Models
New and updated models, and how they score.
VideoStop Renting Intelligence: The Train-to-Deploy Loop for Specialized AI — Fireworks AI
Jetashree Ravi, who leads part of the applied machine learning team at Fireworks AI, explains how teams move from closed models to open ones without losing quality.
Scale Bitwise-Deterministic Pretraining with NVIDIA Megatron Core
Bitwise determinism makes large-scale pretraining easier to debug, validate, and resume reproducibly.
One Model Family, Two Gold-Level Results: Fine-Tuning Nemotron for IOI and IMO
Starting from Nemotron 3, our teams used supervised fine-tuning (SFT), reinforcement learning (RL), and feedback-driven inference to create systems that reached gold-medal level at both IMO 2026 and IOI 2026.
CoreWeave targets AI inference bottlenecks with full-stack optimization
The post CoreWeave targets AI inference bottlenecks with full-stack optimization appeared first on SiliconANGLE.
VideoHill-Climbing Skills: Improve Agents Without Changing the Model — Shubhankar Srivastava, Browserbase
Shubhankar Srivastava uses that uneven progress to show how browser agents can learn a task without changing model weights.