jeshragh
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‘Future-guided’ AI improves seizure prediction
Engineers developed a deep learning method that manipulates time to make better predictions.
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Hybrid AI Models Blend Deep Learning With Neuromorphic Ideas
EE Times explores Assistant Professor of Electrical and Computer Engineering Jason Eshraghian’s perspective on how traditional deep learning methods and brain-inspired computing methods are influencing each other in ways that are pushing forward modern artificial intelligence.
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Chancellor’s 2024 innovation awards honor excellence in research and impact
The recipients include innovators who have created breakthroughs in knowledge and technology that are improving our world and community partners.
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A Greener Solution for Artificial Intelligence
A new large language model developed at UCSC removes math from the equation, giving artificial intelligence a more sustainable, greener future.
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Researchers run high-performing large language model on the energy needed to power a lightbulb
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 performance.
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Brain-inspired AI code library passes major milestone, new paper offers perspective on future of field
UCSC Assistant Professor of Electrical and Computer Engineering Jason Eshraghian’s open source code library for brain-inspired deep learning, called “snnTorch,” has surpassed 100,000 downloads and is used in a wide variety of projects. A new paper details the code and offers a perspective on the future of the field.
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SpikeGPT: researcher releases code for largest-ever spiking neural network for language generation
Assistant Professor of Electrical and Computer Engineering Jason Eshraghian and two students recently released the open-sourced code for the largest language-generating spiking neural network ever, named SpikeGPT.
