Outer Web | Explore

Explore >> Select a destination

You are here		www.superannotate.com Reinforcement learning with human feedback (RLHF) for LLMs \| SuperAnnotate
\|	\|	neptune.ai Reinforcement Learning From Human Feedback (RLHF) For LLMs	0.8 parsecs away Travel
\|	\|	Reinforcement learning from human feedback has turned out to be the key to unlocking the full potential of today's LLMs.	0.8 parsecs away Travel
\|	\|	www.v7labs.com 9 Reinforcement Learning Real-Life Applications	3.2 parsecs away Travel
\|	\|	Here's the list of the most prominent applications of Reinforcement Learning shaping the future of Artificial Intelligence.	3.2 parsecs away Travel
\|	\|	www.lesswrong.com Discovering Language Model Behaviors with Model-Written Evaluations - LessWrong	5.5 parsecs away Travel
\|	\|	"Discovering Language Model Behaviors with Model-Written Evaluations" is a new Anthropic paper by Ethan Perez et al. that I (Evan Hubinger) also coll...	5.5 parsecs away Travel
\|	\|	www.greaterwrong.com The Open Agency Model - LessWrong 2.0 viewer	32.7 parsecs away Travel
\|		Eric DrexlerCentre for the Governance of AIUniversity of Oxford This document argues for "open agencies" - not opaque, unitary agents - as the appropriate model for applying future AI capabilities to consequential tasks that call for combining human guidance with delegation of planning and implementation to AI systems. This prospect reframes and can help to tame a wide range of classic AI safety challenges, leveraging alignment techniques in a relatively fault-tolerant context.	32.7 parsecs away Travel