maybe: shivam @kaffeinated
training models @spotify, former matrix multiplier @twitter @x cortex, nyu. techno-optimist. probably on a bike 🚲☕. London Joined October 2012-
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We wrote a book about representation learning! It’s fully open source, available and readable online, and covers everything from theoretical foundations to practical algorithms. 👷♂️ We’re hard at work updating the content for v2.0, and would love your feedback and contributions
A lot of younger people who’re new to the industry ask me how to do “networking”. How do you go from knowing no one in San Francisco to having a network of people that you can do business with, learn from, hire, etc. The trick is I never set out to “network”. Maybe due to…
it's called encoder-decoder for a reason
I have never even slightly wavered in my position that Trump is bad and stupid
this image has singlehandedly saved me from so much overthinking
companies like Facebook record every imaginable interaction their users have with the platform. they log each of your clicks and taps. they keep track of how long your gaze lingered on a post, whether you were on the same WiFi as that woman who might be your friend, which…
Sure, you could use AI to summarize papers and explain them at a level anyone could understand... or you can turn the abstracts into music videos for no reason. The tools are not perfect yet, but the disparate elements (consistent characters, lip syncing, etc.) are evolving fast
There's only so much attention available in a day. Invest it in enthusiasm, wonder, and progress.
It's kind of predictable that it would get defined down, but it's still wild that "AI Agent" went from meaning "AI that can act autonomously to achieve a goal by planning, executing and self-correcting when it makes mistakes" to "a wrapper that calls an LLM a bunch of times"
It's kind of predictable that it would get defined down, but it's still wild that "AI Agent" went from meaning "AI that can act autonomously to achieve a goal by planning, executing and self-correcting when it makes mistakes" to "a wrapper that calls an LLM a bunch of times"
This is what they call "an agent."
Our latest CS336 Language Modeling from Scratch lectures are now available! View the entire playlist here: youtube.com/playlist?list=…
This is actually how it feels. Remember feature engineering?
This is actually how it feels. Remember feature engineering?
Seeing text-to-text regression work for Google’s massive compute cluster (billion $$ problem!) was the final result to convince us we can reward model literally any world feedback. Paper: arxiv.org/abs/2506.21718 Code: github.com/google-deepmin… Just train a simple encoder-decoder…
``An Audio-centric Multi-task Learning Framework for Streaming Ads Targeting on Spotify,'' Shivam Verma, Vivian Chen, Darren Mei, ift.tt/ixew4HW
I’ve independently verified this, twice, and have to spoil the thread to say “Any photo outdoors can be trivially location matched in a fashion you’d assume would imply capabilities of an intelligence agency. If that is news to you, feel free to incorporate it into decisions.”
I’ve independently verified this, twice, and have to spoil the thread to say “Any photo outdoors can be trivially location matched in a fashion you’d assume would imply capabilities of an intelligence agency. If that is news to you, feel free to incorporate it into decisions.”
I shared a controversial take the other day at an event and I decided to write it down in a longer format: I’m afraid AI won't give us a "compressed 21st century". The "compressed 21st century" comes from Dario's "Machine of Loving Grace" and if you haven’t read it, you probably…
Our new AI mechanistic interpretability paper shows that LLMs are surprisingly clever: representing 2-digit numbers on a line is noisy, so they represent them on a generalized helix to get better addition accuracy, seemingly exploiting modular addition digit by digit:
Our new AI mechanistic interpretability paper shows that LLMs are surprisingly clever: representing 2-digit numbers on a line is noisy, so they represent them on a generalized helix to get better addition accuracy, seemingly exploiting modular addition digit by digit:
learning lin algebra 11 years ago was one of the most fun and retrospectively smartest decisions of my life
learning lin algebra 11 years ago was one of the most fun and retrospectively smartest decisions of my life
I don't have too too much to add on top of this earlier post on V3 and I think it applies to R1 too (which is the more recent, thinking equivalent). I will say that Deep Learning has a legendary ravenous appetite for compute, like no other algorithm that has ever been developed…
I don't have too too much to add on top of this earlier post on V3 and I think it applies to R1 too (which is the more recent, thinking equivalent). I will say that Deep Learning has a legendary ravenous appetite for compute, like no other algorithm that has ever been developed…
The start of AI spring
Luca (also on the oth... @__lucab
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VCs Congratulating Th... @VCBrags
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113K Followers 1K Following CEO @youdotcom MP @aixventuresHQ Before: Stanford Adj Prof in AI/NLP, Chief Scientist at Salesforce, MetaMind
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1.1M Followers 275 Following AGI at Keen Technologies, former CTO Oculus VR, Founder Id Software and Armadillo Aerospace
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210K Followers 5K Following Partner @MenloVentures. Formerly founding team @glean, @Google Search. @Cornell CS. Tweets about tech, immigration, India, fitness and search.
Luca (also on the oth... @__lucab
2K Followers 2K Following former @NIST AI Fellow and @UCBerkeley Tech Policy Co-founder of Twitter's Machine Learning Ethics team (RIP) Opinionated about 🇮🇹 food Tweet with Typos
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Machine Learning Stre... @MLStreetTalk
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1K Followers 887 Following All the power of creation right at our fingertips. Making models @bfl_ml https://t.co/xMaJiOl7Y0
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Karthik A Sankararama... @karthikabinav
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davidad 🎇 @davidad
20K Followers 9K Following Programme Director @ARIA_research | accelerate mathematical modelling with AI and categorical systems theory » build safe transformative AI » cancel heat death
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