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Hillclimb

Hugging Face
OpenAI
AWS

Training data for AI self-improvement

About Hillclimb

Hillclimb aims to improve model capabilities toward recursive self-improvement. To do so, the company focuses on solving two core problems: aggregating all human research data and automating RL environment creation. Each step forward on these axes unlocks further data, enabling stronger research capabilities to emerge, bringing the world closer to self-improving models. Hillclimb is backed by Tier 1 VCs, Paul Graham, and angels from OpenAI, Anthropic, DeepMind, xAI, and Meta Superintelligence Labs.

Source: Hillclimb official website

Key Features

Data aggregation

collection of all human research data

RL environment automation

creation of reinforcement learning environments

Model capability improvement

development of models able to self-improve

Access to enriched data

selling data to frontier research labs

Support from renowned investors

top-tier backers like OpenAI and Meta

Advanced research

facilitating advanced research through data access

Talented team

collaboration with domain experts

Collaborative environment

workspace conducive to innovation.

Practical Use Cases

Improving AI models: using Hillclimb's capabilities to develop self-sufficient AI models
Frontier research: supporting labs researching advanced AI
Automating research processes: streamlining research steps through automation
Starting from
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