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Mistral released a new Mixture of Experts (M.O.E.) model, which combines different models fine-tuned for specific tasks. The model outperforms GPT 3.5 and provides better reasoning abilities. It was open-sourced with an Apache 2.0 license, making it usable for commercial purposes. The model also introduced the concept of sparse architecture, which allows for parallel processing and efficient inference.
Together announced the HANIN architecture, which aims to overcome the limitations of transformers on longer sequences. The architecture shows better performance on longer sequences and lower inference times. Together also introduced state-space models like Mamba, which further improves performance on lower-complexity sequences. The release of these new architectures demonstrates the continuous advancements in the open source community.
Ego, a new decoding method, was introduced, delivering faster token outputs and providing a better user experience. It shows a 3x improvement in decoding speed. Quiq, a state-of-the-art quantization and compression technique, was also mentioned, offering better compression rates for models. These updates highlight the advancements in enhancing user experience and model efficiency.
Phi 2.0, the latest model from Microsoft, performed impressively well on reasoning and provides resistance to bias. It's a smaller model without instruction and fine-tuning, yet it exhibits remarkable capabilities. Although the model has been compared to Gemini architecture, a direct comparison with Gemini Nano has not been possible yet. Phi 2.0 brings promising characteristics to smaller models and demonstrates efficient and effective reasoning abilities.
Gemini Pro API is now available and includes models like Gemini Pro, Gemini Ultra, and Gemini Nano. These models offer significant improvements in image and text inference. The Gemini Pro model is especially noteworthy, showing a 42% gain over local inference on laptops. The pricing is competitive and Gemini Pro API has already sparked competition in the market.
Intel has launched its fifth generation Xeon processor specifically designed for AI. This processor offers a 42% performance gain in local inference, making on-device AI even more accessible.
OpenAI has open-sourced code for week-to-strong alignment, allowing researchers and developers to explore this important technique. They have also announced a 10 million grant program for those working on superhuman AI alignment. These initiatives reflect OpenAI's dedication to transparency and collaborative research.
NewRips 2021, one of the largest conferences in AI, wrapped up this week with thousands of researchers and industry leaders attending. Notable moments include Jan LeCun's talk on open assistant, Andrew Ng's presentation, and the poster sessions where researchers showcased their work. The conference also featured numerous parties to facilitate networking and collaboration between attendees.
Wow what a week. I think Iāve reached to a level that Iām not phased by incredible weeks or days that happen in AI, but Iā¦ guess I still have much to learn!
TL;DR of everything we covered (aka Show Notes)
* Open Source LLMs
* Mixtral MoE - 8X7B experts dropped with a magnet link again (Announcement, HF, Try it)
* Mistral 0.2 instruct (Announcement, HF)
* Upstage Solar 10B - Tops the HF leaderboards (Announcement)
* Together -Striped Hyena architecture and new models (Announcement)
* EAGLE - a new decoding method for LLMs (Announcement, Github)
* Deci.ai - new SOTA 7B model
* Phi 2.0 weights are available finally from Microsoft (HF)
* QuiP - LLM quantization & Compression (link)
* Big CO LLMs + APIs
* Gemini Pro access over API (Announcement, Thread)
* Uses character pricing not token
* Mistral releases API inference server - La Platforme (API docs)
* Together undercuts Mistral with serving Mixtral by 70% and announces OAI compatible API
* OpenAI is open sourcing again - Releasing Weak-2-strong generalization paper and github! (announcement)
* Vision
* Gemini Pro api has vision AND video capabilities (API docs)
* AI Art & Diffusion
* Stability announces Zero123 - Zero Shot image to 3d model (Thread)
* Imagen 2 from google (link)
* Tools & Other
* Optimus from Tesla is coming, and it looks incredible
This week started on Friday, as we saw one of the crazier single days in the history of OSS AI that I can remember, and Iāve been doing this now for .. jesus, 9 months!
In a single say, we saw a new Mistral model release called Mixtral, which is a Mixture of Experts (like GPT4 is rumored to be) of 8x7B Mistrals, and beats GPT3.5, we saw a completely new architecture that competes with Transformers called HYENA from Tri Dao and Together.xyz + 2 new models trained with that architecture, we saw a new SoTA 2-bit quantization method called QuiP from cornell AND a new 3x faster decoding method for showing tokens to users after an LLM has done āthinkingā.
And the best thing? All those advancements are stackable! What a day!
Then I went to NeurIPS2023 (which is where I am right now, writing these words!), which I cover at length at the second part of the podcast, but figured Iād write about it here as well, since it was such a crazy experience.
NeurIPS is the biggest AIML conference, I think they estimated 15K people from all over the world attending! Of course this brings many companies to sponsor, raise booths, give out swag and try to record!
Of course with my new position at Weights & Biases I had to come as well and experience this for myself!
Many of the attendees are customers of ours, and I was not expecting this amount of love given, just an incredible stream of people coming up to the booth, and saying how much they love the product!
So I manned the booth, did interviews and live streams, and connected with a LOT of folks and I gotta say, this whole NeurIPS thing is quite incredible from the ability to meet people!
I hung out with folks from Google, Meta, Microsoft, Apple, Weighs & Biases, Stability, Mistral, HuggingFace and PHD students and candidates from most of the top universities in the world, from KAIST to MIT and Stanford, Oslo and Shaghai, it's really a worldwide endeavor!
I also got to meet many of the leading figures in AI, all of whom I had to come up to and say hi, shake their hand, introduce myself (and ThursdAI) and chat about what they or their team released and presents at the conference! Truly an unforgettable experience!
Of course, This Weeksā Buzz is that, everyone here loves W&B, from the PHD students, to literally every big LLM lab! They all came up to us (yes yes, even researches at Google who kinda low-key hate their internal tooling) and told us how awesome the experience was! (besides Xai folks, Jimmy wasnāt that impressed haha) and of course I got to practice the pitch so many times, since I manned the W&B booth!
Please do listen to the above podcast, thereās so much detail thatās in there that doesnāt get up on the newsletter, as itās impossible to cover all, but it was a really fun conversation, including my excited depiction of this weeks NOLA escapades!
I think Iāll end here, cause I can go on and on about the parties (There were literally 7 at the same time last night, Google, Stability, OpenAI, Runway, and Iām sure there were a few more I wasnāt invited to!) and about New Orleans food (itās my first time here, I ate a soft shell deep fried crab and turtle soup!) and I still have the poster sessions to go to and workshops! I will report more on my X account and the Weights & Biases X account, so stay tuned for that there, and as always, thanks for tuning in, reading and sharing ThursdAI with your friends š«”
P.S - Still canāt really believe I get to do this full time now and share this journey with all of you, bringing you all with me to SF, and now NeurIPS and tons of other places and events in the future!
ā Alex Volkov, AI Evangelist @ Weights & Biases, Host of ThursdAI š«”
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