The way I see the current state of research in LLMs and foundation models is that we’ve figured out a way to build an intelligent database — one that compresses human knowledge (largely from the internet) in an autoregressive manner.

The first textbook on multi-agent reinforcement learning is out - a landmark for the field, the first textbook covering game-theoretic foundations with state-of-the-art deep learning! Congrats to its authors Stefano Albrecht , LukasSchaefer and Filippos Christianos More details: www.marl-book.com

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Textbook published by MIT Press (2024)

marl-book.com

Grok knows 🫢 x.com/garykoepnick...

Fascinating read on streaming RL in deep learning - arxiv.org/pdf/2410.14606

The Andromeda galaxy captured by the Hubble Space telescope

How do people genuinely feel about this? are we not pushing it too far now? I have never associated the terminology described here with being offensive or exclusionary, but perhaps I'm just unaware, curious for your opinions. www.acm.org/diversity-in...

Words matter: Alternatives for charged terminology in the computing profession

ACM’s efforts to combat exclusion in the computing profession, ACM's Diversity and Inclusion Council has launched "Words Matter," an effort to replace offensive or exclusionary terminology in the comp...

acm.org

I'm loving this place. It's a technological miracle to only have seen two small outages in the past 2 weeks.. 🙏🙏🙏😅

Rafael Pinto@rcpinto.bsky.social · 2y ago

The server is almost succumbing, but still resisting bravely.

Ok, last two papers for this week! A final game-theoretic RLHF method and a different take on RLHF altogether inspired by prospect theory. 1. 🧲 Magnetic Preference Optimization (MPO). 2. Kahneman-Tversky Optimization (KTO). 🧵 1/3.

Marc Lanctot@sharky6000.bsky.social · 2y ago

Last week, I shared some papers in the intersection of agent/model evaluation and social choice theory. The last was a position paper on RLHF/alignment. This week I will share papers (in pairs) on the topic of "game-theoretic or social choice meet meet alignment/RLHF". 🧵 1/3.