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AWS Details AI Product Tagging System Built With SageMaker Serverless Model Customization

AWS published a technical walkthrough describing how to build a product tagging system by customizing the Qwen3-8B open-weight model with SageMaker serverless model customization, using supervised fine-tuning and reinforcement learning with verifiable rewards, then deploying the result to SageMaker Asynchronous Inference for catalog enrichment.

  • AWS published a walkthrough for building an AI-powered product tagging system using Amazon SageMaker serverless model customization.
  • The walkthrough customizes the open-weight Qwen3-8B model, first with supervised fine-tuning (SFT), then with reinforcement learning with verifiable rewards (RLVR) using Group Relative Policy Optimization (GRPO).
2 min read
Tools & products

Databricks Says Internal AI Assistant Tripled Marketers' Use of Data

Databricks says its marketing team built Marge, a Genie Agents-based conversational analytics assistant, on a governed Marketing Lakehouse. The company reports marketers now use data three times more often in decisions, adoption exceeds 85% of the marketing organization, and flagged incorrect responses have dropped 25%.

2 min read
Tools & products

Databricks Says Internal AI Assistant Tripled Marketers' Use of Data

Databricks says it built Marge, an AI analytics assistant powered by Genie Agents and grounded in a governed Marketing Lakehouse, that lets marketers ask questions in natural language. The company reports marketers now use data three times more often in decisions, with adoption exceeding 85% of the marketing organization.

2 min read
Tools & products

Perplexity Portable Computer Comes to Windows on NVIDIA RTX PCs

NVIDIA announced on September 14, 2026 that Perplexity's Portable Computer agent is now available on Windows PCs with NVIDIA GeForce RTX or RTX PRO Workstation GPUs (24GB+ VRAM). The local agent runs multistep tasks on-device, keeps sensitive data off the cloud, uses no Perplexity Computer credits, and can escalate to cloud models with permission.

2 min read

AI news briefing

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

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Analysis and explainers

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

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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.

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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

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