Don’t Assume AI Will Take Your Job. Learn To Be A Superworker
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @demishassabis @Ronald_vanLoon @TamaraMcCleary @geoffreyhinton @goodfellow_ian @jeffdean @erikbryn
MACHINE LEARNING
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Don’t Assume AI Will Take Your Job Learn To Be A Superworker
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AI World Models and Robotics: Genie 3 Discussion
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Thanks @friedberg & the @theallinpod crew for inviting me to the summit, it was a blast! Fun conversation discussing everything from the limitations of today's AI systems to the latest world models like Genie 3 and their key potential role in robotics – enjoy! https://t.co/v4YNbpKnRq
— Demis Hassabis (@demishassabis) 14 septembre 2025Thanks @friedberg & the @theallinpod crew for inviting me to the summit, it was a blast! Fun conversation discussing everything from the limitations of today's AI systems to the latest world models like Genie 3 and their key potential role in robotics – enjoy!
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Pi0.5 bin picking experiment and robotic picking throughput advances
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Thank you Junyao for running this experiment so quickly! It’s helpful to see how Pi0.5 picks from bins. Dex-Net used a CNN inside a kinematic control loop; newer methods @AmbiRobotics operate at 500 PPH. https://t.co/FF1W2IwPX5
— Ken Goldberg (@Ken_Goldberg) 14 septembre 2025Thank you Junyao for running this experiment so quickly! It’s helpful to see how Pi0.5 picks from bins. Dex-Net used a CNN inside a kinematic control loop; newer methods @AmbiRobotics operate at 500 PPH.
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Demis Hassabis: Google DeepMind Has Tech Beyond AlphaFold 3
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Demis Hassabis déclare qu’en interne, ils ont des technologies bien plus avancées qu’AlphaFold 3.
— VISION IA (@vision_ia) 14 septembre 2025
Les prochaines étapes vont au-delà du repliement des protéines, vers la découverte complète de médicaments : chimie, conception de composés, toxicité et propriétés clés. pic.twitter.com/BSJvHm4kolDemis Hassabis déclare qu’en interne, ils ont des technologies bien plus avancées qu’AlphaFold 3. Les prochaines étapes vont au-delà du repliement des protéines, vers la découverte complète de médicaments : chimie, conception de composés, toxicité et propriétés clés.
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ImageNet’s Human Baseline and Deep Learning’s Foundation
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ImageNet is also the only large-scale benchmark that had real accurate human baseline accuracy, Karpathy was the human baseline hh. I read/watched somewhere that he went through every image and label in ImageNet and that's very very cute. Without ImageNet efforts, deep learning
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Tencent SRPO: Aligning Diffusion Models with Human Preferences
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Tencent released SRPO on Hugging Face Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference By fine-tuning the FLUX1dev model with optimized denoising and online reward adjustment, improve its human-evaluated realism and aesthetic quality by over 3x
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AI Capability Expansion: Variable Performance Across Tasks
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You can find examples of both on X every day. The existence of graduate-level performance does not mean they are equally good at everything & the existence of idiotic failures does not mean they are not capable of leaps. So far, the trend had been fast expansion of abilities.
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GSM8K Paper Insights on Mathematical Reasoning in AI
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reminded of this paragraph from gsm8k paper, 2021 🙂
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Which invention deserves more recognition and credit?
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What’s an invention you feel deserves more credit?
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SimpleVLA-RL: Scaling VLA Training Through Reinforcement Learning
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SimpleVLA-RL Scaling VLA Training via Reinforcement Learning