Democratizing Automation

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Models aren't moats and how emergent behavior scaling laws will change the business landscape.
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Robotics Transformers, DreamerV3, XLand 2, and hoping that scaling laws are coming embodied AI.
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I make the case why people iteratively training any model should learn some core concerns of reinforcement learning.
How an unlikely corner of robotics research, locomotion, defined RL's new notion of success.
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My predictions for machine learning this year: 3D assets, self-driving, GPT4, RLHF, Deep RL, diffusion models, and conference cycles.
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Model-as-a-service makes more sense when there is a data advantage to back it up.
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Common machine learning systems are starting to deploy the RL lens of feedback.
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A private space for us to converse and connect
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A musing on how I think autonomous system companies should use RL.
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What I've been up to and what's coming soon.
Choices, risks, and reward reporting. Recommendations for how to integrate RL systems with society.
A tour of control theory, multi-agent RL, and hierarchical learning.
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Democratizing Automation

On machine learning and robotics. The interface of systems and society. The border between high-level and technical thinking. Join 1k+ readers 🤖.
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