ThursdAI - The top AI news from the past week

著者： 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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  • ThursdAI - Sep 19 - 👑 Qwen 2.5 new OSS king LLM, MSFT new MoE, Nous Research's Forge announcement, and Talking AIs in the open source!

    ThursdAI - Sep 19 - 👑 Qwen 2.5 new OSS king LLM, MSFT new MoE, Nous Research's Forge announcement, and Talking AIs in the open source!
    2024/09/19
    Hey folks, Alex here, back with another ThursdAI recap – and let me tell you, this week's episode was a whirlwind of open-source goodness, mind-bending inference techniques, and a whole lotta talk about talking AIs! We dove deep into the world of LLMs, from Alibaba's massive Qwen 2.5 drop to the quirky, real-time reactions of Moshi. We even got a sneak peek at Nous Research's ambitious new project, Forge, which promises to unlock some serious LLM potential. So grab your pumpkin spice latte (it's that time again isn't it? 🍁) settle in, and let's recap the AI awesomeness that went down on ThursdAI, September 19th! ThursdAI is brought to you (as always) by Weights & Biases, we still have a few spots left in our Hackathon this weekend and our new advanced RAG course is now released and is FREE to sign up!TL;DR of all topics + show notes and links* Open Source LLMs * Alibaba Qwen 2.5 models drop + Qwen 2.5 Math and Qwen 2.5 Code (X, HF, Blog, Try It)* Qwen 2.5 Coder 1.5B is running on a 4 year old phone (Nisten)* KyutAI open sources Moshi & Mimi (Moshiko & Moshika) - end to end voice chat model (X, HF, Paper)* Microsoft releases GRIN-MoE - tiny (6.6B active) MoE with 79.4 MMLU (X, HF, GIthub)* Nvidia - announces NVLM 1.0 - frontier class multimodal LLMS (no weights yet, X)* Big CO LLMs + APIs* OpenAI O1 results from LMsys do NOT disappoint - vibe checks also confirm, new KING llm in town (Thread)* NousResearch announces Forge in waitlist - their MCTS enabled inference product (X)* This weeks Buzz - everything Weights & Biases related this week* Judgement Day (hackathon) is in 2 days! Still places to come hack with us Sign up* Our new RAG Course is live - learn all about advanced RAG from WandB, Cohere and Weaviate (sign up for free)* Vision & Video* Youtube announces DreamScreen - generative AI image and video in youtube shorts ( Blog)* CogVideoX-5B-I2V - leading open source img2video model (X, HF)* Runway, DreamMachine & Kling all announce text-2-video over API (Runway, DreamMachine)* Runway announces video 2 video model (X)* Tools* Snap announces their XR glasses - have hand tracking and AI features (X)Open Source Explosion!👑 Qwen 2.5: new king of OSS llm models with 12 model releases, including instruct, math and coder versionsThis week's open-source highlight was undoubtedly the release of Alibaba's Qwen 2.5 models. We had Justin Lin from the Qwen team join us live to break down this monster drop, which includes a whopping seven different sizes, ranging from a nimble 0.5B parameter model all the way up to a colossal 72B beast! And as if that wasn't enough, they also dropped Qwen 2.5 Coder and Qwen 2.5 Math models, further specializing their LLM arsenal. As Justin mentioned, they heard the community's calls for 14B and 32B models loud and clear – and they delivered! "We do not have enough GPUs to train the models," Justin admitted, "but there are a lot of voices in the community...so we endeavor for it and bring them to you." Talk about listening to your users!Trained on an astronomical 18 trillion tokens (that’s even more than Llama 3.1 at 15T!), Qwen 2.5 shows significant improvements across the board, especially in coding and math. They even open-sourced the previously closed-weight Qwen 2 VL 72B, giving us access to the best open-source vision language models out there. With a 128K context window, these models are ready to tackle some serious tasks. As Nisten exclaimed after putting the 32B model through its paces, "It's really practical…I was dumping in my docs and my code base and then like actually asking questions."It's safe to say that Qwen 2.5 coder is now the best coding LLM that you can use, and just in time for our chat, a new update from ZeroEval confirms, Qwen 2.5 models are the absolute kings of OSS LLMS, beating Mistral large, 4o-mini, Gemini Flash and other huge models with just 72B parameters 👏 Moshi: The Chatty Cathy of AIWe've covered Moshi Voice back in July, and they have promised to open source the whole stack, and now finally they did! Including the LLM and the Mimi Audio Encoder! This quirky little 7.6B parameter model is a speech-to-speech marvel, capable of understanding your voice and responding in kind. It's an end-to-end model, meaning it handles the entire speech-to-speech process internally, without relying on separate speech-to-text and text-to-speech models.While it might not be a logic genius, Moshi's real-time reactions are undeniably uncanny. Wolfram Ravenwolf described the experience: "It's uncanny when you don't even realize you finished speaking and it already starts to answer." The speed comes from the integrated architecture and efficient codecs, boasting a theoretical response time of just 160 milliseconds!Moshi uses (also open sourced) Mimi neural audio codec, and achieves 12.5 Hz representation with just 1.1 kbps bandwidth.You can download it and run on your own machine or give it a try here just don't expect a masterful conversationalist ...
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    1 時間 56 分
  • 🔥 📅 ThursdAI - Sep 12 - OpenAI's 🍓 is called 01 and is HERE, reflecting on Reflection 70B, Google's new auto podcasts & more AI news from last week

