axios.com/2026/04/09/openai-… [Translated from EN to English]
→ View original post on X — @kimmonismus, 2026-04-09 09:35 UTC
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axios.com/2026/04/09/openai-… [Translated from EN to English]
→ View original post on X — @kimmonismus, 2026-04-09 09:35 UTC

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Big update: OpenAI developed its own ChatGPT-"Mythos" and will also not roll it out publicly, via Axios OpenAI is planning a limited, staggered rollout of a new model with advanced cybersecurity capabilities, mirroring Anthropic's restricted release of its Mythos Preview to a small group of vetted companies. More and more AI models are now capable enough at autonomous hacking that their makers are treating releases like responsible vulnerability disclosure. [Translated from EN to English]
→ View original post on X — @kimmonismus, 2026-04-09 09:35 UTC
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Hey @AnthropicAI , its been 2 days sind your mythos reveal. Have you tested it enough for safety now? May we have it too, please? 🙂
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Having a model like Gemma 4, which is perfectly adequate for everyday use in many cases, runs locally, is free, and secure, still feels unreal. We have a very good AI that costs nothing, uses hardly any power, and is always there. I think that's simply fantastic. The only problem is: 99% of people have never even heard of it.
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Holy: OpenAI researchers report solving five (!) additional Erdős problems using an internal model, showcasing AI’s growing strength in deep mathematical reasoning.
— Chubby♨️ (@kimmonismus) 9 avril 2026
Excitement for spud increases day by day. https://t.co/xss1rxAm6Z
Holy: OpenAI researchers report solving five (!) additional Erdős problems using an internal model, showcasing AI’s growing strength in deep mathematical reasoning. Excitement for spud increases day by day. Mehtaab Sawhney (@mehtaab_sawhney) We’ve just released another paper solving five further Erdős problems with an internal model at OpenAI: arxiv.org/abs/2604.06609. Several of the proofs were especially enjoyable to digest while writing the paper. My personal favorite was the solution to Erdős Problem 1091. The question asks: if a graph G has chromatic number 4, while every small subgraph has chromatic number at most 3, must it contain an odd cycle with many diagonals? The internal model gives a very enlightening counterexample to this conjecture, and the proof was a pleasure to understand. For those so inclined, a really fun exercise is to try to reconstruct the proof from Figure 5 of the paper, which was of course produced by Codex. — https://nitter.net/mehtaab_sawhney/status/2042072817395757467#m
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OpenClaw running Gemma 4 locally at 25 tok/s on a MacBook Air with 16GB RAM. Atomic Chat's TurboQuant algorithm compresses the KV cache so aggressively that models which used to need 32GB+ now run smoothly on base configs. No cloud, no API costs.
— Chubby♨️ (@kimmonismus) 8 avril 2026
This is where local AI is… https://t.co/RqI6xkk46K
OpenClaw running Gemma 4 locally at 25 tok/s on a MacBook Air with 16GB RAM. Atomic Chat's TurboQuant algorithm compresses the KV cache so aggressively that models which used to need 32GB+ now run smoothly on base configs. No cloud, no API costs. This is where local AI is heading! atomic.chat (@atomic_chat_hq) Run OpenClaw with Gemma 4 and Atomic Chat MacBook Air M4 · 16 GB RAM · 25 tok/s No cloud! No subscription fees! Open-source local model. Runs on your regular device — https://nitter.net/atomic_chat_hq/status/2041999885407252732#m
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Yeah. Anthropic just casually kill3d dozens, hundreds, thousands of startups.
— Chubby♨️ (@kimmonismus) 8 avril 2026
Again. https://t.co/bI9gcY0SPF
Yeah. Anthropic just casually kill3d dozens, hundreds, thousands of startups. Again. Claude (@claudeai) Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform. — https://nitter.net/claudeai/status/2041927687460024721#m
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Didn't expect Meta's model to outperform Opus 4.6 or GPT-5.4.
— Chubby♨️ (@kimmonismus) 8 avril 2026
But it still surprises me how well it performs and how close it is to other frontier models on toughest challenges. https://t.co/p7mKtDuj3f pic.twitter.com/TiQLRI5EHd
Didn't expect Meta's model to outperform Opus 4.6 or GPT-5.4. But it still surprises me how well it performs and how close it is to other frontier models on toughest challenges. Epoch AI (@EpochAIResearch) We had pre-release access to Meta’s new Muse Spark model and evaluated it on FrontierMath. It scored 39% on Tiers 1-3 and 15% on Tier 4. This is competitive with several recent frontier models, though behind GPT-5.4. — https://nitter.net/EpochAIResearch/status/2041947954202988757#m
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They tried to integrate it into an OS. No one wanted it this way. Meta however has a much sleeker apporach due to their platforms
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NVIDIA spotlights major advances pushing AI into real-world robotics, from simulation-first training to scalable deployment in agriculture, energy, and households.
— Chubby♨️ (@kimmonismus) 8 avril 2026
Breakthroughs like foundation models, synthetic environments, and edge AI (e.g., Jetson and Isaac platforms) are… pic.twitter.com/6F7SJaV6HK
NVIDIA spotlights major advances pushing AI into real-world robotics, from simulation-first training to scalable deployment in agriculture, energy, and households. Breakthroughs like foundation models, synthetic environments, and edge AI (e.g., Jetson and Isaac platforms) are helping robots learn faster, adapt better, and perform complex tasks autonomously. I love those two examples 🙂 Building solar autonomously and increasing producoty in agriculture are so much beneficial for society.