ThursdAI - The top AI news from the past week

By: From Weights & Biases Join AI Evangelist Alex Volkov and a panel of experts to cover everything important that happened in the world of AI from the past week
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  • Every ThursdAI, Alex Volkov hosts a panel of experts, ai engineers, data scientists and prompt spellcasters on twitter spaces, as we discuss everything major and important that happened in the world of AI for the past week. Topics include LLMs, Open source, New capabilities, OpenAI, competitors in AI space, new LLM models, AI art and diffusion aspects and much more.

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Episodes
  • 📆 ThursdAI - Jan 9th - NVIDIA's Tiny Supercomputer, Phi-4 is back, Kokoro TTS & Moondream gaze, ByteDance SOTA lip sync & more AI news

    📆 ThursdAI - Jan 9th - NVIDIA's Tiny Supercomputer, Phi-4 is back, Kokoro TTS & Moondream gaze, ByteDance SOTA lip sync & more AI news
    Jan 10 2025
    Hey everyone, Alex here 👋This week's ThursdAI was a whirlwind of announcements, from Microsoft finally dropping Phi-4's official weights on Hugging Face (a month late, but who's counting?) to Sam Altman casually mentioning that OpenAI's got AGI in the bag and is now setting its sights on superintelligence. Oh, and NVIDIA? They're casually releasing a $3,000 supercomputer that can run 200B parameter models on your desktop. No big deal.We had some amazing guests this week too, with Oliver joining us to talk about a new foundation model in genomics and biosurveillance (yes, you read that right - think wastewater and pandemic monitoring!), and then, we've got some breaking news! Vik returned to the show with a brand new Moondream release that can do some pretty wild things. Ever wanted an AI to tell you where someone's looking in a photo? Now you can, thanks to a tiny model that runs on edge devices. 🤯So buckle up, folks, because we've got a ton to cover. Let's dive into the juicy details of this week's AI madness, starting with open source.03:10 TL;DR03:10 Deep Dive into Open Source LLMs10:58 MetaGene: A New Frontier in AI20:21 PHI4: The Latest in Open Source AI27:46 R Star Math: Revolutionizing Small LLMs34:02 Big Companies and AI Innovations42:25 NVIDIA's Groundbreaking Announcements43:49 AI Hardware: Building and Comparing Systems46:06 NVIDIA's New AI Models: LLAMA Neumatron47:57 Breaking News: Moondream's Latest Release50:19 Moondream's Journey and Capabilities58:41 Weights & Biases: New Evals Course01:08:29 NVIDIA's World Foundation Models01:08:29 ByteDance's LatentSync: State-of-the-Art Lip Sync01:12:54 Kokoro TTS: High-Quality Text-to-SpeechAs always, TL;DR section with links and show notes below 👇Open Source AI & LLMsPhi-4: Microsoft's "Small" Model Finally Gets its Official Hugging Face DebutFinally, after a month, we're getting Phi-4 14B on HugginFace. So far, we've had bootlegged copies of it, but it's finally officially uploaded by Microsoft. Not only is it now official, it's also officialy MIT licensed which is great!So, what's the big deal? Well, besides the licensing, it's a 14B parameter, dense decoder-only Transformer with a 16K token context length and trained on a whopping 9.8 trillion tokens. It scored 80.4 on math and 80.6 on MMLU, making it about 10% better than its predecessor, Phi-3 and better than Qwen 2.5's 79What’s interesting about phi-4 is that the training data consisted of 40% synthetic data (almost half!)The vibes are always interesting with Phi models, so we'll keep an eye out, notable also, the base models weren't released due to "safety issues" and that this model was not trained for multi turn chat applications but single turn use-casesMetaGene-1: AI for Pandemic Monitoring and Pathogen DetectionNow, this one's a bit different. We usually talk about LLMs in this section, but this is more about the "open source" than the "LLM." Prime Intellect, along with folks from USC, released MetaGene-1, a metagenomic foundation model. That's a mouthful, right? Thankfully, we had Oliver Liu, a PhD student at USC, and an author on this paper, join us to explain.Oliver clarified that the