Skip to content
DigitalNeuron

Independent AI journalism

Clear reporting on the changes shaping the AI industry.

News and analysis on models, chips, companies, investment and policy, with the context readers need to judge what matters.

NewsExplainers

Latest news

View all →
Tools & products

AWS Brings ChatGPT Desktop App to Amazon Bedrock in GovCloud (US)

AWS says the ChatGPT desktop app, including OpenAI's Work and Codex, is now available through Amazon Bedrock in AWS GovCloud (US). Codex routes requests through Amazon Bedrock Mantle in us-gov-west-1, governed by AWS IAM. AWS says pricing is per-token, zero data retention is supported, and data stays within the selected Region.

  • AWS says the ChatGPT desktop app, with OpenAI's Work and Codex components, is now available through Amazon Bedrock in AWS GovCloud (US).
  • AWS says Codex routes model requests through Amazon Bedrock Mantle in the us-gov-west-1 region, where access is governed by AWS IAM and GovCloud (US) network controls.
2 min read
Business & funding

Anthropic Files S-1 With SEC for Proposed IPO

Anthropic, PBC filed a Form S-1 registration statement with the U.S. Securities and Exchange Commission on Oct. 26, 2026, for a proposed initial public offering of its Class A common stock. The company intends to list on the Nasdaq Global Select Market under the ticker ANT. Share count and price range are not yet set.

2 min read
Tools & products

Databricks Details Lakebase Branching for CI/CD Testing

Databricks says its Lakebase serverless Postgres database uses copy-on-write branching to give each CI/CD pull request an isolated, writable copy of production data in under 60 seconds instead of over 30 minutes, as shown in a case study with customer Snorkel AI managing about 100 concurrent branches on a roughly 2.5 terabyte dataset.

3 min read
Tools & products

NVIDIA Shows Developers Using AI Agents to Build Omniverse Simulations

NVIDIA published a blog post describing developers across its teams who used frontier AI agents, including Astra and Claude Fable 5, alongside NVIDIA Omniverse libraries to build simulation applications covering warehouse automation, gas-turbine testing, robot training, autonomous-driving workflows and a browser-based space station model.

2 min read
Open source AI

Mistral AI Releases Open-Weight Mistral Large 4

Mistral AI released the open weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter multimodal model. The company says it leads open-weight coding and cybersecurity benchmarks, offers three reasoning modes, and was trained on European infrastructure for sovereign AI deployment.

2 min read

AI news briefing

Headlines from other outlets, collected automatically and updated daily. Every item links to the original.

View all →

Analysis and explainers

The technology and business of AI, explained from the ground up.

View all →
Tools & products

How to choose an AI model for a real product

Start from the constraints rather than the leaderboard. Write down your latency budget, your cost ceiling per request, your context requirement, whether you need tool calling or structured output, and where the data is allowed to go. Those five usually eliminate most candidates. Test the remaining two or three on fifty real cases from your own traffic, compare per-case rather than on average, and pick the cheapest one that passes.

5 min read
Models & research

Fine-tuning, retrieval or a better prompt: how to choose

Diagnose the failure first. If the model does not know something, that is a knowledge gap and retrieval fixes it. If the model knows but answers in the wrong shape, tone or format, that is a behaviour gap and prompting fixes it first, fine-tuning second. If the model fails at a specialised skill after both, fine-tuning is the remaining option. Prompting is cheapest and reversible, retrieval is the right default for facts, and fine-tuning is the most expensive and least reversible of the three.

5 min read
Chips & infrastructure

Why does AI use so much electricity?

AI accelerators draw far more power per rack than traditional servers, and that power has to be delivered, cooled and paid for continuously. Training a large model is a one-off spike; serving it to millions of users is a permanent load, and inference is what dominates energy use over a deployed model's life.

4 min read

Practical AI guides

Useful guidance based on official documentation and hands-on practice.

View all →
Tools & products

When a Claude Project or a ChatGPT Project actually earns its keep, per each company's own help pages

Both companies frame Projects the same way: a workspace that holds its own chat history, uploaded reference files, and standing instructions, so you stop re-explaining context every session. Claude caps free accounts at 5 projects and scales knowledge capacity up to 10x on paid plans; ChatGPT scopes a project's memory to chats inside that project only, not across your whole account.

3 min read

Browse by topic

View all →
Models & researchNew frontier models, benchmarks, training methods and the research behind them.Agents & automationTool-using AI systems, autonomous workflows and what they actually automate.Chips & infrastructureAccelerators, data centres, memory supply and the power bill behind AI.Business & fundingRounds, revenue, pricing and the economics of shipping AI products.Policy & regulationLaws, enforcement, copyright and the rules AI has to live inside.Safety & ethicsEvaluations, misuse, bias, alignment research and incident reporting.Open source AIOpen-weight models, permissive licences and the community stack around them.Tools & productsApplications people can use today, with honest notes on limits and cost.

AI glossary

Short, precise definitions of the terms you keep seeing in headlines.

18 articles →

Model directory

A side-by-side reference of the frontier models people are actually deploying.

View all →

The five-minute AI briefing

One email a week. What shipped, what it costs, and what it means — no hype.

No spam. Unsubscribe in one click.