<a href="https:&#x2F;&#x2F;openai.com&#x2F;index&#x2F;openai-to-acquire-astral&#x2F;" rel="nofollow">https:&#x2F;&#x2F;openai.com&#x2F;index&#x2F;openai-to-acquire-astral&#x2F;</a>

Astral to Join OpenAI

“Your frustration is the product”

One of those &#x27;woke up to MacOS updates&#x27; and finding none of my dockers are reachable via dnsmasq (which I use), and low and behold, an update silently breaks custom dns resolution. Hopefully Apple will listen to the bug report I&#x27;ve made. Hold off on updating if you use this…

macOS 26 breaks custom DNS settings including .internal

Anthropic takes legal action against OpenCode

<a href="https:&#x2F;&#x2F;android-developers.googleblog.com&#x2F;2026&#x2F;03&#x2F;android-developer-verification.html" rel="nofollow">https:&#x2F;&#x2F;android-developers.googleblog.com&#x2F;2026&#x2F;03&#x2F;android-de...</a>

Google details new 24-hour process to sideload unverified Android apps

Kitten TTS (<a href="https:&#x2F;&#x2F;github.com&#x2F;KittenML&#x2F;KittenTTS" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;KittenML&#x2F;KittenTTS</a>) is an open-source series of tiny and expressive text-to-speech models for on-device applications. We had a thread last year here: <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=44807868">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=44807868</a>.Today we&#x27;re releasing three new models with 80M, 40M and 14M parameters.The largest model (80M) has the highest quality. The 14M variant reaches new SOTA in expressivity among similar sized models, despite being &lt;25MB in size. This release is a major upgrade from the previous one and supports English text-to-speech applications in eight voices: four male and four female.Here&#x27;s a short demo: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=ge3u5qblqZA" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=ge3u5qblqZA</a>.Most models are quantized to int8 + fp16, and they use ONNX for runtime. Our models are designed to run anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! This release aims to bridge the gap between on-device and cloud models for tts applications. Multi-lingual model release is coming soon.On-device AI is bottlenecked by one thing: a lack of tiny models that actually perform. Our goal is to open-source more models to run production-ready voice agents and apps entirely on-device.We would love your feedback!

Show HN: Three new Kitten TTS models – smallest less than 25MB

An update on Steam / GOG changes for OpenTTD

Juggalo makeup blocks facial recognition technology (2019)

<a href="https:&#x2F;&#x2F;www.ofcom.org.uk&#x2F;online-safety&#x2F;illegal-and-harmful-content&#x2F;4chan-fined-450000-for-not-protecting-children-from-online-pornography" rel="nofollow">https:&#x2F;&#x2F;www.ofcom.org.uk&#x2F;online-safety&#x2F;illegal-and-harmful-c...</a>

4Chan mocks £520k fine for UK online safety breaches

OpenBSD: PF queues break the 4 Gbps barrier

Return of the Obra Dinn: spherical mapped dithering for a 1bpp first-person game

World Happiness Report 2026

A rogue AI led to a serious security incident at Meta

Noq: n0's new QUIC implementation in Rust

Scaling Karpathy's Autoresearch: What Happens When the Agent Gets a GPU Cluster

The Shape of Inequalities

Waymo Safety Impact

Tesla: Failure of the FSD's degradation detection system [pdf]

There&#x27;s a lot of work happening around both generative UI and code execution for AI agents. I kept wondering: how do you bring them together into a fully featured architecture? I built a prototype:- Markdown as protocol — one stream carrying text, executable code, and data- Streaming execution — code fences execute statement by statement as they stream in- A mount() primitive — the agent creates React UIs with full data flow between client, server, and LLMLet me know what you think!

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