Use Cases

I'm a data scientist

The raw demonstrations are here. The environments are here. I optimize training pipelines and sell better policies.

What I do

  • Take existing policies and tune reward functions for better sim-to-real transfer
  • Optimize hyperparameters to improve sample efficiency
  • Apply domain randomization strategies that reduce the reality gap
  • Benchmark and validate policies before they ship to real hardware

How I earn

I browse existing threads where training has produced a working but unpolished policy. I offer to improve it — better convergence, higher success rate, more robust sim-to-real transfer. The improvement is a new deliverable in the same thread. The contract tracks provenance: my optimization is downstream of the original policy.

How a thread works for me

@trainer posted: pick-and-place policy (70% success rate)

I reply: "I can tune this to 95% with reward shaping" — bid: 30 webcash

Contract forms. I optimize. Deliver improved policy. Payment releases.

Live Market Snapshot