New models, API changes, coding tools and pricing — the news and guides that change your day-to-day work.
Start hereEveryone
What AI is, how to ask it, and what to watch out for — the basics everyone should start with, whatever their job.
5 guides41 min in totalBeginner
Courses by roleDevelopers
From your first API call to working with coding assistants, structured output and cost control.
4 guides61 min in totalBeginner → Practical
How-to guide17 min
Give context, work in small steps, verify with tests — a workflow that makes AI-written code something you can trust.
Explainer9 min
How do chatbots answer from your company's documents? Here's how RAG, a pattern widely used in AI products, works.
Explainer8 min
What "$2 per million tokens" on an AI price list means, and how to estimate what your own usage would cost.
How-to guide14 min
Using the Claude API as the example: keep your API key safe, send a first request from Python, and read the answer, the stop reason and the token usage.
How-to guide15 min
Instead of asking for JSON and hoping, define the shape as a schema and get responses your code can use directly. Worked through with a customer-message classifier.
How-to guide15 min
Cache the long instructions and documents you resend with every request, and their input cost drops sharply. Using a support bot built on a manual, here's how to place the cache point and check that it works.
Explainer9 min
Unlike a chatbot that only answers, an agent takes a goal and keeps going, using tools and checking results, until the job is done. How it works, what it suits, and what to settle before you hand it work.
How-to guide18 min
Build a Python chatbot that searches ten internal policy documents with embeddings and answers only from what it finds, then test search and answers separately and fix what breaks.
Windows laptops built on NVIDIA's RTX Spark chip are now on sale.
Reflection, a new US AI lab, released its first model, Beam, as an open model on Hugging Face.
NVIDIA released Nemotron 3.5 Super VL, an open model for agents, plus two Bolt models for PCs and edge devices.
Apple showed how a new version of its MLX framework can link several Mac Studios to run very large models.
NVIDIA committed $250 million worth of compute over five years to strengthen agentic AI safety and security research in the UK.
Google DeepMind and Singapore's Government Technology Agency built an AI model that spots scam conversations on the phone itself.
Google unveiled Gemini 4 Argon, its latest frontier model, on October 13 and released it globally the same day.
Anthropic introduced a life sciences research group and lab, and shared early results in which Claude found a new enzyme system reminiscent of CRISPR.
Microsoft researchers introduced StudentSim, AI simulators that imitate individual real students.
Meta unveiled Muse Wonder and Muse Wonder Full on October 12, calling them its most capable models to date.
Anthropic published a new version of its Usage Policy for Claude, effective November 12.
Naver Cloud published results from re-optimizing Mamba-2 compute kernels for NVIDIA's B200 GPU.
Google DeepMind released EmbeddingGemma 2, a lightweight embedding model that maps text, images, audio and video into one space.
European AI company Mistral released Mistral Large 4, its largest model, as a public preview on October 6.
