kay (@kodeefr) header
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ml researcher and founder @EmperoAI closing the loop one optimizer step at a time

Joined October 2024
Photo by kay (@kodeefr)Photo by kay (@kodeefr)Photo by kay (@kodeefr)Photo by kay (@kodeefr)Photo by kay (@kodeefr)Photo by kay (@kodeefr)Photo by kay (@kodeefr)Photo by kay (@kodeefr)Photo by kay (@kodeefr)Photo by kay (@kodeefr)
kay retweeted
You can now comment on posts at empero.org. Sign in with your Empero account, the one you use for Abacus, to reply, vote on comments, like posts and save them for later. Replies to you and your saved posts are collected at empero.org/community
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idk how they built that, but it works surprisingly well. This time, my favorite neuroanatomy with brain pathologies as a service (125 tool calls and 200k tokens later) ;) -> @EmperoAI kojo in @zorai_agent
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kay retweeted
abacus 0.7.1 and Abacus Desktop 0.1.1 are out. The big change: providers and profiles. Add any OpenAI-compatible or Anthropic API with its key and headers, pick from the models it serves, and save profiles with their own settings. First-run setup is now two questions.
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Use kojo @ kojo.sh We are planning on a secondary release concerning cybersecurity-oriented models, which might pique some of your interests. gif made by kojo in ~3 minutes and 21 seconds.
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Proud to finally share what we’ve been working on at Empero: Kojo. 🚀 The model performed extremely well on the completed SWE-bench Verified test suite (461/500 bugs fixed = 92.2%). Claude Opus 4.8 achieved 88.6% in the published leaderboard; Sonnet 5 85.2%; and Mythos Preview achieved 93.9%. We achieved better performance than Opus 4.8 and Sonnet 5 and is within 1.7% of Mythos Preview. The API prices are as follows: $0.175 per million input tokens $1.00 per million output tokens. $0.02 per million cached input tokens. It is also super exciting to be part of the team launching this product so we can get more people using Kojo! Below is something that Kojo made in one-shot: (Do know there are better things made with this model so definitely check out the others within EmperoAI!!)
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welcome to the frontier! kojo.sh from @EmperoAI i got the chance to beta test this model, and i have to say it's the most amazing experience in a LONG time 🧵1/?
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<T-30 minutes>
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I can't believe it WAS easier to just make an AI lab than to join an existing one
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What a terrible day to release a new model, but at least we @EmperoAI can claim to be a reaaaal lab now. Android app incoming, maybe. More models, maybe, incoming. Pricing will be reasonable come monday, as we are still completely self-bootstrapped. We're available, ask us :D
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I am proud to announce that I am currently an active contributer at @EmperoAI. I will be helping with training the models and providing datasets. Even though I am still a novice I am curious to see where my experience with AI will lead me!
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Kojo is our next model in beta currently. Take a gander for yourself @ kojo.empero.org We're pleased with ourselves. I am, at least. Requests for access via a payed API will be handled. P.S, try asking it to make a 3D model of a rocket engine :) Logo by me.
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real RL has never been tried
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kay retweeted
Thank you all for 1M downloads on our 35B Qwen3.8 distill! 🍾
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🚀 Abacus Desktop 0.1.0 is out. The abacus coding agent, now in a window: your projects and sessions, the agent's work as it streams, the diff, a terminal, and a browser it can use. Open source. macOS, Windows, Linux. Any model. abacus.empero.org
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kay retweeted
New from Empero: PageGram: Multi-Head N-gram Memory at the Read Cost of a Flat Table. Engram-style n-gram tables cost 16 random flash reads per token. PageGram reads 2, and matches or beats both flat and Engram-style tables in loss. 📄 alphaxiv.org/pdf/2610.pagegr… 🧵 1/7
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kay retweeted
New from Empero: Identity on Demand: Multi-head Gated Value Residuals (MGVR). A drop-in change to attention that reaches the same loss in 16–22% fewer steps: 1.15–1.23× effective compute for +0.2% parameters. 📄 alphaxiv.org/abs/2610.multi-… 🧵
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