Jason Eshraghian
@jasoneshraghian
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assistant professor @ucsc / neuromorphic engineer & filmmaker
Santa Cruz, CA
Joined July 2015
Thoroughly enjoyed the hour I spent with @ucsc's @jasoneshraghian talking about some of the areas of crossover between neuromorphic models/hardware and mainstream deep learning: https://t.co/e5rBJO299h
eetimes.com
Crossover between mainstream deep learning and neuromorphic computing may find useful applications for brain-inspired models and hardware.
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A Survey of Latent Reasoning Nice overview on the emerging field of latent reasoning. Great read for AI devs. (bookmark it)
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Hybrid architectures mix linear & full attention in LLMs. But which linear attention is best? This choice has been mostly guesswork. In our new work, we stop guessing. We trained, open-sourced 72 MODELS (340M & 1.3B) to dissect what truly makes a hybrid model tick🧶
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[1/7] Excited to share our new survey on Latent Reasoning! The field is buzzing with methods—looping, recurrence, continuous thoughts—but how do they all relate? We saw a need for a unified conceptual map. 🧵 📄 Paper: https://t.co/BWhB5b08JY 💻 Github: https://t.co/JFAm1FRaPW
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🥁 And the top #BaskinEngineering research story of 2024 is...? Developing a high-performing large language model (like ChatGPT) that runs on the energy needed to power a lightbulb! 💡 Led by Assistant Professor @jasoneshraghian. Read more:
news.ucsc.edu
UC Santa Cruz researchers show that it is possible to eliminate the most computationally expensive element of running large language models, called matrix multiplication, while maintaining performa...
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A paper authored by #BaskinEngineering undergrads Ruhai Lin and Ridger Zhu has been selected for the Best Paper Award at the 17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip (@MCSoC_symposium) — they are advised by prof @jasoneshraghian. Congrats!
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Excited for @NeurIPSConf in Vancouver (Dec 9-15)! Join us at the @NeuroAI_NeurIPS workshop on Dec 14 for fascinating keynotes exploring the intersection of neuroscience & AI. Let’s chat, share ideas, and connect—see you there! 🙌 https://t.co/TkEnTV5zgN
neuroai-workshop.github.io
Examining the fusion of neuroscience and AI: unlocking brain-inspired algorithms, advancing biological and artificial intelligence
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🌟 Thrilled to be at @NeurIPSConf in Vancouver (Dec 9-15)! Don’t miss our @NeuroAI_NeurIPS workshop on Dec 14 with an incredible lineup of keynotes. Stop by, join the discussions, and let’s connect! 🙌 https://t.co/HeAB8cbqmo
neuroai-workshop.github.io
Examining the fusion of neuroscience and AI: unlocking brain-inspired algorithms, advancing biological and artificial intelligence
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Excited to share that our paper Evaluation and mitigation of cognitive biases in medical language models was published in @npjDigitalMed In this work, we ask the question: can LLMs be easily fooled with simple cognitive bias-inducing prompts during patient diagnosis? To
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It has been an incredible experience organizing the @NeuroAI_NeurIPS workshop. Join us on December 14th at #NeurIPS2024 to explore the amazing research from the authors of our accepted papers, fusing Neuroscience and AI! For more details:
neuroai-workshop.github.io
Examining the fusion of neuroscience and AI: unlocking brain-inspired algorithms, advancing biological and artificial intelligence
📢Update: The peer-review is complete for NeuroAI workshop at @NeurIPSConf which took 31. Some stats: Submissions 113 Accepred papers 43 Accpetance rate 38% Total reviews 349 Unfortunatley, some good papers didn't make it but we had some constraints to work with. 1/3
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#Neuromorphic #computing just got more accessible! Our work on a Neuromorphic Intermediate Representation (NIR) is out in @SpringerNature Communications. We demonstrate interoperability with 11 platforms. And more to come! https://t.co/dEnqKMdL2C A thread 🧵 1/5
nature.com
Nature Communications - Neuromorphic software and hardware solutions vary widely, challenging interoperability and reproducibility. Here, authors establish a representation for neuromorphic...
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🚨NeuroAI researchers! ⏰5 days left for #NeuroAI workshop submissions! 🌟Awards: Spotlight papers: 1 student author gets free workshop registration, Top paper: 1 lucky student flies for free!✈️ 🔗submit here: https://t.co/qcwsH64xkX
#NeurIPS2024 #CallForPapers
openreview.net
Welcome to the OpenReview homepage for NeurIPS 2024 Workshop NeuroAI
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🚨We have extended the paper submission deadline for our NeuroAI workshop @NeurIPSConf to 23:59, Sept 9 (AoE)! For more details and travel awards on offer: https://t.co/1wuQjXwVya Nomination form for reviewers: https://t.co/Nms3MLJtQJ Follow @NeuroAI_NeurIPS for updates.
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An accompanying News & Views by @jasoneshraghian and colleagues is also available! https://t.co/BXtiBrFcvC ➡️ https://t.co/G1YDmXfKJY
nature.com
Nature Computational Science - According to a recent study, a small network consisting of four leaky integrate-and-fire neurons can reproduce the behavior of a single Hodgkin–Huxley neuron,...
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🚨📷We are organizing the 1st NeuroAI workshop at #NeurIPS2024! 📷 https://t.co/Z9gdMED6yY Submission deadline: 7th September 2024
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📢We're delighted to organise NeuroAI workshop at this year's @NeurIPSConf 2024 (excuse the typo in the graphic). Accepting submissions (4 pages + supp): https://t.co/pBJUoAeJLm Highlight: In-person panel with Yoshua Bengio and Karl Friston Follow @NeuroAI_NeurIPS for details
neuroai-workshop.github.io
Examining the fusion of neuroscience and AI: unlocking brain-inspired algorithms, advancing biological and artificial intelligence
🚨📷We are organizing the 1st NeuroAI workshop at #NeurIPS2024! 📷 https://t.co/Z9gdMED6yY Submission deadline: 7th September 2024
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Telluride Neuromorphic Cognition & Engineering workshop time.
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💡#BaskinEngineering Prof. Jason Eshraghian (@jasoneshraghian) & team developed an energy efficient way to run AI language models by eliminating matrix multiplication - which has important implications for the future of green computing. Via @arstechnica
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While there are some conceptual similarities between the just released absolutely amazing paper "Scalable MatMul-free Language Modeling" which eliminates the regular Matrix Multiplication and the earlier released paper (in Feb-2024) "The Era of 1-bit LLMs: All Large Language
This is really a 'WOW' paper. 🤯 Claims that MatMul operations can be completely eliminated from LLMs while maintaining strong performance at billion-parameter scales and by utilizing an optimized kernel during inference, their model’s memory consumption can be reduced by more
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If this is accurate, then NVIDIA's grip on the tech industry has just vanished. Matrix matrix multiplication (MatMul) is notoriously computationally difficult, which is why it's offloaded to GPUs. If MatMul can be avoided, then it's not just leveling the playing field. It's
This is really a 'WOW' paper. 🤯 Claims that MatMul operations can be completely eliminated from LLMs while maintaining strong performance at billion-parameter scales and by utilizing an optimized kernel during inference, their model’s memory consumption can be reduced by more
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