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Today we’re launching INTELLECT-2: The first decentralized 32B-parameter RL training run open to join for anyone with compute — fully permissionless. Scaling towards frontier reasoning across coding, math and science.

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Prime Intellect

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353,791 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 11

Фото профиля Prime Intellect
Prime Intellect1 год назад

INTELLECT-2 brings decentralized training into the inference-time compute era: • Fully async, decentralized reinforcement learning • Eliminating communication overhead • Scalable across heterogeneous GPUs worldwide

Фото профиля Prime Intellect
Prime Intellect1 год назад

Over the past months, we’ve built the full open-source stack to enable INTELLECT-2: • PRIME-RL: fully async decentralized RL • GENESYS & SYNTHETIC-1: crowdsourced tasks & verifiers for RL • TOPLOC validation: verifiable inference with low overhead • Protocol Testnet: global AI coordination infrastructure

Фото профиля Prime Intellect
Prime Intellect1 год назад

How INTELLECT-2 operates: • Inference Rollout Workers: Decentralized swarm collects rollouts using the latest policy model • TOPLOC Validators: Verify the inference computations • GRPO Training Workers: Train on new data and broadcast weights via our shardcast library

Фото профиля Prime Intellect
Prime Intellect1 год назад

Asynchronous RL completely eliminates communication bottlenecks. Our ablation studies confirm we maintain performance even with 4-step delays, making decentralized training viable with weak global interconnects.

Фото профиля Prime Intellect
Prime Intellect1 год назад

With INTELLECT-2 we aim for frontier reasoning performance with a controllable thinking budget. By incorporating length rewards into our training run, users can specify how long the model should reason for a given task.

Фото профиля Prime Intellect
Prime Intellect1 год назад

Contribute compute and watch training live on our dashboard: • Participate in our testnet powering an open reasoning model • Slashing and validation keep contributions honest Join us in building towards open and decentralized AGI

Фото профиля Lab4crypto
Lab4crypto1 год назад

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Фото профиля Michael Luo
Michael Luo1 год назад

This is amazing work! Looks like asynchronous RL for LLMs is pretty stable 🤩, a paradigm shift away from traditional Deep RL where synchronous PPO won, as opposed to A3C and IMPALA

Фото профиля Tom Bennet
Tom Bennet1 год назад

Decentralized RL training? Sounds like we're breeding digital superminds in a worldwide compute farm. Count me in for the chaos.

Фото профиля jesse.base.eth
jesse.base.eth1 год назад

ok this is really sick

Фото профиля Burny — Effective Omni
Burny — Effective Omni1 год назад

Decentralized open source is climbing

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