    🔥 📅 ThursdAI - Sep 12 - OpenAI's 🍓 is called 01 and is HERE, reflecting on Reflection 70B, Google's new auto podcasts & more AI news from last week
    2024/09/13
    March 14th, 2023 was the day ThursdAI was born, it was also the day OpenAI released GPT-4, and I jumped into a Twitter space and started chaotically reacting together with other folks about what a new release of a paradigm shifting model from OpenAI means, what are the details, the new capabilities. Today, it happened again! Hey, it's Alex, I'm back from my mini vacation (pic after the signature) and boy am I glad I decided to not miss September 12th! The long rumored 🍓 thinking model from OpenAI, dropped as breaking news in the middle of ThursdAI live show, giving us plenty of time to react live! But before this, we already had an amazing show with some great guests! Devendra Chaplot from Mistral came on and talked about their newly torrented (yeah they did that again) Pixtral VLM, their first multi modal! , and then I had the honor to host Steven Johnson and Raiza Martin from NotebookLM team at Google Labs which shipped something so uncannily good, that I legit said "holy fu*k" on X in a reaction! So let's get into it (TL;DR and links will be at the end of this newsletter)OpenAI o1, o1 preview and o1-mini, a series of new "reasoning" modelsThis is it folks, the strawberries have bloomed, and we finally get to taste them. OpenAI has released (without a waitlist, 100% rollout!) o1-preview and o1-mini models to chatGPT and API (tho only for tier-5 customers) 👏 and are working on releasing 01 as well.These are models that think before they speak, and have been trained to imitate "system 2" thinking, and integrate chain-of-thought reasoning internally, using Reinforcement Learning and special thinking tokens, which allows them to actually review what they are about to say before they are saying it, achieving remarkable results on logic based questions.Specifically you can see the jumps in the very very hard things like competition math and competition code, because those usually require a lot of reasoning, which is what these models were trained to do well. New scaling paradigm Noam Brown from OpenAI calls this a "new scaling paradigm" and Dr Jim Fan explains why, with this new way of "reasoning", the longer the model thinks - the better it does on reasoning tasks, they call this "test-time compute" or "inference-time compute" as opposed to compute that was used to train the model. This shifting of computation down to inference time is the essence of the paradigm shift, as in, pre-training can be very limiting computationally as the models scale in size of parameters, they can only go so big until you have to start building out a huge new supercluster of GPUs to host the next training run (Remember Elon's Colossus from last week?). The interesting thing to consider here is, while current "thinking" times are ranging between a few seconds to a minute, imagine giving this model hours, days, weeks to think about new drug problems, physics problems 🤯.Prompting o1 Interestingly, a new prompting paradigm has also been introduced. These models now have CoT (think "step by step") built-in, so you no longer have to include it in your prompts. By simply switching to o1-mini, most users will see better results right off the bat. OpenAI has worked with the Devin team to test drive these models, and these folks found that asking the new models to just give the final answer often works better and avoids redundancy in instructions.The community of course will learn what works and doesn't in the next few hours, days, weeks, which is why we got 01-preview and not the actual (much better) o1. Safety implications and future plansAccording to Greg Brokman, this inference time compute also greatly helps with aligning the model to policies, giving it time to think about policies at length, and improving security and jailbreak preventions, not only logic. The folks at OpenAI are so proud of all of the above that they have decided to restart the count and call this series o1, but they did mention that they are going to release GPT series models as well, adding to the confusing marketing around their models. Open Source LLMs Reflecting on Reflection 70BLast week, Reflection 70B was supposed to launch live on the ThursdAI show, and while it didn't happen live, I did add it in post editing, and sent the newsletter, and packed my bag, and flew for my vacation. I got many DMs since then, and at some point couldn't resist checking and what I saw was complete chaos, and despite this, I tried to disconnect still until last night. So here's what I could gather since last night. The claims of a llama 3.1 70B finetune that Matt Shumer and Sahil Chaudhary from Glaive beating Sonnet 3.5 are proven false, nobody was able to reproduce those evals they posted and boasted about, which is a damn shame. Not only that, multiple trusted folks from our community, like Kyle Corbitt, Alex Atallah have reached out to Matt in to try to and get to the bottom of how such a thing would happen, and how claims like these could have been made in good ...
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    1 時間 58 分
  • 📅 ThursdAI - Sep 5 - 👑 Reflection 70B beats Claude 3.5, Anthropic Enterprise 500K context, 100% OSS MoE from AllenAI, 1000 agents world sim, Replit agent is the new Cursor? and more AI news

