Liam Li @liamcli
Research @Pokee_AI | PhD from @mldcmu | prev @DeterminedAI | ML expert specializing in large scale model development, AutoML, and MLOps. Joined February 2019-
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@Pokee_AI is now live with Nano Banana at pokee.ai ! Unparallel consistency in image editing with Pokee's prompt optimization and the fastest AI Agent in social media marketing across the internet! Publish to any platforms (@instagram, @YouTube , @tiktok_us ,…
GPT-5 is here—and Pokee AI is already integrated! We’ve already built it into Pokee AI to give you next-level performance right now. But Pokee AI is way more beyond GPT-5! At Pokee AI, we’ve built a full-scale productivity engine—not just with GPT‑5, but by intelligently…
🚀 Big news! Pokee AI just raised a $12M seed round—3x oversubscribed! Our mission: Automate every human workflow on the internet with frictionless AI agents. Public beta now live 👉 pokee.ai Here's what we're building and who's backing us 🧵👇
🧵 on surprising revelations from our study of specialized foundation models (FMs beyond vision/text): after evaluating dozens of scientific & time series FMs we found that most weren’t even competitive with simple supervised models, some with as little as 513 parameters. 1/n
Introducing Copilot Arena - Interactive coding evaluation in the wild. Our extension lets you test top models for free, right in VSCode. Let's vote and build the Copilot leaderboard! Download here: marketplace.visualstudio.com/items?itemName… Led by @iamwaynechi and @valeriechen_ at CMU. 1/🧵
Introducing Unified PDE Solvers (UPS), a step towards efficiently building foundation models for PDE solvers (arxiv.org/abs/2403.07187)! Starting from a pretrained LM, UPS tackles diverse spatiotemporal PDEs with SOTA accuracy, using ~20x less data and a single A6000! 🧵[1/x]
One of the clearest explanations I’ve seen of kv cache, continuous batching, paged attention, and mqa.
One of the clearest explanations I’ve seen of kv cache, continuous batching, paged attention, and mqa.
New blog post: how to make LLMs go fast! Want to understand how people are making LLMs go brrrrr? This post is a survey of lots of different LLM inference optimizations, ranging from "everyone uses this in prod" to "I cooked this up last week (but it seems to work)"
Chat with Mistral 7B Instruct v0.2 running locally in iphone and ipad. Now available in @AppStore. apps.apple.com/gb/app/mlc-cha…
phew, did our annual @UntappedVC LP summit yesterday! thought it'd be fun to share a few of our slides (w candid/cheeky commentary). 👇
The EU AI Act negotiations ended. One contentious issue was the regulation of foundation models, particularly open source ones. Kudos to the French, German, and Italian governments for not giving up on open source models. Juicy part: "The legislation ultimately included…
I'm moderating a plenary panel at #NeurIPS2023 entitled "LLMs: Beyond Scaling" with some amazing researchers. Please send or upvote any interesting questions: dory.app/events/2KZxWFP…
Is training deep neural nets from scratch about to become obsolete? Recent research indicates that the answer might be yes. Here's why... 📰: arxiv.org/abs/2302.05738 [1/5]
Super excited to share our work led by @JunhongShen1 on cross-modal fine-tuning! We show it's possible to adapt LLM to genomics, music, ECG, and tabular data with surprisingly strong results, often surpassing current SoTA. Check out the thread for more details!
Super excited to share our work led by @JunhongShen1 on cross-modal fine-tuning! We show it's possible to adapt LLM to genomics, music, ECG, and tabular data with surprisingly strong results, often surpassing current SoTA. Check out the thread for more details!
Excited to introduce 💠 𝗭𝗲𝗻𝗼, an ML evaluation framework for any data or model, from classification to image generation. Our goal is to create a standard tool for ML evaluation, like PyTest for testing or PyTorch for model dev. Learn more at zenoml.com (1/6)
1/ A large part of my job is producing detailed reports for commercial clients regarding how the ongoing pandemic will affect the market in the future. Weeks, months, years.
Can’t wait to attend @NeurIPSConf tomorrow, my first in-person conference in way too long! And excited to share this experience with several students / collaborators who are finally getting to present their work in person... 1/N
Thankful for @DeterminedAI putting collaboration and innovation above all else, and all the wonderful folks at @pachyderminc and @seldon_io. You all make my ML platform dreams a reality. 🤍
The essays that students turn in are about to get a lot better 😬 I just tried Moonbeam (app.gomoonbeam.com) and it produced an outline & credible undergraduate essay with just the prompt “Legitimation and startups.” And that is without human intervention, which would help
I've found it unexpectedly useful to memorize facts about systems I work with. Knowing these numbers allows one to 1. sanity check performance, 2. sketch out feasibility of technical solutions, and 3. reason about performance characteristics. Some examples below: (1/7)

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