goal is to use AI for "biosurveillance, pandemic monitoring, and pathogen detection." They trained a 7B parameter model on 1.5 trillion base pairs of DNA and RNA sequences from wastewater, creating a model surprisingly capable of zero-shot embedding. Oliver pointed out that while using genomics to pretrain foundation models is not new, MetaGene-1 is, "in its current state, the largest model out there" and is "one of the few decoder only models that are being used". They also have collected 15T bae pairs but trained on 10% of them due to grant and compute constraints.I really liked this one, and though the science behind this was complex, I couldn't help but get excited about the potential of transformer models catching or helping catch the next COVID 👏rStar-Math: Making Small LLMs Math Whizzes with Monte Carlo Tree SearchAlright, this one blew my mind. A paper from Microsoft (yeah, them again) called "rStar-Math" basically found a way to make small LLMs do math better than o1 using Monte Carlo Tree Search (MCTS). I know, I know, it sounds wild. They took models like Phi-3-mini (a tiny 3.8B parameter model) and Qwen 2.5 3B and 7B, slapped some MCTS magic on top, and suddenly these models are acing the AIME 2024 competition math benchmark and scoring 90% on general math problems. For comparison, OpenAI's o1-preview scores 85.5% on math and o1-mini scores 90%. This is WILD, as just 5 months ago, it was unimaginable that any LLM can solve math of this complexity, then reasoning models could, and now small LLMs with some MCTS can!Even crazier, they observed an "emergence of intrinsic self-reflection capability" in these models during problem-solving, something they weren't designed to do. LDJ chimed in saying "we're going to see more papers showing these things emerging and caught naturally." ...
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    1 hr and 20 mins
  • 📆 ThursdAI - Jan 2 - is 25' the year of AI agents?

    📆 ThursdAI - Jan 2 - is 25' the year of AI agents?
    Jan 2 2025
    Hey folks, Alex here 👋 Happy new year!On our first episode of this year, and the second quarter of this century, there wasn't a lot of AI news to report on (most AI labs were on a well deserved break). So this week, I'm very happy to present a special ThursdAI episode, an interview with Joāo Moura, CEO of Crew.ai all about AI agents!We first chatted with Joāo a year ago, back in January of 2024, as CrewAI was blowing up but still just an open source project, it got to be the number 1 trending project on Github, and #1 project on Product Hunt. (You can either listen to the podcast or watch it in the embedded Youtube above)00:36 Introduction and New Year Greetings02:23 Updates on Open Source and LLMs03:25 Deep Dive: AI Agents and Reasoning03:55 Quick TLDR and Recent Developments04:04 Medical LLMs and Modern BERT09:55 Enterprise AI and Crew AI Introduction10:17 Interview with João Moura: Crew AI25:43 Human-in-the-Loop and Agent Evaluation33:17 Evaluating AI Agents and LLMs44:48 Open Source Models and Fin to OpenAI45:21 Performance of Claude's Sonnet 3.548:01 Different parts of an agent topology, brain, memory, tools, caching53:48 Tool Use and Integrations01:04:20 Removing LangChain from Crew01:07:51 The Year of Agents and Reasoning01:18:43 Addressing Concerns About AI01:24:31 Future of AI and Agents01:28:46 Conclusion and Farewell---Is 2025 "the year of AI agents"?AI agents as I remember them as a concept started for me a few month after I started ThursdAI ,when AutoGPT exploded. Was such a novel idea at the time, run LLM requests in a loop,(In fact, back then, I came up with a retry with AI concept and called it TrAI/Catch, where upon an error, I would feed that error back into the GPT api and ask it to correct itself. it feels so long ago!)AutoGPT became the fastest ever Github project to reach 100K stars, and while exciting, it did not work.Since then we saw multiple attempts at agentic frameworks, like babyAGI, autoGen. Crew AI was one of them that keeps being the favorite among many folks.So, what is an AI agent? Simon Willison, friend of the pod, has a mission, to ask everyone who announces a