    📅 ThursdAI - Sep 5 - 👑 Reflection 70B beats Claude 3.5, Anthropic Enterprise 500K context, 100% OSS MoE from AllenAI, 1000 agents world sim, Replit agent is the new Cursor? and more AI news
    2024/09/06
    Welcome back everyone, can you believe it's another ThursdAI already? And can you believe me when I tell you that friends of the pod Matt Shumer & Sahil form Glaive.ai just dropped a LLama 3.1 70B finetune that you can download that will outperform Claude Sonnet 3.5 while running locally on your machine? Today was a VERY heavy Open Source focused show, we had a great chat w/ Niklas, the leading author of OLMoE, a new and 100% open source MoE from Allen AI, a chat with Eugene (pico_creator) about RWKV being deployed to over 1.5 billion devices with Windows updates and a lot more. In the realm of the big companies, Elon shook the world of AI by turning on the biggest training cluster called Colossus (100K H100 GPUs) which was scaled in 122 days 😮 and Anthropic announced that they have 500K context window Claude that's only reserved if you're an enterprise customer, while OpenAI is floating an idea of a $2000/mo subscription for Orion, their next version of a 100x better chatGPT?! TL;DR* Open Source LLMs * Matt Shumer / Glaive - Reflection-LLama 70B beats Claude 3.5 (X, HF)* Allen AI - OLMoE - first "good" MoE 100% OpenSource (X, Blog, Paper, WandB)* RWKV.cpp is deployed with Windows to 1.5 Billion devices* MMMU pro - more robust multi disipline multimodal understanding bench (proj)* 01AI - Yi-Coder 1.5B and 9B (X, Blog, HF)* Big CO LLMs + APIs* Replit launches Agent in beta - from coding to production (X, Try It)* Ilya SSI announces 1B round from everyone (Post)* Cohere updates Command-R and Command R+ on API (Blog)* Claude Enterprise with 500K context window (Blog)* Claude invisibly adds instructions (even via the API?) (X)* Google got structured output finally (Docs)* Amazon to include Claude in Alexa starting this October (Blog)* X ai scaled Colossus to 100K H100 GPU goes online (X)* DeepMind - AlphaProteo new paper (Blog, Paper, Video)* This weeks Buzz* Hackathon did we mention? We're going to have Eugene and Greg as Judges!* AI Art & Diffusion & 3D* ByteDance - LoopyAvatar - Audio Driven portait avatars (Page)Open Source LLMsReflection Llama-3.1 70B - new 👑 open source LLM from Matt Shumer / GlaiveAI This model is BANANAs folks, this is a LLama 70b finetune, that was trained with a new way that Matt came up with, that bakes CoT and Reflection into the model via Finetune, which results in model outputting its thinking as though you'd prompt it in a certain way. This causes the model to say something, and then check itself, and then reflect on the check and then finally give you a much better answer. Now you may be thinking, we could do this before, RefleXion (arxiv.org/2303.11366) came out a year ago, so what's new? What's new is, this is now happening inside the models head, you don't have to reprompt, you don't even have to know about these techniques! So what you see above, is just colored differently, but all of it, is output by the model without extra prompting by the user or extra tricks in system prompt. the model thinks, plans, does chain of thought, then reviews and reflects, and then gives an answer! And the results are quite incredible for a 70B model 👇Looking at these evals, this is a 70B model that beats GPT-4o, Claude 3.5 on Instruction Following (IFEval), MATH, GSM8K with 99.2% 😮 and gets very close to Claude on GPQA and HumanEval! (Note that these comparisons are a bit of a apples to ... different types of apples. If you apply CoT and reflection to the Claude 3.5 model, they may in fact perform better on the above, as this won't be counted 0-shot anymore. But given that this new model is effectively spitting out those reflection tokens, I'm ok with this comparison)This is just the 70B, next week the folks are planning to drop the 405B finetune with the technical report, so stay tuned for that! Kudos on this work, go give Matt Shumer and Glaive AI a follow! Allen AI OLMoE - tiny "good" MoE that's 100% open source, weights, code, logsWe've previously covered OLMO from Allen Institute, and back then it was obvious how much commitment they have to open source, and this week they continued on this path with the release of OLMoE, an Mixture of Experts 7B parameter model (1B active parameters), trained from scratch on 5T tokens, which was completely open sourced. This model punches above its weights on the best performance/cost ratio chart for MoEs and definitely highest on the charts of releasing everything. By everything here, we mean... everything, not only the final weights file; they released 255 checkpoints (every 5000 steps), the training code (Github) and even (and maybe the best part) the Weights & Biases logs! It was a pleasure to host the leading author of the OLMoE paper, Niklas Muennighoff on the show today, so definitely give this segment a listen, he's a great guest and I learned a lot! Big Companies LLMs + APIAnthropic has 500K context window Claude but only for Enterprise? Well, this sucks (unless you work for Midjourney, Airtable or Deloitte). Apparently ...
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    1 時間 45 分

あらすじ・解説

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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Alex Volkov
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