내가 좋아할 만한 콘텐츠
Available on IEEE Xplore now: ieeexplore.ieee.org/document/10873…
Excited to present our work on extending Ising machines with Gaussian probabilistic bits this December at IEEE IEDM 2024 in San Francisco! Come check out our work on December 10th! iedm24.mapyourshow.com/8_0/sessions/s…
The universe is a beautifully consistent system of rules. Intelligence is the efficiency with which you can go from the output of these rules (what you can observe) back to the rules themselves.
Fei-Fei Li says language models are extremely limited. This @GoogleDeepMind paper makes almost the same point, just in the world of video. The models are just very advanced pattern matchers. They can recreate what looks like reality because they’ve seen so much data, but they…
Fei-Fei Li (@drfeifei) on limitations of LLMs. "There's no language out there in nature. You don't go out in nature and there's words written in the sky for you.. There is a 3D world that follows laws of physics." Language is purely generated signal.
Exciting news: #UCSB professors Michel H. Devoret and John M. Martinis have been awarded the Nobel Prize in physics 🏆
BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2025 #NobelPrize in Physics to John Clarke, Michel H. Devoret and John M. Martinis “for the discovery of macroscopic quantum mechanical tunnelling and energy quantisation in an electric circuit.”
I've just drafted a new blogpost "The Bitter Lesson's Bitter Lesson" Richard Sutton and Dwarkesh discussed the Bitter Lesson, where Richard argued that babies and animals don’t learn through imitation, so state-of-the-art LLMs are pursuing the wrong path by imitating humans…
Dwarkesh and I had a frank exchange of views. I hope we moved the conversation forward. Dwarkesh is a true gentleman.
After years of developing probabilistic hardware accelerators to implement advanced probabilistic algorithms, our interdisciplinary team is excited to share an important update. Our new study, "Pushing the Boundary of Quantum Advantage in Hard Combinatorial Optimization with…
This is interesting as a first large diffusion-based LLM. Most of the LLMs you've been seeing are ~clones as far as the core modeling approach goes. They're all trained "autoregressively", i.e. predicting tokens from left to right. Diffusion is different - it doesn't go left to…
We are excited to introduce Mercury, the first commercial-grade diffusion large language model (dLLM)! dLLMs push the frontier of intelligence and speed with parallel, coarse-to-fine text generation.
Interesting that the energy costs of ML are so high because we use chips to simulate optimizer dynamics in a high-dimensional parameter space. This requires lots of highly time-irreversible operations per unit time, which is thermodynamically expensive. Harnessing the actual…
Grateful to see our collaborative and interdisciplinary efforts recognized with the prestigious Misha Mahowald Prize.
It’s an incredible honor to receive this year’s Misha Mahowald Prize in Neuromorphic Engineering! 🎉 My deepest gratitude goes to the Jury for this recognition, to Dr. Misha Mahowald for pioneering the field that inspires our work, and to my amazing students and colleagues,…
It’s an incredible honor to receive this year’s Misha Mahowald Prize in Neuromorphic Engineering! 🎉 My deepest gratitude goes to the Jury for this recognition, to Dr. Misha Mahowald for pioneering the field that inspires our work, and to my amazing students and colleagues,…
Watch the Nobel Prize lectures in physics. See 2024 physics laureates John Hopfield and Geoffrey Hinton deliver their Nobel Prize lectures. Where are you watching from? #NobelPrize
My favorite book is The Beginning of Infinity. But it's not an easy read. I recently gifted it to a friend along with some notes to help her read it. Here they are in case it's useful for someone else: - Some chapters are easy to read, others are very complex but all are…
We need a new kind of async for loop in python:
Even though Newton's laws are deterministic, the behavior of many interacting bodies is so chaotic that it looks essentially "random." Statistical mechanics effectively says: why bother with all those complex trajectories? Just go ahead and replace them with truly random motion.
still the most compelling Figure 1 i've ever seen - from "Visualizing the Loss Landscape of Neural Nets" (2017)
Check out our recent work on physics-to-systems modeling of CMOS+X platforms, published open access in NPJ Spintronics!
Exploratory CMOS + X systems often require physics-based modeling, rather than compact models developed for highly mature semiconductor technologies. In a paper just out in NPJ Spintronics, we outline a modular circuit approach for CMOS + (X=spintronics & magnetism), tightly…
Exploratory CMOS + X systems often require physics-based modeling, rather than compact models developed for highly mature semiconductor technologies. In a paper just out in NPJ Spintronics, we outline a modular circuit approach for CMOS + (X=spintronics & magnetism), tightly…
Excited to present our work on extending Ising machines with Gaussian probabilistic bits this December at IEEE IEDM 2024 in San Francisco! Come check out our work on December 10th! iedm24.mapyourshow.com/8_0/sessions/s…
2024 physics laureate Geoffrey Hinton used a network developed by his co-laureate John Hopfield as the foundation for a new network: the Boltzmann machine. This can learn to recognise characteristic elements in a given type of data. The Boltzmann machine can be used to classify…
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