new agent, what they mean when they say it because it seems that everyone "shares" a common understanding of AI agents, but it's different for everyone.We'll start with Joāo's explanation and go from there. But let's assume the basic, it's a set of LLM calls, running in a self correcting loop, with access to planning, external tools (via function calling) and a memory or sorts that make decisions.Though, as we go into detail, you'll see that since the very basic "run LLM in the loop" days, the agents in 2025 have evolved and have a lot of complexity.My takeaways from the conversationI encourage you to listen / watch the whole interview, Joāo is deeply knowledgable about the field and we go into a lot of topics, but here are my main takeaways from our chat* Enterprises are adopting agents, starting with internal use-cases* Crews have 4 different kinds of memory, Long Term (across runs), short term (each run), Entity term (company names, entities), pre-existing knowledge (DNA?)* TIL about a "do all links respond with 200" guardrail* Some of the agent tools we mentioned* Stripe Agent API - for agent payments and access to payment data (blog)* Okta Auth for Gen AI - agent authentication and role management (blog)* E2B - code execution platform for agents (e2b.dev)* BrowserBase - programmatic web-browser for your AI agent* Exa - search grounding for agents for real time understanding* Crew has 13 crews that run 24/7 to automate their company* Crews like Onboarding User Enrichment Crew, Meetings Prep, Taking Phone Calls, Generate Use Cases for Leads* GPT-4o mini is the most used model for 2024 for CrewAI with main factors being speed / cost* Speed of AI development makes it hard to standardize and solidify common integrations.* Reasoning models like o1 still haven't seen a lot of success, partly due to speed, partly due to different way of prompting required.This weeks BuzzWe've just opened up pre-registration for our upcoming FREE evaluations course, featuring Paige Bailey from Google and Graham Neubig from All Hands AI (previously Open Devin). We've distilled a lot of what we learned about evaluating LLM applications while building Weave, our LLM Observability and Evaluation tooling, and are excited to share this with you all! Get on the listAlso, 2 workshops (also about Evals) from us are upcoming, one in SF on Jan 11th and one in Seattle on Jan 13th (which I'm going to lead!) so if you're in those cities at those times, would love to see you!And that's it for this week, there wasn't a LOT of news as I said. The interesting thing is, even in the very short week, the news that we did get were all about agents and reasoning, so it looks like 2025 is agents and reasoning, agents and reasoning!See you all next week 🫡TL;DR with links:* Open Source LLMs* HuatuoGPT-o1 - medical LLM designed for medical ...
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    1 hr and 31 mins
  • 📆 ThursdAI - Dec 26 - OpenAI o3 & o3 mini, DeepSeek v3 658B beating Claude, Qwen Visual Reasoning, Hume OCTAVE & more AI news

    📆 ThursdAI - Dec 26 - OpenAI o3 & o3 mini, DeepSeek v3 658B beating Claude, Qwen Visual Reasoning, Hume OCTAVE & more AI news
    Dec 27 2024
    Hey everyone, Alex here 👋I was hoping for a quiet holiday week, but whoa, while the last newsletter was only a week ago, what a looong week it has been, just Friday after the last newsletter, it felt like OpenAI has changed the world of AI once again with o3 and left everyone asking "was this AGI?" over the X-mas break (Hope Santa brought you some great gifts!) and then not to be outdone, DeepSeek open sourced basically a Claude 2.5 level behemoth DeepSeek v3 just this morning!Since the breaking news from DeepSeek took us by surprise, the show went a bit longer (3 hours today!) than expected, so as a Bonus, I'm going to release a separate episode with a yearly recap + our predictions from last year and for next year in a few days (soon in your inbox!) TL;DR* Open Source LLMs* CogAgent-9B (Project, Github)* Qwen QvQ 72B - open weights visual reasoning (X, HF, Demo, Project)* GoodFire Ember - MechInterp API - GoldenGate LLama 70B* 🔥 DeepSeek v3 658B MoE - Open Source Claude level model at $6M (X, Paper, HF, Chat)* Big CO LLMs + APIs* 🔥 OpenAI reveals o3 and o3 mini (Blog, X)* X.ai raises ANOTHER 6B dollars - on their way to 200K H200s (X)* This weeks Buzz* Two W&B workshops upcoming in January* SF - January 11* Seattle - January 13 (workshop by yours truly!)