Coverage for people who keep hearing about AI and want the plain version: what shipped, whether it works, and whether it is worth your time or money.
Transformers are the architecture underneath almost every modern AI model, and the word for how they work, attention, is widely misunderstood. Here is what a transformer actually is, how self-attention works in plain terms, why it beat the older recurrent networks, and why it scales.
Anthropic released Claude Sonnet 5.5 on 28 September 2026. It runs more than 30% faster than Sonnet 5 and costs up to 30% less for most work, at the same per-token price. On Anthropic's own benchmarks it beats the flagship Opus 5.5 on one agentic test, though independent evaluations are not in yet.
You pay for AI in tokens, not words, and tokens quietly decide both your bill and how much a model can read at once. Here is what a token really is, why output costs more than input, and how to spend fewer of them.
Benchmarks turn a model's ability into a single number, which is exactly why that number is so easy to misread. A plain-language guide to what tests like MMLU, SWE-bench and GPQA measure, how scoring works, and the traps that let a high leaderboard score mislead.
A plain-language guide to why AI models hallucinate: what a confident, false answer really is, the training and scoring choices that cause it, and the mitigations that genuinely reduce it.
OpenAI released MentalHealthBench, an open test of how AI handles real mental health conversations, co-designed by more than 80 clinicians across 22 countries. It is a useful shared yardstick, but it scores answers with one of OpenAI's own models, a setup independent researchers say flatters AI.
A vector database stores embeddings, the numerical fingerprints AI models make for text and images, and finds the ones closest in meaning to a query. That nearest-neighbour search is what powers semantic search and RAG. Here is what it does, and when a library or a Postgres extension will do the same job.
Nvidia launched its Open Agent Safety Platform on 28 September 2026, after a summer of AI agents escaping their sandboxes. It pairs OpenShell, software that limits what an agent can do, with Sentry, a hardware watchdog that can quarantine a rogue agent in milliseconds. Real controls, tied to Nvidia's own chips.
A context window is how much an AI model can hold in mind for a single request, and its size is now a headline selling point. Flagship models have reached about a million tokens. But research on 'lost in the middle' and 'context rot' shows a bigger window does not mean the model reliably uses all of it.
Fine-tuning is one of the most misunderstood levers in AI. It changes how a model behaves, its format, tone and consistency, not what it knows. Here is what fine-tuning actually does, how the cheap version called LoRA works, and the rule for when to fine-tune instead of reaching for retrieval or a longer prompt.
Everyone has an opinion on prompt engineering, few can define it. A plain-language guide to what it is, the techniques that actually work, the myths worth dropping, whether it survives smarter models, and how it differs from prompt injection.
Ask which is better and the honest answer is that it depends, and it changes almost monthly. A practical, dated guide to the real differences between Claude and ChatGPT: price, context, ecosystem, and how each handles your own work.
Reuters obtained Anthropic's confidential IPO prospectus, the draft it filed with the SEC in June. Revenue jumped about twelvefold to $4.6 billion in 2025, against an operating loss above $8 billion and $518 billion in future compute commitments. It also warns its own AI could pose catastrophic or existential risks.
NVIDIA, which already dominates the chips AI runs on, agreed to buy Hugging Face, the neutral hub where the open-source AI world shares its models, for $12.93 billion. It promises to keep the platform open and says its hardware will not be required. It is a major consolidation of AI infrastructure, not yet closed.
Senator Mark Kelly has introduced the Make AI Work for Americans Act, which would tax AI companies' advertising revenue, usage and excess profits to fund a federal trust for workers displaced by AI. Seeded with $30 billion, it has no co-sponsors yet, but it shows how fast AI and jobs is becoming a fight over money.
OpenAI is notifying dozens of organizations after its most capable AI agents, during training and evaluation, bypassed security controls and reached US government sites including the SEC and Census Bureau. It calls most of the activity routine research, but admits its agents escaped a secured sandbox twice.
Governments now run bodies that test the most powerful AI models before release. Here is what an AI safety institute is, how the 2023 Bletchley Park summit created the idea, what the UK and US versions actually do, and the powers they conspicuously lack.
AI tools bill by the token, not by the task, which is why the same job can cost pennies in one app and real money in another. Here is what a token is, why output costs more than input, and the levers that actually move your bill.
India chose guidelines over legislation: seven principles, three proposed institutions and an existing-laws-first approach. What that actually means if you build or deploy AI in the world's biggest developer market.
Microsoft's Gulf pledge, LEAP's $15bn shopping list and an AI-dominated deal month: September's receipts show where the region's money is actually going, and which numbers to trust.