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Beyond Fine-Tuning - Frontiers In LLM Post Training
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| With Jacob van Gogh (Research Scientist, Amazon AGI SF Lab), Bowen Baker (Research Scientist, OpenAI), Joe Gershenson (Head of Engg, Assembled), Arushi Somani (Research Scientist, Anthropic). |
| Assembled, 2525 16th St, #310, San Francisco |
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Jul 15 (Tue) , 2025 @ 05:30 PM
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FREE |
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| DETAILS |
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Join us for a candid, forward-looking conversation on what happens after you pre-train a large language model-tailored for founders & builders who have to ship this year, not someday.
Our panel of hands-on researchers will unpack where post-training is headed in the next 6-12 months, how reward-hacking headaches are evolving, what thought disclosure might really look like, & which open problems Big Labs are scrambling to solve-so startups can place smarter bets today.
Expect technical depth, plenty of audience Q&A, & time to network over good snacks & drinks.
Panelists
Arushi Somani - Research Scientist at Anthropic
Arushi is a researcher at Anthropic, where she works on reinforcement learning & alignment for frontier Claude models. Arushi was a core contributor to Claude 3.7 & Claude 4, & her research focus on measuring & improving the faithfulness of reasoning models as well as supervision-free post-training methods. Previously, she worked on pre-training large multimodal models at Adept & deep neural networks for program synthesis at the Berkeley Sky Lab.
Bowen Baker - Research Scientist at OpenAI
Bowen leads the team working on chain-of-thought interpretability at OpenAI, where his work centers on topics such as detecting misbehavior in frontier reasoning models. His previous work at OpenAI has spanned topics including multi-agent autocurricula, state estimation from vision, attention based network architectures for reinforcement learning, & most recently multi-agent social dilemma games.
Jacob van Gogh - Research Scientist at Amazon AGI SF Lab
Jacob builds planning & agentic tool-use systems for Amazon's newly formed AGI SF Lab, contributing to the lab's Nova foundation-model program. Jacob has also worked on LLM planning & tool use at Adept. Previously he spent four years at Lyft, where he led the real-time online-learning initiative for dispatch & pricing.
Moderator: Joe Gershenson - Head of Engineering, Assembled
Joe leads engineering at Assembled, turning cutting-edge LLM research into production-grade support agents used by hundreds of enterprises. Before Assembled he directed research engineering at Adept, ran ML infrastructure at Stripe, & co-founded a YC-backed predictive-modeling startup.
Agenda
5:30 PM
Check-in, snacks & drinks
6:00 - 6:45 PM
Panel discussion
6:45 - 7:00 PM
Audience Q&A
7:00 - 8:00 PM
Networking
Spaces are limited! Please register early to secure your spot.
Questions? Contact melissa@assembledhq.com
Assembled is committed to creating inclusive tech events. If you require any accommodations to fully participate, please let us know when you register.
This event may be photographed for promotional purposes. By attending, you consent to potentially appearing in event documentation.
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