shitpost maximalist
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Joined January 2022
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It's also easier for people to move on in online spaces, probably something to do with the transient nature of digital experiences and lack of physical context
cat ✨ •̥/ᐠ｡ꞈ｡ᐟ\ retweeted
A few months ago a collaborator and I built a tool which allows hiding encrypted texts inside of LLM texts to avoid censorship or message scanning and for creative misuse of public platforms for encrypted private communication.
You can try it here: garfieldnaruto.com
cat ✨ •̥/ᐠ｡ꞈ｡ᐟ\ retweeted
Anthropic and Irregular went on a press tour with literally apocalyptic language. ROGUE AGENTS. SWARMS. AI DOOM.
But in reality, they told the models to conduct cyberattacks, and that's what the models did.
cat ✨ •̥/ᐠ｡ꞈ｡ᐟ\ retweeted
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.
The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.
The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
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To us, GEN-1.5 represents a new frontier of generality — one that challenges our own understanding of how these models behave when pretrained at a scale of physical interaction data few thought possible without shortcuts. We do not yet see where this asymptotes.
Read more in the full blog: generalistai.com/blog/gen-1.…
wow
In-context learning also crosses the sim-to-real gap, zero-shot. Prompts can be formed entirely from simulated experience (e.g., from a scripted policy, an RL agent, or a human teleoperating a simulated robot) and be used to produce behaviors on a real robot. The model was not trained on the task in either the simulator or the real world.
cat ✨ •̥/ᐠ｡ꞈ｡ᐟ\ retweeted
yes, nonsofic groups exist: this statement is one of many new beautiful results proved by Astra, our next major model.
We're releasing 10 such Astra proofs, complete with lean certificates and CoT walkthroughs for each of them. The results are wide-ranging, from von Neumann algebras (disproof of Connes' Rigidity Conjecture) to better bounds for high dimensional sphere packing, for circuit complexity, for monochromatic triangles in multicolored graphs, and more.
More thoughts here: openai.com/index/ten-advance…
