ChatGPT Is Now Officially a Big Deal in the EU

The European Commission has officially designated ChatGPT as a Very Large Online Search Engine under the Digital Services Act (DSA — the EU's set of laws governing major online platforms and services), according to The Verge. Reddit and Roblox received similar designations as Very Large Online Platforms on the same day.

The threshold for "Very Large" status is 45 million average monthly users in the EU. Once you cross it, the rules change considerably.

For ChatGPT specifically, that means OpenAI must now take active steps to protect minors, mitigate risks to user mental health, and limit the spread of illegal content on the platform. The DSA also bans targeted advertising based on a person's religion, ethnicity, sexual orientation, or political beliefs, and requires companies to be transparent about how their recommendation systems work.

OpenAI has until the end of December 2026 to comply.

This matters because it is the first time ChatGPT has been subject to this level of formal regulatory accountability in the EU. The rules were already in place — they just did not apply to OpenAI until now. Whether the company can implement meaningful safeguards in four months, and how the Commission will verify compliance, remain open questions.

If you are a regular ChatGPT user in the EU, watch for changes to how the platform handles content moderation and what new transparency disclosures appear in the coming months.

OpenAI has launched a direct integration between ChatGPT for Healthcare and Epic — one of the most widely used electronic health record (EHR) systems in the US — along with a Healthcare Public Data plugin, according to OpenAI's announcement.

The integration lets clinicians pull authorised patient information into ChatGPT and ask questions in plain language: what changed since the last visit, which labs need review, whether there are unresolved referrals. The public data plugin connects directly to sources including PubMed, DailyMed, ClinicalTrials.gov, and Medicare coverage data.

This is aimed squarely at clinical teams, not individual patients. The product requires an organisational subscription and a supported Epic deployment — it is not something a GP can sign up for independently.

OpenAI says the company partners with physicians across 60 countries who have reviewed more than 700,000 model responses as part of ongoing evaluation work.

The tool is available now for qualifying healthcare organisations.

Honest read: Genuinely useful if your organisation already runs Epic and has the compliance infrastructure to support it — for everyone else, this is worth watching rather than acting on.

What it is: A new way for Google's Gemini models to analyse video by deciding, on the fly, which parts of a video to actually watch — rather than processing every frame at a fixed rate.

What's new: Standard video processing ingests footage at a fixed pace, typically one frame per second. That forces developers to trade off between cost and detail. Agentic video understanding lets the model seek through footage actively, inspecting only the segments relevant to the task.

How it works: Instead of receiving a uniform stream of frames, Gemini enters an agentic loop — a process where it repeatedly calls an internal tool to fetch specific video segments, audio, or transcript excerpts based on what it needs to answer the query. Think of it like a researcher who skims a report and only reads the footnotes when they become relevant, rather than transcribing the whole document word for word. According to Google's own benchmarks, this cuts analysis costs by up to 66% and token consumption (the volume of data the model processes, which drives cost) by up to 88%, while improving accuracy by up to 7%.

What it can't do: The benchmark figures come from Google's own testing, not independent evaluation. The gains are most pronounced on long videos; performance on short clips is less dramatically different from static processing. Frontier testing beyond the three supported Flash models has not been published.

Who should care: Developers building tools that process long-form video — surveillance, lecture transcription, automated video editing — stand to see meaningful cost reductions today.

Try it / read it: Google DeepMind blog

Hugging Face has released @huggingface/kernels, a JavaScript library that loads and runs GPU-optimised operations for machine learning directly in the browser using WebGPU (a browser API that lets web pages use your device's graphics card for computation), as detailed in the Hugging Face blog post.

The release ships with an initial collection of 207 kernels — the individual mathematical operations, like matrix multiplication and normalisation, that underpin most AI models. Each is versioned, documented, and testable.

Also included: Fleet, a browser-based benchmarking tool that runs these kernels on your own hardware and contributes performance data back to the project.

Who this is for: JavaScript developers building browser-based AI features. You will need a modern browser with WebGPU support (Chrome 113+ or Edge 113+). No server, no API key, no GPU cluster required.

Get started at huggingface.co/webgpu-kernels. The library is Apache 2.0 licensed, meaning free for commercial use.

Worth knowing: Performance varies significantly by device and browser — Fleet exists precisely because behaviour across real-world hardware is still being mapped.

OpenAI has publicly supported California Senate Bill 1119, which would require AI companies to verify user age, conduct independent audits, limit targeted advertising to minors, and connect young users with crisis support resources when safety risks arise, according to OpenAI's policy blog.

The bill now awaits Governor Newsom's signature. If signed, it would set a state-level standard for youth AI safety in the absence of any equivalent federal law. For parents and educators, the practical question is whether the auditing requirement has any enforcement teeth — the bill's text will determine that.