New features, redesigns and business moves in AI products and apps: which got better, pricier or finally usable.
Today we’re releasing Olmo-core 3, a significant upgrade to our framework for developing large language models featuring a redesigned open mixture-of-experts (MoE) training system. Olmo-core 3 is designed to scale MoE training into the trillion-parameter range while preserving computational efficiency.
Building on nearly a decade of co-engineering, CoreWeave has built NVIDIA compute, networking and software into a cloud purpose-built for AI that’s still returning on investment across multiple generations of deployment. Now, CoreWeave is bringing the next generation of NVIDIA infrastructure to production.
Proof of concept for watermarking AI-generated proteins while preserving biological function.
GPT-6.1 Sol is now generally available on Amazon Bedrock, bringing stronger reasoning to coding, computer use, and professional workloads that run frequently.
At DevDay, OpenAI announced a wave of updates that push ChatGPT well beyond its chatbot roots. The company is adding shared workspaces, collaborative documents and slides, an open plugin system with MCP event automation, Slack and Microsoft Teams integrations, an enterprise marketplace with 32 partners, and a new Pro 500 pricing tier.
OpenAI is responding to Meta's buzzy Muse AI with agentic helpers of its own: Dots. During its DevDay keynote on Tuesday, OpenAI announced that Dots will serve as always-on AI assistants that can "do nearly anything" across connected apps in the background while learning your preferences over time.
OpenAI's new Dots are always-on agents that run on their own cloud computers, where they fix bugs or send out forgotten invoices, sometimes before anyone asks. Users can reach them through ChatGPT, Slack, and Microsoft Teams. When no one is working with them, Dots look for ways to help in the background using read-only access.
At DevDay 2026, OpenAI gave Codex reusable cloud environments, automatic security scans for GitHub repositories, and a code review view in the desktop app. The Agents API now supports Computer Use, and a new Decisions API handles fast, single decisions. The Ultrafast premium tier promises up to eight times the speed at six times the price.
It’s OpenAI’s turn in the fall tech events calendar. The company is hosting its annual DevDay on September 29th in San Francisco, and during a live keynote featuring CEO Sam Altman, it revealed several notable updates, including Dots, its AI agent product that rivals Meta’s recently-launched Muse.
Explore more than 20 announcements from OpenAI DevDay 2026, including GPT-6 Astra, ChatGPT, Codex, APIs, security, and new tools for builders.
Dots by OpenAI are a proactive assistant that can keep working across complex projects and everyday tasks. Learn how dots help you stay in control while work moves forward.
xAI's Grok 4.7 is now available on Amazon Bedrock: a frontier model for coding, long-running agents, and knowledge work. It offers a 500K token context window and four configurable reasoning effort levels, reachable through the Responses, Chat Completions, and Converse APIs.
Reinforcement Learning environments give new capabilities to agentic AI systems, and they’re a great way to measure and improve performance in your agents. Therefore, Hugging Face Hub now has a special place for RL Environments.
In this blog post, I explain how to use the new fuzzing taskflow based on the GitHub Security Lab Taskflow Agent AI framework.
Introducing private, server-side memory to Private AI Compute for personal AI.
To build and deploy sophisticated robotics applications that can perceive, reason and act in dynamic environments, developers need new physical AI models and tools. The ROS open framework is a project from Open Robotics that helps humans build robots.
Hugging Face added GGUF support to transformers. Users can choose a quantised checkpoint from the Hub and pass gguf_file to from_pretrained for local generation without additional configuration.
System performance, efficient infrastructure scaling and continuous software optimization are key levers that determine AI inference economics. Higher system performance means more tokens generated, resulting in higher revenue. Efficient scaling means throughput grows proportionally as hardware gets added, requiring fewer resources to serve users at scale. Continuous optimization means generating more value from infrastructure investments.
Know everything. Do anything. That was the message NVIDIA founder and CEO Jensen Huang brought to Salesforce Dreamforce Tuesday, joining CEO Marc Benioff onstage in an appearance that coincided with the announcement of Koa — Salesforce’s first CRM reasoning model, built on NVIDIA Nemotron 3 Super. Huang didn’t just take the stage.
On a sweltering August evening in Silicon Valley, as the sun dropped and air conditioning loads spiked, Silicon Valley Power sent a signal to an AI factory to adjust its power consumption.