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
  • Summary

  • 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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Episodes
  • 📅 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
    Sep 6 2024
    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 hr and 45 mins
  • 📅 ThursdAI - Aug 29 - AI Plays DOOM, Cerebras breaks inference records, Google gives new Geminis, OSS vision SOTA & 100M context windows!?
    Aug 30 2024
    Hey, for the least time during summer of 2024, welcome to yet another edition of ThursdAI, also happy skynet self-awareness day for those who keep track :) This week, Cerebras broke the world record for fastest LLama 3.1 70B/8B inference (and came on the show to talk about it) Google updated 3 new Geminis, Anthropic artifacts for all, 100M context windows are possible, and Qwen beats SOTA on vision models + much more! As always, this weeks newsletter is brought to you by Weights & Biases, did I mention we're doing a hackathon in SF in September 21/22 and that we have an upcoming free RAG course w/ Cohere & Weaviate? TL;DR* Open Source LLMs * Nous DisTrO - Distributed Training (X , Report)* NousResearch/ hermes-function-calling-v1 open sourced - (X, HF)* LinkedIN Liger-Kernel - OneLine to make Training 20% faster & 60% more memory Efficient (Github)* Cartesia - Rene 1.3B LLM SSM + Edge Apache 2 acceleration (X, Blog)* Big CO LLMs + APIs* Cerebras launches the fastest AI inference - 447t/s LLama 3.1 70B (X, Blog, Try It)* Google - Gemini 1.5 Flash 8B & new Gemini 1.5 Pro/Flash (X, Try it)* Google adds Gems & Imagen to Gemini paid tier* Anthropic artifacts available to all users + on mobile (Blog, Try it)* Anthropic publishes their system prompts with model releases (release notes)* OpenAI has project Strawberry coming this fall (via The information)* This weeks Buzz* WandB Hackathon hackathon hackathon (Register, Join)* Also, we have a new RAG course w/ Cohere and Weaviate (RAG Course)* Vision & Video* Zhipu AI CogVideoX - 5B Video Model w/ Less 10GB of VRAM (X, HF, Try it)* Qwen-2 VL 72B,7B,2B - new SOTA vision models from QWEN (X, Blog, HF)* AI Art & Diffusion & 3D* GameNgen - completely generated (not rendered) DOOM with SD1.4 (project)* FAL new LORA trainer for FLUX - trains under 5 minutes (Trainer, Coupon for ThursdAI)* Tools & Others* SimpleBench from AI Explained - closely matches human experience (simple-bench.com)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.Open SourceLet's be honest - ThursdAI is a love letter to the open-source AI community, and this week was packed with reasons to celebrate.Nous Research DiStRO + Function Calling V1Nous Research was on fire this week (aren't they always?) and they kicked off the week with the release of DiStRO, which is a breakthrough in distributed training. You see, while LLM training requires a lot of hardware, it also requires a lot of network bandwidth between the different GPUs, even within the same data center. Proprietary networking solutions like Nvidia NVLink, and more open standards like Ethernet work well within the same datacenter, but training across different GPU clouds has been unimaginable until now. Enter DiStRo, a new decentralized training by the mad geniuses at Nous Research, in which they reduced the required bandwidth to train a 1.2B param model from 74.4GB to just 86MB (857x)! This can have massive implications for training across compute clusters, doing shared training runs, optimizing costs and efficiency and democratizing LLM training access! So don't sell your old GPUs just yet, someone may just come up with a folding@home but for training the largest open source LLM, and it may just be Nous! Nous Research also released their function-calling-v1 dataset (HF) that was used to train Hermes-2, and we had InterstellarNinja who authored that dataset, join the show and chat about it. This is an incredible unlock for the open source community, as function calling become a de-facto standard now. Shout out to the Glaive team as well for their pioneering work that paved the way!LinkedIn's Liger Kernel: Unleashing the Need for Speed (with One Line of Code)What if I told you, that whatever software you develop, you can add 1 line of code, and it'll run 20% faster, and require 60% less memory? This is basically what Linkedin researches released this week with Liger Kernel, yes you read that right, Linkedin, as in the website you career related posts on! "If you're doing any form of finetuning, using this is an instant win"Wing Lian - AxolotlThis absolutely bonkers improvement in training LLMs, now works smoothly with Flash Attention, PyTorch FSDP and DeepSpeed. If you want to read more about the implementation of the triton kernels, you can see a deep dive here, I just wanted to bring this to your attention, even if you're not technical, because efficiency jumps like these are happening all the time. We are used to seeing them in capabilities / intelligence, but they are also happening on the algorithmic/training/hardware side, and it's incredible to see!Huge shoutout to Byron and team at Linkedin for this unlock, check out their Github if you want to get involved!Qwen-2 VL - SOTA image and video understanding + open weights mini VLMYou may already know that we love the folks at Qwen here on ThursdAI, not only ...
