Microsoft Research's Jennifer Neville discusses how evaluation pushes AI systems beyond traditional benchmarks and why "surprising failures" emerge when models are tested on real user needs. She offers practical guidance for working with current AI systems and explains why examining data matters when results defy expectations.
NVIDIA's State of AI in Telecommunications report finds 89% of respondents say open source models and software are important to their AI strategy. NVIDIA announced the 30-billion-parameter Nemotron 3 Large Telco Model, fine-tuned by AdaptKey on open source telecom datasets, plus a full fine-tuning recipe via NeMo. SoftBank, AT&T and Indosat Ooredoo Hutchison are using open models for telecom-specific AI.
NVIDIA argues AI factory ROI hinges on three factors: earning capacity, useful life.
GitHub argues chat is often the wrong interface for AI.
A GitHub Podcast episode pushes back on five common AI hot takes: you still need to read AI-generated code.
UC Berkeley's Aditya Parameswaran argues near-free inference (GPT-4-class costs fell from ~$30 to under $1 per million tokens) demands redesigning data systems for.