Dr. Kaoutar El Maghraoui

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Dr. Kaoutar El Maghraoui

Dr. Kaoutar El Maghraoui

@kaoutarTech

Computer Scientist, Researcher, Science and Technology Lover, and Loving Mom.

NY Katılım Eylül 2013
448 Takip Edilen663 Takipçiler
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Katyayani Shukla
Katyayani Shukla@aibytekat·
Instead of watching Netflix, watch this interview of Anthropic’s CEO
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Rohan Paul
Rohan Paul@rohanpaul_ai·
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 than 10× compared to unoptimized models. 🤯 'Scalable MatMul-free Language Modeling' Concludes that it is possible to create the first scalable MatMul-free LLM that achieves performance on par with state-of-the-art Transformers at billion-parameter scales. 📌 The proposed MatMul-free LLM replaces MatMul operations in dense layers with ternary accumulations using weights constrained to {-1, 0, +1}. This reduces computational cost and memory utilization while preserving network expressiveness. 📌 To remove MatMul from self-attention, the Gated Recurrent Unit (GRU) is optimized to rely solely on element-wise products, creating the MatMul-free Linear GRU (MLGRU) token mixer. The MLGRU simplifies the GRU by removing hidden-state related weights, enabling parallel computation, and replacing remaining weights with ternary matrices. 📌 For MatMul-free channel mixing, the Gated Linear Unit (GLU) is adapted to use BitLinear layers with ternary weights, eliminating expensive MatMuls while maintaining effectiveness in mixing information across channels. 📌 The paper introduces a hardware-efficient fused BitLinear layer that optimizes RMSNorm and BitLinear operations. By fusing these operations and utilizing shared memory, training speed improves by 25.6% and memory consumption reduces by 61% over an unoptimized baseline. 📌 Experimental results show that the MatMul-free LLM achieves competitive performance compared to Transformer++ baselines on downstream tasks, with the performance gap narrowing as model size increases. The scaling law projections suggest MatMul-free LLM can outperform Transformer++ in efficiency and potentially in loss when scaled up. 📌 A custom FPGA accelerator is built to exploit the lightweight operations of the MatMul-free LLM. The accelerator processes billion-parameter scale models at 13W beyond human-readable throughput, demonstrating the potential for brain-like efficiency in future lightweight LLMs.
Rohan Paul tweet media
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Ayish hussain
Ayish hussain@AAbubakar43601·
@jacksonhinklle Hedge's letter to the children in Gaza.
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Dr. Kaoutar El Maghraoui
Dr. Kaoutar El Maghraoui@kaoutarTech·
Check out our newly published work about the open-source Toolkit for In-memory computing: Using the IBM analog in-memory hardware acceleration kit for neural network training and inference pubs.aip.org/aip/aml/articl…
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Mr. Joseph DeGennaro
Mr. Joseph DeGennaro@YHSDeGennaro·
Congrats to @YClassof2024 Zayneb Cherif for achieving 3rd place at recent IBM/IEEE AI Compute Symposium Poster Session. Zayneb is a member of our @YHSSciRes program under the direction of our outstanding educators Mr. Rubeo & Mr. Seweryn.🌽🏆 @GOLLISZJOHN @earthscifanatic
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Fahad A. AlTuwaym
Fahad A. AlTuwaym@FT_288·
We are the believers ♥️♥️🇲🇦 #WorldCup2022 #المغرب_اسبانيا
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𝐌𝐨𝐬𝐞𝐬 𝐍𝐠𝐢𝐠𝐞
An appreciation Tweet for the 31-year-old Morocco Goalkeeper, Yassine Bounou Bono. Stopper!
𝐌𝐨𝐬𝐞𝐬 𝐍𝐠𝐢𝐠𝐞 tweet media
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IBM Research
IBM Research@IBMResearch·
IBM Quantum Summit 2022 kicks off tomorrow morning at 9:00am ET in New York City. Stay tuned for some major quantum announcements from our annual flagship event.
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ClevelandClinicNews
ClevelandClinicNews@CleClinicNews·
Construction has started on the IBM Quantum System on our main campus. It will be the first quantum computer in healthcare, aimed at accelerating the pace of medical research. Read more about our partnership with @IBMResearch: cle.clinic/3CEERUt
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Latest in space
Latest in space@latestinspace·
BREAKING 🚨: Jupiter is now at its closest to Earth since 1963, and it won't be this close for another 107 years
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