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Post-training is becoming a critical workload for data providers. As data & environment supply increases, it is increasingly important to validate & show the quality of the data, which means vendors are training their own models: orchestrating evals, rollouts, sandboxes, & training & inference workloads all at once.
We're excited to gather practitioners in the community together to share best practices & hear how Mercor is running RL at scale with SkyRL; how Harbor is providing the open standard for evaluation & optimization; & how SkyRL is pushing the frontier on enabling large scale post-training for all
Agenda:
5:30 PM - Doors open, food, & networking
6:00 PM - Mercor
6:20 PM - SkyRL/Anyscale/UC Berkeley
6:40 PM - Harbor
7:00 PM - Open networking
... more details on speakers & topics coming soon!
Hosted by:
Anyscale, the company behind the Ray open source project, is a fully managed AI platform for foundation model-scale workloads. AI teams use it to run data, training, inference, & RL workloads at scale on any cloud.
Harbor builds open-source infrastructure for specifying sandboxed agent tasks for evaluation & optimization, from the makers of Terminal-Bench.
UC Berkeley Sky Computing Lab is the latest in Berkeley EECS's series of five-year collaborative research labs, working on AI & systems.
Mercor is the AI data company for building AI systems with human intelligence. Its network of more than five million experts helps frontier AI labs, big tech, AI startups, & Fortune 500 companies train, evaluate, & measure AI on real professional work. Founded in 2023 & headquartered in San Francisco, Mercor is backed by Benchmark, Felicis, General Catalyst, & Menlo Ventures.
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