Introducing Kitten TTS, a SOTA tiny text-to-speech model - Just 15M parameters - Runs without a GPU - Model size less than 25 MB - Multiple high-quality voices - Ultra-fast - even runs on low-end edge devices Github and HF links below

How do we teach LLMs not just to reason, but to reflect, debug, and improve themselves? We at AWS AI Labs introduce MURPHY 🤖, a multi-turn RL framework that brings self-correction into #RLVR (#GRPO). 🧵👇 Link: https://t.co/3kFjI5mxR5

We have launched on YC!

Link to KittenTTS :

Announcing it a little late, but excited to share that I got into YC S25! I've always been super passionate about on-device AI and have always wanted to start a company. So we're building @stellon_labs, where we create tiny frontier models that can run on edge devices. Some

I've left Meta Reality Labs. Miss working with the best team for realistic avatars. Damn, I definitely miss using thousands of GPUs and running super large-scale training experiments. Now back to being GPU poor, but excited to start something new: building tiny AI models for

Repo link :

We launched on possibly the worst timing ever - right when OpenAI, Google DeepMind, and Anthropic all had major releases. Somehow we still made it to #1 on Hacker News. Thanks to everyone who checked us out! 🙏

Also, we would love to collaborate with y’all. If you want to potentially use this model somewhere, shoot me a DM

Someone deployed it on a browser within few hrs!

link:

The open-source community is amazing. We released a tiny TTS model under 25MB. And someone made a web-browser demo within few hours. Yes, its running locally in the web-browser Thanks clowerweb!

Github:  https://t.co/D4k25qj7eR Huggingface:  https://t.co/eCvdtppwTC

link :

Open source speech AI models are getting incredibly powerful So we built a free Mac app that makes them easy to use! 🎤✨

ARC-AGI-3 preview is out It consists of a few games which AI agents can play. It's a good test of few shot learning, generalization and adaptation to new scenarios. > No instructions given to AI > Easy for humans, but hard for AI For perspective: most RL algos have to play

MLX can now run on CUDA devices! 🔥 A game changer for cross platform local AI

Right now a lot of LLM usage is for very basic tasks. eg. Extracting info from text We will soon have several small task specific LMs which are faster, cheaper and more accurate!

Would love to hear your thoughts:

Introducing NamiGen, a fully local Mac App to run state-of-the-art speech models locally. - Easy to install and use - Local alternative to ElevenLabs - High quality TTS - Free to use