Incredibly powerful, must-watch moment. Thank you, Eddie S. Glaude Jr..

Know the difference.

Two new websites that I'll be keeping handy for the foreseeable future: 🙌 tellina.rocks: translates natural language inputs into bash commands using TensorFlow 2.x 🐚 explainshell.com: beautiful, detailed manpage explanations for arbitrary shell commands

Them: GPT-3 is going to take over the job of artists everywhere, it must be stopped! GPT-3:

Without a doubt the most insightful interview I've seen with Trump. Everyone should take the time to watch this youtu.be/zaaTZkqsaxY

ML people: Do you have a tool in your current model training workflow that is a secret weapon? Maybe something that labels data automatically, autotunes hyper-parameters, simplifies testing or does feature extraction? Tell us your secrets :)

Our API now includes a brand new pipeline: zero-shot text classification This feature lets you classify sequences into the specified class names out-of-the-box w/o any additional training in a few lines of code! 🚀 Try it out (and share screenshots 📷): huggingface.co/facebook/bart-…

Powerful LMs such as GPT-3 and T5 have impressive ability to answer questions by continuing a textual prompt. However, how can we know when an LM knows the answer with confidence, and when it's making a random guess? Our new preprint asks this: phontron.com/paper/jiang20l… 1/N

Interested in AlphaFold 2? Read my piece on how good it actually is, how it works, and what it means for the scientific community and those of us working in computational biology: blopig.com/blog/2020/12/c…

So there's a lot of confusion about what Parler being kicked off of Amazon Web Services (Amazon Web Services) means. Let me do a quick thread to explain it to folks who aren't deep in the technical weeds...

We have this awesome function called sublots_mosaic where you can pass us a layout id'ed on name axd = plt.subplot_mosaic( """ ABD CCD """) matplotlib.org/stable/tutoria…

Conor Tiago Forte I like this one even better

If you have less than 3 hours to spare & want to learn (almost) everything about state-of-the-art explainable ML, this thread is for you! Below, I am sharing info about 4 of our recent tutorials on explainability presented at NeurIPS, AAAI, FAccT, and CHIL conferences. [1/n]

What are the one-year risks of COVID-19 for the general population? Possible outcomes are: – didn't catch it – infected, fully recovered – infected, long COVID – infected, death Here's a simple risk analysis for vaccinated and unvaccinated, based on published data.

This semester I've been teaching a new class on designing AI/ML products in MechSense, and as part of that class I have learned SO MUCH about great tools for ML rapid prototyping. Here are a few of my favorites:

The Stable Diffusion innovation just doesn't stop! Here's a new open-source model from the MONA that produces seamless tiling images: replicate.com/tommoore515/ma…

Planning is a key agentic AI design pattern in which we use a large language model (LLM) to autonomously decide on what sequence of steps to execute to accomplish a larger task. For example, if we ask an agent to do online research on a given topic, we might use an LLM to break

introducing: ComfyAGI 🧙‍♂️😉 we've taught Claude to generate ComfyUI workflows, so you can now build comfy workflows just with prompts... We're open sourcing the entire prompt chain for this (which is a glif too), so u can remix & adapt it join our Discord & come hack with us: