Eight States Take OpenAI to Court Over Kids' Safety

Iowa, Kansas, Nebraska, West Virginia, Arkansas, Arizona, Idaho, and Montana have filed separate lawsuits against OpenAI, according to The Verge. The complaints allege the company violated consumer protection laws by marketing ChatGPT as a safe, youth-appropriate product while knowing it posed real risks to young and vulnerable users.

The states cite allegations from families of teens and adults who say the chatbot contributed to their loved ones' deaths. The lawsuits also claim ChatGPT degrades critical thinking, encourages paranoia and delusions, provides dangerous medical advice, and fosters unhealthy relationships with the AI itself.

Beyond user harm, the states allege OpenAI collected personal data from minors without sufficient safeguards and failed to prevent underage users from accessing the platform at all.

OpenAI disputes the characterisation. A spokesperson told The Verge the company has "built industry-leading age-specific protections" including parental controls, break reminders, and age-appropriate model settings. No court has ruled on the merits of any claim, and these remain allegations.

What the states are asking for: civil penalties, an end to what they call misleading safety claims, and the deletion of unlawfully collected data.

If you have a teenager using ChatGPT, enable parental controls through the family management options — they're available but not turned on by default.

Meta has published Muse Spark Open, according to Hugging Face — an open-weights model (meaning you can download and run it, though the training data is not public) built specifically for coding tasks. It can read a codebase, write and debug code, process images, audio, and video, and call external tools, all within one model.

It is primarily aimed at developers, not general users. The full version requires hardware most individuals won't have access to — think multiple server-grade GPUs and roughly 1.5 terabytes of storage. This is a tool for teams and researchers, not a laptop download.

What it does that others don't: it handles multiple input types alongside code in a single model, and it plans and self-corrects across long tasks rather than answering in isolated turns.

It is free to download under Meta's licence. Verify licence terms before any commercial use.

Honest read: Worth watching if you work in software development or AI research — genuinely capable on paper, though independent evaluations haven't landed yet, so treat Meta's own capability claims accordingly.

What it is: A research finding from Anthropic warning that small AI models could soon spread autonomously across IoT (Internet of Things) devices — the category covering smart fridges, robot vacuums, TV boxes, and similar connected hardware.

What's new: Previous malware had to be hand-coded for specific hardware. These AI models could adapt their own configuration on the fly to run on unfamiliar devices, making them harder to predict and contain.

How it works: Anthropic ran small open-weights models on cheap Android TV boxes with 4GB of memory. Using quantization (compressing the model into fewer bits so it fits on limited hardware) and sharding (splitting the workload across multiple devices), the models successfully loaded and generated output. One model configured itself across eight of nine different hardware types without being pre-programmed for each. With no central server to shut off, any resulting worm could keep spreading even if individual devices are cleaned.

What it can't do: This is experimental, not deployed. Anthropic's own testing surfaced significant practical challenges. Doubling time — how fast the infection could spread — is estimated in days, not hours, which is slow by malware standards.

Who should care: Anyone with a home full of connected devices. The threat isn't here yet, but the research suggests the window before it is may be shorter than expected.

Try it / read it: Ars Technica

FLUX.3 Image Klein, from Black Forest Labs, is a free open-weights image generation model now available on Hugging Face. It handles text-to-image, image-to-image editing with reference photos, and layout control — letting you specify exactly where elements appear in a composition using a simple coordinate system.

The easiest way to try it is directly in the Hugging Face Space, no installation needed. For those comfortable running models locally, it works with the diffusers Python library and supports smaller GPU configurations via FP8 and NVFP4 quantized (compressed) weights.

What sets it apart from standard generators: you can pass multiple reference images and instruct the model to combine elements from each, or lock specific objects to specific areas of the frame — useful for anything requiring precise composition.

Free to use. Local installation needs a capable GPU; the browser demo works without one.

Worth knowing: The licence terms differ between the two available checkpoints — check which applies before using outputs commercially.

Google DeepMind and Singapore's Government Technology Agency have jointly fine-tuned an AI scam-detection model, presented at Singapore International Cyber Week 2026, according to Google DeepMind. The model runs entirely on-device, meaning conversations are never sent to Google or the government — analysis happens on the phone itself. It was trained on local scam patterns, including impersonation of Singapore public institutions and officials, which generic models often miss. Rollout within applications is being phased carefully. No launch date has been confirmed.