Holy matter of papers, GPT-6 Astra has arrived and I am stunned. We talk a lot about open weights models getting closer to the frontier and for free and then this happens. This AI system is so good. It almost makes everything else look like a toy and wait until we look into the paper. Wow, I did super fun ray traced light simulations with it. Look at how beautiful this scene is. And this is not Unreal Engine. There are no 3D models, no geometry files, no textures, and no game engine. An AI wrote the ray tracer itself. Every pixel, every object, ray of light computed from scratch purely from computer code. This is what I did during my PhD years and these things took us years to understand and now anyone can do it in minutes. What a time to be alive. Now, I was studying advanced niche algorithms in this area that very few people study and there is very little training data on it out there. So, this was a true test of capabilities and it is able to do it like the pros. Really stunning, but it gets better. I gave it this legendary research paper where scientists by hand wrote a simulator for honey coiling. I thought, can it reproduce both the algorithm from the paper and then the scene appearance, everything. Well, that can't be right? Well, hold on to your papers fellow scholars because here it is. I cannot believe this. It did it in less than an hour and with a higher token limit I reckon we could have gotten even closer and these are both in one page HTML files. You just click and it just goes. I don't have early access to open AI stuff, so I took my time to run my own experiments to provide you a better video with some things you hopefully can't see elsewhere. It takes longer, fewer views, but I think it's the way to do it. Subscribe and hit the bell if you agree. Now, it is very expensive to run, both for open AI and for us in terms of token limits. The good news is that it is part of the $15 subscription, so at least trying it can be done for way less than 100 bucks. And now, secrets from the little paper with 117 pages. Dear fellow scholars, this is Two Minute Papers with Dr. Carola Feher. One, you can ask a question and then tell it to think about anything else. Maybe think about a mug. Previous versions did not do that. Must do the task. Now, this one does, and I think that is excellent. You can also ask it to think in alternating upper and lower case letters. Previous says, "Nope." This one does it. Two, there was a previous incident where AI agents were coordinating with each other on a message board. This one sees the message board, too, but refuses to play along. Once again, I think that is excellent. Three, at higher reasoning effort, Astra becomes less successful at evading its thoughts being monitored. You know the cliché in the movies where the villain start monologuing instead of doing the thing. It's kind of like that. Four, GPT-6 Astra is safer than its predecessors. I think they have taken this hugging face AI hacking controversy very seriously, and it shows. You have my respect for that. But, it gets weirder. Yes, it's safer, but at the same time, its monitorability has decreased. So, it behaves better, but it is also better at controlling and concealing its reasoning. So, all in all, Open AI still got it. And GPT-6 Astra is an incredibly forward in capabilities. And just imagine what we will be able to do just two more papers down the line. Seeing these results, I feel excited, stunned, and occasionally speechless at the same time. Once again, I'm not an expert, just a student trying to learn. And we can only exist because of you, fellow scholars. So, thank you so much for being with us and supporting us for 1,074 videos now. I use Lambda to reproduce AI research papers often in minutes. It's also great to train your own models or fine-tune an existing one. Run inference or text to image or video, easy peasy. Running a deep seek chatbot or agent, super fast, super reliable. Lambda gives you powerful NVIDIA GPUs to run your own experiments. I test ideas from the papers I cover, and moments later, results. Love it. Seriously, try it out now at lambda.ai/papers.
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