* New Evals course with Paige Bailey and Graham Neubig - pre-sign up for free* Vision & Video* Kling 1.6 update (Tweet)* Voice & Audio* Hume OCTAVE - 3B speech-language model (X, Blog)* Tools* OpenRouter added Web Search Grounding to 300+ models (X)Open Source LLMsDeepSeek v3 658B - frontier level open weights model for ~$6M (X, Paper, HF, Chat )This was absolutely the top of the open source / open weights news for the past week, and honestly maybe for the past month. DeepSeek, the previous quant firm from China, has dropped a behemoth model, a 658B parameter MoE (37B active), that you'd need 8xH200 to even run, that beats Llama 405, GPT-4o on most benchmarks and even Claude Sonnet 3.5 on several evals! The vibes seem to be very good with this one, and while it's not all the way beating Claude yet, it's nearly up there already, but the kicker is, they trained it with a very restricted compute, per the paper, with ~2K h800 (which is like H100 but with less bandwidth) for 14.8T tokens. (that's 15x cheaper than LLama 405 for comparison) For evaluations, this model excels on Coding and Math, which is not surprising given how excellent DeepSeek coder has been, but still, very very impressive! On the architecture front, the very interesting thing is, this feels like Mixture of Experts v2, with a LOT of experts (256) and 8+1 active at the same time, multi token prediction, and a lot optimization tricks outlined in the impressive paper (here's a great recap of the technical details)The highlight for me was, that DeepSeek is distilling their recent R1 version into this version, which likely increases the performance of this model on Math and Code in which it absolutely crushes (51.6 on CodeForces and 90.2 on MATH-500) The additional aspect of this is the API costs, and while they are going to raise the prices come February (they literally just swapped v2.5 for v3 in their APIs without telling a soul lol), the price performance for this model is just absurd. Just a massive massive release from the WhaleBros, now I just need a quick 8xH200 to run this and I'm good 😅 Other OpenSource news - Qwen QvQ, CogAgent-9B and GoldenGate LLamaIn other open source news this week, our friends from Qwen have released a very interesting preview, called Qwen QvQ, a visual reasoning model. It uses the same reasoning techniques that we got from them in QwQ 32B, but built with the excellent Qwen VL, to reason about images, and frankly, it's really fun to see it think about an image. You can try it hereand a new update to CogAgent-9B (page), an agent that claims to understand and control your computer, claims to beat Claude 3.5 Sonnet Computer Use with just a 9B model! This is very impressive though I haven't tried it just yet, I'm excited to see those very impressive numbers from open source VLMs driving your computer and doing tasks for you!A super quick word from ... Weights & Biases! We've just opened up pre-registration for our upcoming FREE evaluations course, featuring Paige Bailey from Google and Graham Neubig from All Hands AI. We've distilled a lot of what we learned about evaluating LLM applications while building Weave, our LLM Observability and Evaluation tooling, and are excited to share this with you all! Get on the listAlso, 2 workshops (also about Evals) from us are upcoming, one in SF on Jan 11th and one in Seattle on Jan 13th (which I'm going to lead!) so if you're in those cities at those times, would love to see you!Big Companies - APIs & LLMsOpenAI - introduces o3 and o3-mini - breaking Arc-AGI challenge, GQPA and teasing AGI? On the last day of the 12 days of OpenAI, we've got the evals of their upcoming o3 reasoning model (and o3-mini) and whoah. ...
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    1 hr and 36 mins

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