“Collect some data, train a model, then deploy; a little bit of data (couple hours) is enough for many tasks”
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Said on Latent Space: The AI Engineer Podcast
“… now with the foundation models, this sort of stuff is quite easy to do… the frontier is moving into whole-body manipulation with generalization.”
Google DeepMind, Kirthana Gopalakrishnan · "The Cognitive Revolution" · One Brain, Any Body: Google DeepMind's Keerthana on Gemini Robotics 2, Cross-Embodiment & Humanoids
Play from 12:33
12:33
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What was described
Collect large amounts of pick-and-place demonstration data to train foundation models for manipulation
Said nearby on the same subject
“We then collected those corrections and then basically fed them back into the training data, retrained the models. They then got better.”
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Said on The Leadership in Insurance Podcast - Insurtech & Innovation
“You need more pre-training data… give the model a bunch of data and think… transform this data… pre-trained on it would make the model smarter”
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Said on "The Cognitive Revolution"
“Mistral Large 4, aka LeChunk, a trillion parameter model trained in two months on 3,800 GPUs in Mistral's own data centers”
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Said on The MAD Podcast: How AI Gets Built - with Matt Turck
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