<a href="https:&#x2F;&#x2F;openai.com&#x2F;index&#x2F;introducing-gpt-oss&#x2F;" rel="nofollow">https:&#x2F;&#x2F;openai.com&#x2F;index&#x2F;introducing-gpt-oss&#x2F;</a>

Open models by OpenAI

I gave the AI arms and legs then it rejected me

Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters.<p>This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg.  raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required!<p>We&#x27;re releasing this to give early users a sense of the latency and voices that will be available in our next release (hopefully next week). We&#x27;d love your feedback! Just FYI, this model is an early checkpoint trained on less than 10% of our total data.<p>We started working on this because existing expressive OSS models require big GPUs to run them on-device and the cloud alternatives are too expensive for high frequency use. We think there&#x27;s a need for frontier open-source models that are tiny enough to run on edge devices!

Show HN: Kitten TTS – 25MB CPU-Only, Open-Source TTS Model

Ollama Turbo

Ozempic shows anti-aging effects in trial

Spotting base64 encoded JSON, certificates, and private keys

Japan: Apple Must Lift Browser Engine Ban by December

I'm Archiving Picocrypt

Software Rot

Constitution of the United States Website has removed sections (web.archive.org)

Claude Code IDE Integration for Emacs

Python performance myths and fairy tales

Wired Called Our AirGradient Monitor 'Not Recommended' over a Broken Display

Rethinking DOM from first principles

LLM Inflation

NautilusTrader: Open-source algorithmic trading platform

About the BLOBs in Ventoy

EU proposal to scan all private messages gains momentum

Automerge 3.0

Some thoughts on journals, refereeing, and the P vs NP problem