The NYT Cooking app has added a built-in AI assistant. A reviewer describes using it and other AI cooking tools as a sous chef that helps but requires close supervision.
Crusoe has sold a troubled Wyoming data center project to Google, a deal that highlights the challenges of developing large AI data centers.
AWS outlines how to deploy a serverless MCP server on Amazon ECS with Fargate, giving AI agents secure, metadata-driven access to an enterprise data lake.
A tutorial on scaling governed AI agent access across an enterprise using Okta Cross App Access and Amazon Bedrock AgentCore, with Cedar policies, EKS, and observability in CloudWatch.
Greenlight Financial's Luna, a tiered multi-agent system on Amazon Bedrock AgentCore, resolves over 90% of up to 4,000 monthly security and risk cases without human intervention.
AWS introduces Web Answer on Amazon Bedrock AgentCore, which returns a synthesized, source-cited answer to a natural-language question in one tool call, removing the need to build a search-and-synthesis pipeline.
Cult.fit is using OpenAI's Codex to let teams across functions build tools and work faster, according to an OpenAI report.
Hugging Face introduces NVIDIA Cosmos 3, a set of new open models aimed at advancing interactive world simulation in gaming.
Claude's new Personal Finance tool lets users connect their bank and card accounts through Plaid and ask questions about their finances.
GitHub Copilot brought AI code completion to millions of developers inside their editors. Here is what it does well, where it needs supervision, and how it fits a modern workflow.
Cursor rethinks the code editor around AI rather than bolting AI onto one. With codebase-aware chat and multi-file edits, it pushed the 'AI-native IDE' idea into the mainstream.
Transformers is the open-source Python library that made state-of-the-art AI models accessible to everyone. Here is what it does, who should use it, and where it fits in a modern AI stack.
Stable Diffusion made high-quality text-to-image generation open and runnable on consumer GPUs, sparking a vast ecosystem of tools and fine-tunes. Here is what it is and why it mattered.
Before GPT dominated headlines, BERT showed that pretraining a Transformer to read text in both directions could transform language understanding. Here is what the landmark 2018 paper introduced.
The 2020 GPT-3 paper made a startling claim: make a language model big enough and it learns new tasks from a few examples in the prompt, with no retraining. Here is what it showed.
CLIP learned to link pictures and language by studying hundreds of millions of image–caption pairs from the web. It quietly became the foundation for image search and generation.
Every modern language model — GPT, Claude, Gemini, Llama — descends from one 2017 paper. Here is what 'Attention Is All You Need' actually proposed, in plain English, and why it changed everything.