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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Fortifying the Future of Cryptography

Rob Matheson | MIT News Office Vinod Vaikuntanathan is using number theory and other mathematical concepts to fortify encryption so it can be used for new applications and stand…


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Lightmatter Aims to Reinvent AI-specific Chips with Photonic Computing and $11M in Funding

Devin Coldewey | TechCrunch It takes an immense amount of processing power to create and operate the “AI” features we all use so often, from playlist generation to voice…


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