Hey everyone, it's Alex (still traveling!), and oh boy, what a week again! Advanced Voice Mode is finally here from OpenAI, Google updated their Gemini models in a huge way and then Meta announced MultiModal LlaMas and on device mini Llamas (and we also got a "better"? multimodal from Allen AI called MOLMO!) From Weights & Biases perspective, our hackathon was a success this weekend, and then I went down to Menlo Park for my first Meta Connect conference, full of news and updates and will do a full recap here as well. ThursdAI - Recaps of the most high signal AI weekly spaces is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Overall another crazy week in AI, and it seems that everyone is trying to rush something out the door before OpenAI Dev Day next week (which I'll cover as well!) Get ready, folks, because Dev Day is going to be epic! TL;DR of all topics covered: * Open Source LLMs * Meta llama 3.2 Multimodal models (11B & 90B) (X, HF, try free) * Meta Llama 3.2 tiny models 1B & 3B parameters (X, Blog, download) * Allen AI releases MOLMO - open SOTA multimodal AI models (X, Blog, HF, Try It) * Big CO LLMs + APIs * OpenAI releases Advanced Voice Mode to all & Mira Murati leaves OpenAI * Google updates Gemini 1.5-Pro-002 and 1.5-Flash-002 (Blog) * This weeks Buzz * Our free course is LIVE - more than 3000 already started learning how to build advanced RAG++ * Sponsoring tonights AI Tinkerers in Seattle, if you're in Seattle, come through for my demo * Voice & Audio * Meta also launches voice mode (demo) * Tools & Others * Project ORION - holographic glasses are here! (link) Meta gives us new LLaMas and AI hardware LLama 3.2 Multimodal 11B and 90B This was by far the biggest OpenSource release of this week (tho see below, may not be the "best"), as a rumored released finally came out, and Meta has given our Llama eyes! Coming with 2 versions (well 4 if you count the base models which they also released), these new MultiModal LLaMas were trained with an adapter architecture, keeping the underlying text models the same, and placing a vision encoder that was trained and finetuned separately on top. LLama 90B is among the best open-source mutlimodal models available — Meta team at launch These new vision adapters were trained on a massive 6 Billion images, including synthetic data generation by 405B for questions/captions, and finetuned with a subset of 600M high quality image pairs. Unlike the rest of their models, the Meta team did NOT claim SOTA on these models, and the benchmarks are very good but not the best we've seen (Qwen 2 VL from a couple of weeks ago, and MOLMO from today beat it on several benchmarks) With text-only inputs, the Llama 3.2 Vision models are functionally the same as the Llama 3.1 Text models; this allows the Llama 3.2 Vision models to be a drop-in replacement for Llama 3.1 8B/70B with added image understanding capabilities. Seems like these models don't support multi image or video as well (unlike Pixtral for example) nor tool use with images. Meta will also release these models on meta.ai and every other platform, and they cited a crazy 500 million monthly active users of their AI services across all their apps 🤯 which marks them as the leading AI services provider in the world now. Llama 3.2 Lightweight Models (1B/3B) The additional and maybe more exciting thing that we got form Meta was the introduction of the small/lightweight models of 1B and 3B parameters. Trained on up to 9T tokens, and distilled / pruned from larger models, these are aimed for on-device inference (and by device here we mean from laptops to mobiles to soon... glasses? more on this later) In fact, meta released an IOS demo, that runs these models, takes a group chat, summarizes and calls the calendar tool to schedule based on the conversation, and all this happens on device without the info leaving to a larger model. They have also been