awesome talk, btw! the cloud-based agentic coding RL setup is super cool.
MACHINE LEARNING
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BEHAVIOR1K Results Promise Exciting AI Research Journey
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That's precisely why these BEHAVIOR1K results excite me! It's going to be a challenging journey with a clear but worthy North Star for all of us!
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NeurIPS Workshop: Foundation Models Meet Embodied Agents Challenge
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Don't miss our NeurIPS workshop this Sunday – in about an hour! Come join us and see the winning teams present their solutions. Event: Foundation Models Meet Embodied Agents Challenge
Dec. 7th, 11:00 AM – 1:45 PM PST
Mezzanine Room 15AB, Convention Center We look forward to -
18 Teams Compete in Global AI Challenge Competition
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We received submissions from 18 teams across academia, industry, and independent participants from around the world, including the US, China, the UK, South Korea, and more.
Amazing work from all participants — thank you for making this challenge truly exceptional! (3/N) -
BEHAVIOR Challenge Results Show Strong Robotic Learning Progress
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How do we measure the rapid progress of robotic learning and embodied AI research? The 1st BEHAVIOR challenge results are out! And we're to see such strong performance on 50 challenging household tasks. Congrats to the winning teams!
Robot Learning Collective
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Waymo customers disagree, autonomous F2 racing more fun in Abu Dhabi
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Actually Waymo customers tell me over and over again you are wrong. And I'm even convinced there's a more fun way to be on a race track. I was at Formula 2 autonomous car races in Abu Dhabi.
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Research-Driven AI Solution Selection in Resource-Constrained Teams
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In small companies like ours, we can’t afford to try every possible solution for each task, so good researchers also play a key role in reasoning about how/why something might work and narrowing down what’s worth trying (and what probably isn’t).
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Recurrent Net Approach with State for Adaptive Agents
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True, @AdaptiveAgents run a similar argument by me yesterday. Thanks. It would be good to try a recurrent net approach ( https://
arxiv.org/abs/2402.19427 or https://
arxiv.org/abs/2312.00752 ) with state. What do you think @caglarml @_albertgu ? Have you tested it? -
Context Length Generalisation and Bandit Training in Language Models
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Some really interesting comments below, but the question is still open and requires investigation. I hope a few students pick it up. I liked the discussions on context length generalisation, the fact that we typically train these models as bandits (even when we do RL, which is
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Testing LLM Attention Mechanisms with Experimental Validation
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Sure. But it attention truly worked, the LLM would no pay attention to the previous topic. Right? We should test this with experiments.