Ben Fielding
@fenbielding
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Co-founder & CEO @GensynAI - the network for machine intelligence. I like modular, composable, decentralised, and evolutionary machine learning
London / Remote
Joined December 2014
The @gensynai network has now trained one million models. This work at Gensyn is quickly unfolding as the most relevant substrate for open, permissionless, and trustless innovation of AI. AI has a real shot at staying *truly open*, and that is very exciting.
One million models trained on the Gensyn testnet. To everyone running nodes, experimenting, and building with us - thank you. This milestone is yours.
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we just hit one million models trained over decentralised infrastructure and coordinated by the @gensynai testnet decentralised AI is getting pretty hard to deny at this point
One million models trained on the Gensyn testnet. To everyone running nodes, experimenting, and building with us - thank you. This milestone is yours.
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For those running RL-Swarm we encourage you to update to CodeZero 👋 To update your local codebase, simply run: git pull This will prepare your environment to launch a new CodeZero node When you’re ready to launch, you have two paths 👇 Docker CPU: docker-compose run --rm
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We shipped CodeAssist last week. Today we are releasing CodeZero. CodeZero evolves RL Swarm into a society of models where agents learn to code together through three roles: proposers create challenges, solvers attempt them, evaluators judge quality. Each role teaches the
Introducing CodeZero, a new environment built on RL-Swarm that extends our distributed learning framework into cooperative coding agents. Today, users can participate as Solvers - tackling coding problems and sharing their results so the swarm can learn collectively.
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Last week we launched CodeAssist - a hands-off coding assistant that learns from you as you work. Today we’re launching CodeZero, an extension of our p2p swarm RL library (GenRL) that raises the performance bar for coding models. Get it below!
Introducing CodeZero, a new environment built on RL-Swarm that extends our distributed learning framework into cooperative coding agents. Today, users can participate as Solvers - tackling coding problems and sharing their results so the swarm can learn collectively.
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Announcing CodeZero CodeZero extends RL Swarm into coding, using the same underlying framework (GenRL) and adding distinct roles for the nodes Together, these roles form a self-sustaining training economy and a continual learning coding system over decentralised infrastructure
Introducing CodeZero, a new environment built on RL-Swarm that extends our distributed learning framework into cooperative coding agents. Today, users can participate as Solvers - tackling coding problems and sharing their results so the swarm can learn collectively.
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"for too long, we have treated the model's architecture (the network structure) and the optimization algorithm (the training rule) as two separate things, which prevents us from achieving a truly unified, efficient learning system." some of us have been doing this for a decade..
Introducing Nested Learning: A new ML paradigm for continual learning that views models as nested optimization problems to enhance long context processing. Our proof-of-concept model, Hope, shows improved performance in language modeling. Learn more: https://t.co/fpdDlYaleL
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we're building CodeAssist as open research - follow along here and follow @gab_p_andrade for updates
We’ve released the Day 0 research report for CodeAssist, outlining a new approach to training personalized AI coding assistants with tool-mediation games. 📄
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crazy that more ML apps aren't using this UX for live RLHF / SFT
Today I’m launching Swipe -- a new way to steer image models. The idea is simple – start with a prompt, swipe left / right to steer the model towards what you’re thinking of.
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CodeAssist is live. Personalised coding assistants being trained at the edge. 🧠⚡️
Introducing CodeAssist, your personal coding assistant that learns as you work. Every edit becomes training data. Every session makes it better. The more you code, the more it understands you.
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so proud of the entire team behind CodeAssist - a true labor of love to bring something this innovative to life huge shoutout to the gensyn community for showing up with 30 minutes’ notice for the live walkthrough. 1.1k of you joined.. unreal
Introducing CodeAssist, your personal coding assistant that learns as you work. Every edit becomes training data. Every session makes it better. The more you code, the more it understands you.
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This is collaborative research - building transparent AI systems that learn in the open. Excited to see where we can take CodeAssist as we iterate and collaborate in public. Open code, open research, open learning.
1/ The research philosophy CodeAssist is a research prototype we just released @gensynai, and we'll iterate COMPLETELY IN THE OPEN from here on out; open source code, research, and insights. The code is all on GitHub. Soon we'll drop a "living paper". More details soon 😎
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The next iteration of AI coding assistance is here! a model that learns how you code and gets personalized to you. team continues to ship
Introducing CodeAssist, your personal coding assistant that learns as you work. Every edit becomes training data. Every session makes it better. The more you code, the more it understands you.
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👀
Was going to wait a few days before saying more, but am too hype about what we're building so here we go... In this 🧵 I'll drop my (biased) thoughts on what I think are the most important and exciting points about CodeAssist.
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So, on top of all the products live on the @gensynai testnet (Judge, RL Swarm, BlockAssist), we now have CodeAssist. CodeAssist allows you to train your own personal coding model. It doesn’t offer suggestions you accept or reject - it writes directly into your editor in real
Introducing CodeAssist, your personal coding assistant that learns as you work. Every edit becomes training data. Every session makes it better. The more you code, the more it understands you.
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We’re thrilled to release CodeAssist today - a novel research prototype exploring whether AI can truly learn to cooperate with you through interaction alone. Unlike traditional coding tools that autocomplete or take over, CodeAssist learns how you work in order to work with you.
blog.gensyn.ai
Today, we're introducing CodeAssist, an AI coding assistant that trains on your local machine. As you write code and solve problems, the assistant observes your edits and preferences - learning how...
Introducing CodeAssist, your personal coding assistant that learns as you work. Every edit becomes training data. Every session makes it better. The more you code, the more it understands you.
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Introducing CodeAssist 🧑🤝🧑 A personalized coding agent built on @gensynai. It learns directly from your keystrokes, adapting to your personal style. Run it today and train the best agent.
Introducing CodeAssist, your personal coding assistant that learns as you work. Every edit becomes training data. Every session makes it better. The more you code, the more it understands you.
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Today we’re launching CodeAssist: a research prototype with a privacy-preserving, on-device coding assistant. The model runs and trains locally, learning alongside you as you solve LeetCode-style coding challenges. Try it now and help us build the next generation of AI
docs.gensyn.ai
Get up and running with CodeAssist and start training local models based to code like you.
Introducing CodeAssist, your personal coding assistant that learns as you work. Every edit becomes training data. Every session makes it better. The more you code, the more it understands you.
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Train your assistant when to take action, what action to take, and instill your taste and style into it.
Introducing CodeAssist, your personal coding assistant that learns as you work. Every edit becomes training data. Every session makes it better. The more you code, the more it understands you.
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