Nihal Singh @nihalssingh
PhD Candidate @UCSBengineering 🎓◦Translating Spin models and Neural networks to scalable probabilistic computers 💻⚛️◦@bitspilaniindia nihalssingh.github.io Santa Barbara, CA Joined February 2018-
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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…
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… https://t.co/HEQZha3vQp
Sean Carroll on entropy and the origin of life
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…
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…
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.
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,…
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!
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…
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…
This year’s #NobelPrize laureate in physics John Hopfield created an associative memory that can store and reconstruct images and other types of patterns in data. The Hopfield network can store patterns and has a method for recreating them. When the network is given an…
# explaining llm.c in layman terms Training Large Language Models (LLMs), like ChatGPT, involves a large amount of code and complexity. For example, a typical LLM training project might use the PyTorch deep learning library. PyTorch is quite complex because it implements a very…
.@KeremCamsari @nihalssingh et al. design a heterogeneous and energy-efficient #hardware combining stochastic magnetic tunnel junction based #probabilistic #bits with versatile field programmable gate arrays for #probabilistic #computing @NatureComms nature.com/articles/s4146…
.@KeremCamsari @nihalssingh et al. design a heterogeneous and energy-efficient #hardware combining stochastic magnetic tunnel junction based #probabilistic #bits with versatile field programmable gate arrays for #probabilistic #computing @NatureComms nature.com/articles/s4146…

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bhavyaps? @bhavsirrelevant
524 Followers 108 Following I was sayi- ARE YOU TIRED OF ADS?? GET AD FREE MUSIC WITH SPOTIFY PREMIUM
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321 Followers 224 Following i dont have any real reason to hate dora, except that she's ugly, which is exactly why i hate all of you.
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