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Machine learning covers methods that train predictive systems from data and evaluate how well they generalize beyond the training set.

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  1. The words Weather Forecasts Get Local beside a flat globe and location-grid illustration
    How WeatherNext 3 Makes Forecasts More Local
    Google DeepMind4m 35s1 VIEW
  2. Animesh Garg in an attention-blue shirt on a black background beside the headline ‘HUMANOIDS AT $10K?’.
    Humanoid Robots Drop to $10K in Two Years - Animesh Garg
    MTS18m 33s
  3. Herbie Bradley beside the words Agent Swarms Learn Together
    How Autonomous Agent Swarms Learn Together
    MTS26m 56s
  4. Three flat trading result lines beside the words AI Bot Trading: 30-Day Results
    What 30 Days of AI Bot Trading Actually Returned
    All About AI12m 10s
  5. Portrait of Chaitanya Asawa with the headline Evaluating Clinical AI.
    From Ambient Documentation to Clinical Intelligence - Chaitanya Asawa, Abridge
    AI Engineer21m 35s
  6. Sangwu Lee presenting the data and training pipeline behind the Krea 2 image model
    Training Krea 2: What matters in generative model training - Sangwu Lee, Krea.ai
    AI Engineer21m 46s
  7. Kristian Fagerlie beside the headline Luck Is Not an Edge
    Why a Winning ML Streak Still Had No Edge
    All About AI20m 40s
  8. Mehul Nariyawala beside the headline The Hardest Robotics Problem on a black background.
    Cracking the Hardest Problem in Robotics
    MTS27m 26s
  9. Samuel Denton beside the headline Continual Learning at Work on a black background.
    Bringing Continual Learning into Enterprises - Samuel Denton, Applied Compute
    AI Engineer19m 3s2 VIEWS
  10. Jack Morris beside the words Scaling Compute on Context
    Scaling Compute on Context - Jack Morris, Engram
    AI Engineer19m 42s
  11. Ronak Malde beside the words Scale Continual Learning
    Scaling Up Continual Learning - Ronak Malde, Trajectory
    AI Engineer23m 3s
  12. Parth Asawa beside the words Evaluate Continual Learning
    Beyond Static Intelligence: Evaluating Continual Learning - Parth Asawa, UC Berkeley
    AI Engineer20m 30s
  13. Nan Jiang beside the headline RL Across Datacenters on a pure black background.
    Cross-Datacenter Reinforcement Learning with Nan Jiang
    AI Engineer19m 50s
  14. Two flat model diagrams feeding a probability gauge beside the words AI Models Test Market Signals
    How AI Models Test Market Signals
    All About AI9m 21s
  15. Guillaume Verdon with a reddish beard and blue top beside the blue-and-white headline “PROBABILISTIC AI CHIPS” on black.
    Classical Computing Can't Scale AI - Guillaume Verdon
    MTS21m 57s
  16. Mahesh Sathiamoorthy in a blue top gestures beside the blue and white headline Post-Training Starts With Data on black.
    Data and Environment Curation for Post-Training LLMs - Mahesh Sathiamoorthy, Bespoke Labs
    AI Engineer19m 12s
  17. Will Brown in glasses and a blue shirt rests a hand on his chin beside the blue and white headline RL beyond easy rewards on black.
    Reinforcement Learning without Verifiable Rewards - Will Brown, Prime Intellect
    AI Engineer19m 27s
  18. Udi Menkes in a blue shirt beside the headline “FINANCIAL AI NEEDS OUTCOMES” on a black background.
    Why Off-the-Shelf AI Doesn't Understand Money - Udi Menkes, Intuit
    AI Engineer19m 50s
  19. Alejandro Vidal beside the words Benchmarks Miss Difficulty
    Why Psychometrics Can Improve LLM Evaluation
    AI Engineer23m 35s
  20. Cormac Brick against a black background beside the blue and white headline “TINY MODELS / MORE DEVICES”.
    Why Large? Tiny LMs & Agents on Edge/Robotics - Cormac Brick, Google
    AI Engineer21m 45s