies using AI are becoming so fast and so hungry that standing still is already fatal. By the time you notice, it’s over. You were never going to be replaced by AI. You were going to be erased by someone it made hungrier than you.

Dustin

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CyrilXBT

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As India prepares to host the India AI Impact Summit 2026, PM Narendra Modi Ji chaired a roundtable with Indian AI start-ups advancing responsible, inclusive, and globally relevant AI innovations. ➡️ These 12 start-ups are working in a diverse set of areas including e-commerce, marketing, engineering simulations, material research, healthcare, medical research and more.
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As India prepares to host the India AI Impact Summit 2026, PM Narendra Modi Ji chaired a roundtable with Indian AI start-ups advancing responsible, inclusive, and globally relevant AI innovations. ➡️ These 12 start-ups are working in a diverse set of areas including e-commerce, marketing, engineering simulations, material research, healthcare, medical research and more.

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I made an AI data science team with Python. I'm excited to share my new project, the AI Data Science Team, a Python package for creating AI co-pilots and agents to assist in common data science tasks. I walk you through the GitHub page, showcasing the progress and potential of this project. I'll explain how these agents can streamline tasks like code generation and modeling pipeline creation, making data science projects more efficient. Introduction to AI Data Science Team Project Integrating Human-in-the-Loop Example: Accessing Agents for Feature Engineering Setting up Feature Engineering Agent Code On GitHub: Python AI-Tips Newsletter (stay updated as I build this project in the open):

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1/3 Zesh AI Layer is an advanced AI solution on SUI, powered by a library of data models that act as its engine. Zesh layer is designed for building cutting-edge AI products, giving every project on Zesh access to its expansive and ever-evolving library of data models. As more products, users, and activity takes place in the Zesh ecosystem, the data model library continually learns and grows. This is AI that evolves with you.
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1/3 Zesh AI Layer is an advanced AI solution on SUI, powered by a library of data models that act as its engine. Zesh layer is designed for building cutting-edge AI products, giving every project on Zesh access to its expansive and ever-evolving library of data models. As more products, users, and activity takes place in the Zesh ecosystem, the data model library continually learns and grows. This is AI that evolves with you.

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Fuser launches today. Backed by a $2M pre-seed led by Collab+Currency, we’re carving a new path for how creatives interface with AI. Sometimes it feels like how we use AI — where it lives, what it’s for — has already been decided for us. But that isn’t true. In fact, it’s more in flux than ever. That’s why we built Fuser: a creative workspace where ideas and the experience of using AI evolve together. Every model. Every medium. One canvas.
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Fuser launches today. Backed by a $2M pre-seed led by Collab+Currency, we’re carving a new path for how creatives interface with AI. Sometimes it feels like how we use AI — where it lives, what it’s for — has already been decided for us. But that isn’t true. In fact, it’s more in flux than ever. That’s why we built Fuser: a creative workspace where ideas and the experience of using AI evolve together. Every model. Every medium. One canvas.

Fuser

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we're more determined than ever to ensure financial services are accessible to all. Your right to participate in the economy is precisely that - a right... covered by @TheBlock__
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we're more determined than ever to ensure financial services are accessible to all. Your right to participate in the economy is precisely that - a right... covered by @TheBlock__

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