stateoftheart.ai
@StateoftheartAI
An open-data and free platform built by the research community to facilitate the collaborative development of AI
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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)
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-…
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
stateoftheart.ai/models Check out our Models & lineage graphs - and along with papers or tasks/datasets, add your own to our #OpenSource collections! #AI #ML #DL
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
Congratulations to those making it through week one of @neuromatch #NMA deep learning!
#Neuromatch DL Brain Inspired Zoom-Out audio-only podcast starts today with Module 1‼ Listen to Amita Kapoor (@Kapoor_Amita), Lyle Ungar (@LyleUngar), & Surya Ganguli (@SuryaGanguli) talk about basics of Deep Learning with Paul Middlebrooks (@pgmid) 🚀🚀 braininspired.co/podcast/nma-4/
Writing code is about making your computer do what you need. Writing good code is about enabling teams of strangers 5 years from now to make their computers do what they need.
#Neuromatch vs. Brain Inspired third zoom out podcast is out now 🚀🚀 @pgmid dives into stochastic processes with @yael_niv, @KordingLab, @gershbrain, and @behrenstimb braininspired.co/podcast/nma-3/
🧵We are pleased to announce the ICML 2021 paper awards. Congratulations to all authors! Test of the Time Award from ICML 2011: • Max Welling and Yee Whye Teh 📜Bayesian Learning via Stochastic Gradient Langevin Dynamics
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