stateoftheart.ai

Hello NeurIPS and Hello World, we are back and excited to launch Stateoftheart AI!... an open-data and free platform that facilitates the collaborative development of AI by mapping and visualizing its progress, evolution, & frontier. Explore more at stateoftheart.ai (1/4)

Awesome! check it out

Team of 3 engineers open for remote work. US time zones.

We are exploring the possibility of an acquihire of our assets and/or our engineering team. Please reach to campero@mit.edu if you are interested.

Announcing the NeurIPS Data-Centric AI workshop! This will be the premier event for academic research on Data-Centric AI. Deadline for research article submissions is Sep 30th. Check it out! datacentricai.org

🧠 Would you like to learn about Graph Neural Networks? Stanford is organizing a workshop with leaders of academia and industry. 🤖 The schedule looks amazing and will be streamed for free! You can register at snap.stanford.edu/graphlearning-…

@StanfordHAI Interesting report here.

NEW: This comprehensive report investigates foundation models (e.g. BERT, GPT-3), which are engendering a paradigm shift in AI. 100+ scholars across 10 departments at Stanford scrutinize their capabilities, applications, and societal consequences. bit.ly/3xZPFYK

@KordingLab @neuromatch congratulations NMA 2021!

And with the last party of the last timezone of the last @neuromatch academy course (DL) all I can do is express my gratitude to the wonderful team and participants. So much learn. So much community. much ❤️,🦖

stateoftheart.ai/models Check out our Models & lineage graphs - and along with papers or tasks/datasets, add your own to our #OpenSource collections! stateoftheart.ai/models #AI #ML #DL

@ethancaballero Let's see where this goes!

Stanford's ~entire AI Department has just released a 200 page 100 author Neural Scaling Laws Manifesto. They're pivoting to positioning themselves as #1 at academic ML Scaling (e.g. GPT-4) research. "On the Opportunities and Risks of Foundation Models" arxiv.org/abs/2108.07258

I really really liked the question: "Why we have a brain in the first place?" to start the tutorial for today at @neuromatch DL course. Amazing material reviewing "representations" and self-supervised learning, thanks @tyrell_turing !

ICYMI: @StateoftheartAI Newsletter 54, with a focus of computational neuroscience & computer vision. FT: SOTA's Evolution of Models view: medium.com/stateofthearta… #ML #AI #NeuromatchAcademy

Second week of #Neuromatch DL is done where students have learned about basics of Convnets, RNNs, Attention, & Generative models. It's now time to decompress for the 2nd time and attend professional development sessions on Saturday (August-14). Details in 🧵

Debuting another new audio release! Listen to @sarahookr and @cinjoncin talk about Sara's paper - Characterising Bias in Compressed Models. Find the audio and transcript at depthfirstlearning.com/2021/Sara-Hook…. Some choice quotes in the thread 👇

#otd in 1991 Tim Berners-Lee first posted on an online newsgroup about a project he was working on called "The World Wide Web."

Concept maps 💯 via #NeuromatchAcademy Deep Learning @neuromatch deeplearning.neuromatch.io/tutorials/intr…

Thanks to the help of some interns, many of my videos have now been adapted into a written/interactive form. The clip below shows an example of one interactive elements made for the neural networks series by @PullJosh. If you have a moment, take a look. 3blue1brown.com