“Nobody called LLMs” totally misunderstands how AI development happens. LLMs didn’t spontaneously appear for no reason. I knew they would work, I demonstrated them working in 2017, and I said at that time I think they’ll be a big deal.

Supercharge Your Home Rig with Data Center-Level LLM Inference Speeds 🔥 💻 Ever dreamt of running data center-grade Large Language Model (LLM) inference on your personal gaming GPU? PowerInfer now makes this a reality. arxiv.org/abs/2312.12456

LLMs and High-Stakes Decisions: Finally Becoming More Reliable? 🤔 A new approach rooted in the principles of social choice theory, leverages a novel application of the Partial Borda Count—a method to merge ranked choices—which could dramatically improve the reliability of

Turbulences Ahead: Are LLMs for Coding Robust or RUSTy? ✈ 🌪 Turbulence is a new benchmark tailored to test the integrity of instruction-tuned Large Language Models (LLMs) in code generation. Rather than just gauging if an AI can code, it zeroes in on the nuances: Can it

Thou Shall Not Lie: LLMs' might be getting a reality check ✔ Hallucinations in AI-generated content often spark intense discussions about the trustworthiness of large language models (LLMs). Now, a new approach called Truth Forest (TrFr) is aiming to significantly enhance