Environmental Impact of LLM Scaling
Concerns center on the carbon footprint and resource demands of training large models, advocating for sustainable practices and efficient architectures. This sub-topic debates whether current scaling methods are viable long-term.
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KOLs Discussing
As companies and governments increasingly depend on LLMs for important decisions, verifiable outputs become increasingly important. Great demo!
Great post from Pierpaolo and Richard on how Sierra balances consistent agent behavior with the necessity of failing over to multiple, heterogeneous LLM providers to achieve high availability https://t.co/Ox0LDTDeBs
A truely generative meta-model of activations, for steering, probing, and understanding LLMs at scale!
I can’t wait for tonight’s rubber match to the Bears-Packers trilogy this season. Both of the regular season games were fantastic (the first settled on a late interception of Caleb Williams, and the second in OT on a Caleb bomb to DJ Moore). Caleb Williams' first playoff game, https://t.co/9tLLmrG6Uf
I've decided to release a minimal, free online version of my upcoming "10-202 - Intro to Modern AI" course, starting January 26: https://t.co/ptnrNmVPyf. As a brief summary, this course introduces students to the elements of modern AI systems: you'll build and train a simple LLM
Value functions play an important role in RL, and increasingly they'll play an important role in RL for LLMs. This new paper led by @rohin_manvi is one step in this direction: using value functions to optimize test-time compute with adaptive computation.
Debug your model with StringSight: LLMs all the way down!
Mistral is proud to provide the text LLM powering Unmute, the open-source voice AI from @kyutai_labs!
Super excited about our new work on pretrained 4-D robotic foundation models. LLMs learned with 4-D representations on egocentric datasets transfer well to real world tasks!