System Brings Deep Learning to “Internet of Things” Devices

Daniel Ackerman | MIT News Office Deep learning is everywhere. This branch of artificial intelligence curates your social media and serves your Google search results.


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Shrinking Deep Learning’s Carbon Footprint

Kim Martineau | MIT Quest for Intelligence In June 2020, OpenAI unveiled the largest language model in the world, a text-generating tool called GPT-3 that can write creative…


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Engineers Put Tens of Thousands of Artificial Brain Synapses on a Single Chip

Jennifer Chu | MIT News Office MIT engineers have designed a “brain-on-a-chip,” smaller than a piece of confetti, that is made from tens of thousands of artificial brain synapses…


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A Foolproof Way to Shrink Deep Learning Models

Kim Martineau | MIT Quest for Intelligence MIT researchers have proposed a technique for shrinking deep learning models that they say is simpler and produces more accurate results…


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Faster Video Recognition for the Smartphone Era

Kim Martineau | MIT Quest for Intelligence A new technique for training video recognition models is up to three times faster than current state-of-the-art methods while improving…


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Powerful Computer Vision Algorithms are Now Small Enough to Run on Your Phone

Karen Hao | MIT Technology Review Researchers have shrunk state-of-the-art computer vision models to run on low-power devices.


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Chip Design Drastically Reduces Energy Needed to Compute with Light

Rob Matheson | MIT News Office Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.


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Using AI to Make Better AI

Mark Anderson | IEEE Spectrum New approach brings faster, AI-optimized AI within reach for image recognition and other applications


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Kicking Neural Network Design Automation into High Gear

Rob Matheson | MIT News Office MIT researchers have developed an efficient algorithm that could provide a “push-button” solution for automatically designing fast-running neural…


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Securing the “Internet of Things” in the Quantum Age

Rob Matheson | MIT News Office Efficient chip enables low-power devices to run today’s toughest quantum encryption schemes.


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