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    1 hr and 35 mins
  • 📅 AI21 Jamba 1.5, DIY Meme Faces, 8yo codes with AI and a Doomsday LLM Device?!
    Aug 22 2024
    Hey there, Alex here with an end of summer edition of our show, which did not disappoint. Today is the official anniversary of stable diffusion 1.4 can you believe it? It's the second week in the row that we have an exclusive LLM launch on the show (after Emozilla announced Hermes 3 on last week's show), and spoiler alert, we may have something cooking for next week as well!This edition of ThursdAI is brought to you by W&B Weave, our LLM observability toolkit, letting you evaluate LLMs for your own use-case easilyAlso this week, we've covered both ends of AI progress, doomerist CEO saying "Fck Gen AI" vs an 8yo coder and I continued to geek out on putting myself into memes (I promised I'll stop... at some point) so buckle up, let's take a look at another crazy week: TL;DR* Open Source LLMs * AI21 releases Jamba1.5 Large / Mini hybrid Mamba MoE (X, Blog, HF)* Microsoft Phi 3.5 - 3 new models including MoE (X, HF)* BFCL 2 - Berkley Function Calling Leaderboard V2 (X, Blog, Leaderboard)* NVIDIA - Mistral Nemo Minitron 8B - Distilled / Pruned from 12B (HF)* Cohere paper proves - code improves intelligence (X, Paper)* MOHAWK - transformer → Mamba distillation method (X, Paper, Blog)* AI Art & Diffusion & 3D* Ideogram launches v2 - new img diffusion king 👑 + API (X, Blog, Try it) * Midjourney is now on web + free tier (try it finally)* Flux keeps getting better, cheaper, faster + adoption from OSS (X, X, X)* Procreate hates generative AI (X)* Big CO LLMs + APIs* Grok 2 full is finally available on X - performs well on real time queries (X)* OpenAI adds GPT-4o Finetuning (blog)* Google API updates - 1000 pages PDFs + LOTS of free tokens (X)* This weeks Buzz* Weights & Biases Judgement Day SF Hackathon in September 21-22 (Sign up to hack)* Video * Hotshot - new video model - trained by 4 guys (try it, technical deep dive)* Luma Dream Machine 1.5 (X, Try it) * Tools & Others* LMStudio 0.0.3 update - local RAG, structured outputs with any model & more (X)* Vercel - Vo now has chat (X)* Ark - a completely offline device - offline LLM + worlds maps (X)* Ricky's Daughter coding with cursor video is a must watch (video)The Best of the Best: Open Source Wins with Jamba, Phi 3.5, and Surprise Function Calling HeroesWe kick things off this week by focusing on what we love the most on ThursdAI, open-source models! We had a ton of incredible releases this week, starting off with something we were super lucky to have live, the official announcement of AI21's latest LLM: Jamba.AI21 Officially Announces Jamba 1.5 Large/Mini – The Powerhouse Architecture Combines Transformer and Mamba While we've covered Jamba release on the show back in April, Jamba 1.5 is an updated powerhouse. It's 2 models, Large and Mini, both MoE and both are still hybrid architecture of Transformers + Mamba that try to get both worlds. Itay Dalmedigos, technical lead at AI21, joined us on the ThursdAI stage for an exclusive first look, giving us the full rundown on this developer-ready model with an awesome 256K context window, but it's not just the size – it’s about using that size effectively. AI21 measured the effective context use of their model on the new RULER benchmark released by NVIDIA, an iteration of the needle in the haystack and showed that their models have full utilization of context, as opposed to many other models.“As you mentioned, we’re able to pack many, many tokens on a single GPU. Uh, this is mostly due to the fact that we are able to quantize most of our parameters", Itay explained, diving into their secret sauce, ExpertsInt8, a novel quantization technique specifically designed for MoE models. Oh, and did we mention Jamba is multilingual (eight languages and counting), natively supports structured JSON, function calling, document digestion… basically everything developers dream of. They even chucked in citation generation, as it's long context can contain full documents, your RAG app may not even need to chunk anything, and the citation can cite full documents!Berkeley Function Calling Leaderboard V2: Updated + Live (link)Ever wondered how to measure the real-world magic of those models boasting "I can call functions! I can do tool use! Look how cool I am!" 😎? Enter the Berkeley Function Calling Leaderboard (BFCL) 2, a battleground where models clash to prove their function calling prowess.Version 2 just dropped, and this ain't your average benchmark, folks. It's armed with a "Live Dataset" - a dynamic, user-contributed treasure trove of real-world queries, rare function documentations, and specialized use-cases spanning multiple languages. Translation: NO more biased, contaminated datasets. BFCL 2 is as close to the real world as it gets.So, who’s sitting on the Function Calling throne this week? Our old friend Claude 3.5 Sonnet, with an impressive score of 73.61. But breathing down its neck is GPT 4-0613 (the OG Function Calling master) with 73.5. That's right, the one released a year ago, the first one ...
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    1 hr and 42 mins

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