6 Posts
Reinforcement learning from human feedback (RLHF) is widely used to fine-tune pretrained models to deliver outputs that align with human preferences. New work aligns pretrained models without the cumbersome step of reinforcement learning.
Reinforcement learning from human feedback (RLHF) is widely used to fine-tune pretrained models to deliver outputs that align with human preferences. New work aligns pretrained models without the cumbersome step of reinforcement learning.
Training an agent that controls a robot arm to perform a task — say, opening a door — that involves a sequence of motions (reach, grasp, turn, pull, release) can take from tens of thousands to millions of examples...
Training an agent that controls a robot arm to perform a task — say, opening a door — that involves a sequence of motions (reach, grasp, turn, pull, release) can take from tens of thousands to millions of examples...
Do language models have their own opinions about politically charged issues? Yes — and they probably don’t match yours. Shibani Santurkar and colleagues at Stanford compared opinion-poll responses of large language models with those of various human groups.
Do language models have their own opinions about politically charged issues? Yes — and they probably don’t match yours. Shibani Santurkar and colleagues at Stanford compared opinion-poll responses of large language models with those of various human groups.
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