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Cyber defense is entering the superintelligence era. ⚡ Introducing the CrowdStrike Cyber Superintelligence Lab, the first frontier AI research organization built for cyberdefense and AI safety. The Lab delivers CrowdStrike SafeMind, a family of purpose-built security models and harnesses. SafeMind runs as one system designed to deliver AI safety:... show more

CrowdStrike

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NVIDIA and CrowdStrike are advancing agentic cyber defense with SafeMind, a new family of security models and harnesses built on NVIDIA Nemotron. Introduced at Fal.Con, SafeMind is customized with CrowdStrike threat data to support triage and detection generation for cyber defense.

NVIDIA and CrowdStrike are advancing agentic cyber defense with SafeMind, a new family of security models and harnesses built on NVIDIA Nemotron. Introduced at Fal.Con, SafeMind is customized with CrowdStrike threat data to support triage and detection generation for cyber defense.

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$CRWD and $NVDA just launched SafeMind to bring frontier AI to cyber defense with George Kurtz saying “the attackers had frontier AI and the defenders didn’t. That changes now.” SafeMind is CrowdStrike’s answer using autonomous red and blue agents to continuously attack, learn and improve defenses at machine speed.

$CRWD and $NVDA just launched SafeMind to bring frontier AI to cyber defense with George Kurtz saying “the attackers had frontier AI and the defenders didn’t. That changes now.” SafeMind is CrowdStrike’s answer using autonomous red and blue agents to continuously attack, learn and improve defenses at machine speed.

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Introducing Ricursive Intelligence, a frontier AI lab enabling a recursive self-improvement loop between AI and the chips that fuel it. Learn more at

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ANTHROPIC'S NEW AI MODEL "MYTHOS" IS SO POWERFUL THE COMPANY WON'T RELEASE IT TO THE PUBLIC YET Instead, they're giving it to 11 companies first through "Project Glasswing" to find cybersecurity vulnerabilities before bad actors can. The partners: Amazon, Apple, Broadcom, Nvidia, Google, and others. The model wasn't built for cybersecurity. It was built to be an automated AI researcher, an AI that helps build better AI. But those same capabilities make it a serious tool for both offensive and defensive cyber operations. OpenAI reportedly has a similar model codenamed "SPU" going through the same slow rollout process. Palisade Research: "Anthropic is a little ahead, but not overwhelmingly ahead. They don't necessarily have a permanent moat here."

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TARS Research is now live, the first AI research lab built entirely for Solana. Research is where real innovation begins. If TARS is to lead AI infrastructure onchain, it must define the frameworks others will follow. TARS Research is built for that: > A dedicated lab advancing agent architecture, tokenization, and onchain intelligence > Powering everything from the AI Marketplace to Sona > Focused on setting standards, not following them AI on Solana starts here.

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Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (Bryan Catanzaro). NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed

Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (Bryan Catanzaro). NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed

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Introducing Paygent.01 The quickest way to spin up an AI Agent that moves real money. Literally just one API key is need and you have your own personal AI Agent that can. - Pay your bills - Send money to that one relative - Go out and ask for money Fully open-source. Built using the AI SDK and Payman.

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