#大佬观点

What happens when AIs become smarter than us? Why would they keep humans around if given the choice? Our new paper argues that only trying to control AIs is a limited strategy, and that a stable, mutualistic human-AI future may be possible.

My first interview with @sama, Co-Founder of @OpenAI. 0:04 How to start a startup 3:30 Trusting exponentials 4:57 Operating in chaotic environments 6:12 Learning to enjoy painful experiences 8:03 Creating abundant intelligence 11:15 Keeping core suppliers on OpenAI’s timelines 12:10 Invention of the joint-stock company 15:30 The best CEOs aren’t sociopaths 16:46 We are in the singularity 18:09 AI authoritarianism vs liberty 19:24 Texting 300-400 people a day 20:32 Having a small number of deep beliefs about the future 21:41 Critical path 22:25 Thinking about what’s next 23:38 Getting on planes in marginal situations 28:16 Buying lots of compute 30:51 Ambition 34:00 Google shouldn’t have let OpenAI survive 37:54 Having his life shot through a cannon after the launch of ChatGPT 41:20 The growth of Codex 42:02 The Death Star tweet 44:46 Status games and desire to be useful 47:57 Not being ambitious enough on compute investments 50:26 Execution 51:45 Ask for what you want 54:11 First few weeks of OpenAI 55:15 Shutting down Sora to focus on Codex 57:44 Designing beautiful products 59:01 Getting addicted to TikTok 1:01:03 Inventing a new device 1:02:53 Try to get better at your strengths 1:05:57 Masa is an n of 1 1:07:11 Real trends vs fake trends

Conjecture that every complex topological vector bundle on CP^n is algebraic is false. GPT-5.6 Pro found me an example on CP^5 that is not only non-algebraizable, but also with no motivic lift. This also disproves a more recent conjecture by Asok-Fasel-Hopkin.

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models. https://images.nvidia.com/pdf/Open-Weights-and-American-AI-Leadership.pdf

时代变了，过去那么多的规则、约束、文档，感觉现在只会让模型的推理效率和效果变得越来越垃圾，Anthropic说的确实对。 今天决定直接大幅重构所有的文档和规则，清空重写。。。 从此思路不再是用规则约束模型指望它一次写对，而是在前期交给模型更多的思考空间更多的注意力，把更多的限制，加在测试侧，用测试来限制一切。 文档和规则，真的要退环境了。

We removed ~80% of the Claude Code system prompt for our newest models, this is what we've learned about writing system prompts, skills and Claude.MDs for them. http://x.com/i/article/2080703729385512960

Jensen Huang on "distillation" On his new interview with axios, he was asked this question "Should open source model companies be allowed to distill closed models" "Distillation—learning from AI, learning from other people, and learning from other sources of knowledge, is fundamental to intelligence. We are constantly learning from other people. I am learning from you through the questions you are asking, and you are learning from me. All day long, we are learning from one another. AI also has to learn from something. The original AI models, whether they were open or closed, were trained on previously created knowledge from the internet. Now, AI is generating more content than humans. In a few more years, the internet could be 99% AI-generated content, and that content will have been created by some form of AI. As a result, AI systems will constantly be distilling knowledge and intelligence from other AI systems. The fact that AI can learn is a good thing. We want AI systems to be intelligent because a smarter AI can also be a safer AI." ---- From "Axios" YouTube channel, (full video link in comment)

Jensen Huang on "distillation" On his new interview with axios, he was asked this question "Should open source model companies be allowed to distill closed models" "Distillation—learning from AI, learning from other people, and learning from other sources of knowledge, is fundamental to intelligence. We are constantly learning from other people. I am learning from you through the questions you are asking, and you are learning from me. All day long, we are learning from one another. AI also has to learn from something. The original AI models, whether they were open or closed, were trained on previously created knowledge from the internet. Now, AI is generating more content than humans. In a few more years, the internet could be 99% AI-generated content, and that content will have been created by some form of AI. As a result, AI systems will constantly be distilling knowledge and intelligence from other AI systems. The fact that AI can learn is a good thing. We want AI systems to be intelligent because a smarter AI can also be a safer AI." ---- From "Axios" YouTube channel, (full video link in comment)

A billion users can now create and publish websites from their phones with ChatGPT Work. But most people don’t really grasp the full extent of the capabilities here. From your phone, you also have access to: - Cloud computer (15 GB RAM) - Persistent workspace & files - Terminal and code execution - Remote browser - Connected plugins (Slack, Gmail, GitHub, etc.) - All your personal finances, transactions, bank statements - Scheduled tasks - Git clone & PR creation - Build & deploy websites - Create docs, sheets, and slides - Inbox/calendar summarization - Website monitoring & alerts All at your fingertips, using a simple chat interface, no laptop required. All you have to do is switch to the Work tab on your ChatGPT app.

And this comes from a theoretical physicist.

Introducing FLUX 3. One multi-modal model for Image, Video, Audio and Action-Prediction. Creations are truer to life in every kind of style. FLUX 3 Video is now available in early access (link below). Jointly trained in one unified architecture, our model can be extended to predict actions for robotics. See our work with mimic and Audi in the thread.

http://x.com/i/article/2076881344618184704