At CES 2026, Nvidia made a decisive move to position itself as the foundational platform for generalist robotics, unveiling a full stack of open AI models, simulation tools, and edge hardware designed to power robots that can reason, plan, and act across diverse real-world environments.  Much like Android became the default operating system for smartphones, Nvidia aims to provide the underlying intelligence layer for robotics as artificial intelligence moves out of the cloud

At AWS re:Invent this week, Amazon Web Services signaled that the next phase of enterprise AI is less about picking a single “best” chatbot model and more about tailoring models to a company’s exact data, language, and use cases.  Coming right after AWS announced Nova Forge, a service for training custom versions of its Nova AI models, the company introduced new features in Amazon Bedrock and Amazon SageMaker AI meant to make custom large language model work faster and less

Zyphra’s unveiling of ZAYA1 marks a significant moment in the AI hardware landscape, proving that large-scale model training can succeed outside NVIDIA’s well-established ecosystem.  After a year of collaboration with AMD and IBM, Zyphra trained ZAYA1 entirely on AMD Instinct MI300X GPUs, Pensando networking, and the ROCm software stack, demonstrating that AMD’s platform can support major foundation models without exotic configurations or performance compromises (Artificial

Nvidia’s latest earnings paint a picture of a company not just riding the AI wave, but helping create its momentum. The chipmaker reported an astonishing $57 billion in revenue for the third quarter, a 62% jump from the same period last year (TechCrunch; Yahoo Finance; Startup Ecosystem). This surge was matched by equally impressive profitability: net income soared to $32 billion, up 65% year-over-year (TechCrunch; Yahoo Finance; Startup Ecosystem). Both figures blew past Wal