Show HN: SAI – A Reinforcement Learning Competition Platform

We’ve been building something for the reinforcement learning (RL) community in stealth for the past two years, and I'm really excited to finally be able to share it here.

Before diving into what we’ve built, here’s the baseline we started from:

- AGI won’t emerge from isolated algorithms. It will require a shared ecosystem where researchers can train, benchmark, and learn together in open environments.

- We believe RL is the most promising pathway toward general intelligence.

- Most RL researchers are still publishing results in isolation, on tasks that can’t easily be compared.

So, we built SAI, a RL competition platform designed to make RL progress more accessible, standardized, and measurable.

SAI is a platform where you can train, benchmark, and submit models to a global leaderboard. A proving ground for reproducible RL research:

- Competitions designed to surface real research challenges (generalization, transfer, and adaptation)

- Infrastructure for reproducible experiments and shared results

- Community through discussion forums, visible progress and collaboration

With SAI live, the next step is competition, and our second one launches October 6: the Booster Soccer Showdown, in partnership with Booster Robotics.

The challenge itself asks a core AGI question in miniature:

Can one agent generalize across different environments without per-task tuning?

Competitors will need to train a humanoid soccer agent to succeed at three related tasks - testing policies for adaptability, transfer, and generalization, the very qualities real-world intelligence requires.

If you’re into RL or just curious about ML, feel free to try out the platform. All feedback and ideas are welcome!

Platform: https://competesai.com/

Booster Soccer Showdown: https://competesai.com/competitions/cmp_xnSCxcJXQclQ

Comments URL: https://news.ycombinator.com/item?id=45467021

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