I had a great time giving a talk at MLSys this morning on "Advances in ML for Systems and Systems for ML". So many enthusiastic questioners! https://
mlsys.org
RESEARCH
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MLSys Talk on ML for Systems and Systems for ML
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BAIR Students and Alumni Win Major Awards at ICRA2024
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Hearty congratulations to BAIR students, faculty and alumni for their many awards at #ICRA2024 this week in Japan BAIR alumni @pulkitology @LerrelPinto @RCalandra won Early Career awards; students from @svlevine @Ken_Goldberg @JitendraMalikCV labs won both Best Paper awards!
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Workshop on Multi-Object Grasping at ICRA 2024
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Also looking forward to Workshop on Multi-Object Grasping: Progress and Prospects today #ICRA2024 in CC-313:
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Hands-on Tutorial on Cloud and Fog Robotics with ROS2 and FogROS2
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Excited about the Hands-on Tutorial on Cloud and Fog Robotics: with ROS2 and FogROS2 today #ICRA2024 in CC-304 8:30am-12:30pm:
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GPT model MMLU performance shows slowing progress
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GPT-3’s score on the MMLU benchmark was 40%. First release of GPT-4 scored 86%, and today GPT-4o is 89%. An increase of just 3% — that’s a full year of progress. If you plot the prior trend we were supposed to be at 100, maybe 120% by now. AI is hitting a wall.
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Data and Engineering in Large Robot Models at ICRA24
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Looking fwd to presenting "Is Data All You Need? Large Robot Models and Good Old Fashioned Engineering (GOFE)" at #ICRA24 in Tokyo at the 3D Manipulation Workshop in room CC-301 at 11:10am this morning: https://
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Evolution of Ideas in Groundbreaking AI Research Papers
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Hi Neil, I learned about this nice paper from reading your *truly* groundbreaking papers. I wasn’t sure who introduced the idea from reading the related work sections. Without intending to put you on the spot, could you please provide us with a short note on the evolution of
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Human Confirmation Bias vs AI Credulity Problem
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Humans have a natural tendency to filter out evidence that disagrees with their beliefs. AIs have the opposite problem: they believe everything you tell them.
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Mosaic AI Releases 70M Image-Text Dataset on Hugging Face
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Awesome models and datasets released by our friends at @DbrxMosaicAI Not only is this a large openly licensed image-text pair dataset (~70M images), it is also the largest dataset hosted on the Hugging Face Hub
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AlphaGo Tuning with Bayesian Optimization Improved Win Rate
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I agree with this thread of @avt_im
. Prior to the match with Lee Sedol, we tuned the latest AlphaGo agent with Bayesian Optimization and this improved its win-rate from 50% to 66.5% in self-play games. This tuned version was deployed in the final match. See