Ashish Mehta @_ashish_m
Just curious. Philadelphia, PA Joined April 2014-
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Time’s always moving on. Nothing can stop it. The question is whether we use our time well or not. We can't do anything about the past, but what happens in the future depends on what we do now. We can create a happier future by remembering that in being human we are all the same.
Bernhard Scholkopf (@bschoelkopf) just published a single author paper titled "Causality for Machine Learning" (arxiv.org/abs/1911.10500); this should probably at the top of the reading list for many people interested in machine learning / AI; @yudapearl @eliasbareinboim
Here's Richard Feynman, in 1985, describing Douglas Lenat's heuristic-based system and its winning solutions. Reminds me of reinforcement learning efforts of today. Given objectives & constraints, algorithms may lead to unexpected consequences. Full clip: youtube.com/watch?v=ipRvjS…
The move towards bigger models + bigger data makes me worried about the career perspective of for ML researchers. At this point, it seems like you *have* to join a big company that has tremendous resources to make any progress.
@dwilliams999 "I am not sure that I exist, actually. I am all the writers that I have read, all the people that I have met, all the women that I have loved; all the cities I have visited." - Jorge Luis Borges
❤️🌲? We've got you covered x 20 million. share.teamtrees.org/542458515t #TeamTrees
"Mathematics is the language in which God has written the universe." -- Galileo Galilei (1564 - 1642)
.@Nestle you have created a #plasticmonster, end your reliance on throwaway plastic packaging and immediately phase out single-use plastics across your supply chains. #breakfreefromplastic
My talk at MSR is online now! on our findings and open problems in figuring out minimal assumptions that enable theoretical guarantees for RL. talk was meant to offer a minimalist view of RL accessible to learning theoreticians or even TCS audience. youtube.com/watch?v=SjO386… (1/2)
• Question. • Hypothesize. • Experiment. • Fail. • Learn. • Repeat.
"It is true that a mathematician who is not somewhat of a poet, will never be a perfect mathematician." - Karl Weierstrass (1815 - 1897)
Training ever bigger convnets and LSTMs on ever bigger datasets gets us closer to Strong AI -- in the same sense that building taller towers gets us closer to the moon.
An Introduction to Deep Reinforcement Learning (PDF book manuscript, Nov 2018) arxiv.org/abs/1811.12560
Same facts are compatible with any number of different theories ..
Our newest work on Multitask Soft Option Learning (MSOL) is out. By leveraging RL as Inference, we are able to overcome several challenges specific to this setting and even learn good option termination policies. With @nntsn @shimon8282, Andrew, Sid and Wendelin
[MIT News] "Teaching machines to reason about what they see: Researchers combine statistical and symbolic artificial intelligence techniques to speed learning and improve transparency." tinyurl.com/yy4d3xn5 @CBMM_MIT 's Josh Tenenbaum
The last days, a fascinating discussion has been happening on #econtwitter & #epitwitter abt #causalinference, pot outcomes, & dir acyclical graphs. Since #AcademicTwitter is great for open discourse, & bad at keeping all in 1 place, I thought I provide this public good.. 1/19
Seven Myths in Machine Learning Research crazyoscarchang.github.io/2019/02/16/sev…
For folks looking for a thorough intro to the mathematical foundations of reinforcement learning: Video lectures for Bertsekas’ course on RL and control are now available here: web.mit.edu/dimitrib/www/R…
"Due to our concerns about malicious applications of [Our model ... trained simply to predict the next word], we are not releasing the trained model" for the humanity, i feel now obliged to remove all the pretrained model weights i've made public so far. 😅
"Due to our concerns about malicious applications of [Our model ... trained simply to predict the next word], we are not releasing the trained model" for the humanity, i feel now obliged to remove all the pretrained model weights i've made public so far. 😅
GapFillTrader🇺🇸 @Irvroonor159
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99K Followers 8K Following Compiling in real-time, the race towards AGI. The Largest Show on X for AI. 🗞️ Get my daily AI analysis newsletter to your email 👉 https://t.co/6LBxO8215l
#buildinpublic @buildinpublic
52K Followers 2 Following Use hashtag #buildinpublic to share what you're working on. – Made by @marckohlbrugge. – Sponsored by https://t.co/vASwn0HF5o ⚡
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93K Followers 374 Following Senior AI Product Manager at Google | Open Source Awesome LLM Apps Repo (#1 GitHub with 70k+ stars) | Author of books on GPT-3 & Neural Search in Production
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165K Followers 0 Following Invented principles of meta-learning (1987), GANs (1990), Transformers (1991), very deep learning (1991), etc. Our AI is used many billions of times every day.
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