Deep Learning won't replace radiologists any time soon, but it sure looks like it's helping them and their patients. https://t.co/QB141zS292
— Yann LeCun (@ylecun) December 21, 2022
Deep Learning won't replace radiologists any time soon, but it sure looks like it's helping them and their patients. https://t.co/QB141zS292
— Yann LeCun (@ylecun) December 21, 2022
Holidays' reading list 📚🎁 Part 2
— Fermat's Library (@fermatslibrary) December 20, 2022
"The more comfortable we become with being stupid, the deeper we will wade into the unknown and the more likely we are to make big discoveries."
"The importance of stupidity in scientific research", an insightful read: https://t.co/iE404kMDkI pic.twitter.com/VF2vENr1fq
Blog Post (w/ @gail_w): On "Thinking Like Transformers"
— Sasha Rush (@srush_nlp) December 20, 2022
In which, I get a bit obsessed with learning how to code in Transformer lang🤖. https://t.co/Nb6G52vuiK
(You can follow along or do the exercises yourself in a colab notebook.) pic.twitter.com/Hk4aIxQr7l
Pretty eery: AI models learn to reflect user views back at them (since I figure getting low loss rewards monitoring the _context_ of whatever emitted the input tokens). Pretty weird to see it in the wild. LLMs seek to reflect the views of people that talk to them. https://t.co/gD5qbAwRUb
— Jack Clark (@jackclarkSF) December 19, 2022
Good reading on AI alignment, I've been wondering how one could steer LLMs with an equivalent of Three Laws of Robotics https://t.co/82X9F93qRw
— Andrej Karpathy (@karpathy) December 17, 2022
“It is the more personal pain of seeing a 5% GPU utilization number in production. I am offended by it.” 🔥
— hardmaru (@hardmaru) December 17, 2022
—@ID_AA_Carmack, reflecting on his resignation from Facebook. pic.twitter.com/P0D6zODNit
I don't claim TikTok is "better". I'm just trying to explain its success. There's a dark side to a scrolling UX that relies on our automatic actions rather than our explicit choices: it feeds our basest impulses. I've previously written about it here: https://t.co/wI5ezce9JT
— Arvind Narayanan @randomwalker@mastodon.social (@random_walker) December 15, 2022
Just read through state of AI report by McKinsey: https://t.co/fYhnZ2JGvX
— Sebastian Raschka (@rasbt) December 10, 2022
(As a researcher, it seems to be useful summary of how AI is *actually* used in industry.)
Interesting insights
1. Computer vision now ties with NLP for classification/understanding
1 of 4 pic.twitter.com/8FBhjjRJau
AI twitter had erupted in controversy over Meta’s release of the Galactica demo. Is it a dangerous product, or was it unnecessarily maligned with overblown fears of harm? Here’s my take. https://t.co/XlCIo3S0mf
— Andrew Ng (@AndrewYNg) November 28, 2022
“Defective Altruism” by @NathanJRobinson
— hardmaru (@hardmaru) November 15, 2022
I’m far from a leftist-socialist, but this article is a great read: https://t.co/FJvtFayru9
Many are lured into Effective Altruism by caring about the future only to discover the truth that EA people are very preoccupied with AGI x-risk. pic.twitter.com/qx8ZxsGDBB
You can read more about it in the following blog post by @DannyCEbanks: https://t.co/oHlAoqtSab
— Bojan Tunguz (@tunguz) November 5, 2022
Link to Prof. Alvarez’ CalTech profile: https://t.co/HdXau1uDVY#PoliticalScience #POlitics #SocialScience #DataScience #MachineLearning #NaturalLanguageProcessing #DS #ML #NLP
8/8
Over the past year and a half I’ve had the privilege of collaborating with a brilliant @Caltech Computational Political Science group centered around prof. @rmichaelalvarez.
— Bojan Tunguz (@tunguz) November 5, 2022
1/8 pic.twitter.com/Gg3xrhvSjH