Computer chips
Computer chips

Computer chips

Artificial Intelligence Computer chips Computer science and technology Electrical engineering and computer science (EECS) Electronics Energy Materials science and engineering Microsystems Technology Laboratories MIT Schwarzman College of Computing MIT.nano Nanoscience and nanotechnology Research School of Engineering Sustainable computing

New materials could boost the energy efficiency of microelectronics

By stacking multiple active components based on new materials on the back end of a computer chip, this new approach reduces the amount of energy wasted during computation.

Artificial Intelligence Cleaner industry Collaboration Computer chips Electrical engineering and computer science (EECS) Electronics Energy efficiency Industry Microsystems Technology Laboratories MIT.nano Photonics Research Research Laboratory of Electronics School of Engineering Semiconductors Silicon Sustainable computing

Collaborating to advance research and innovation on essential chips for AI

Agreement between MIT Microsystems Technology Laboratories and GlobalFoundries aims to deliver power efficiencies for data centers and ultra-low power consumption for intelligent devices at the edge.

2-D Artificial Intelligence Computer chips DMSE Electronics Materials science and engineering Mechanical engineering Research School of Engineering Semiconductors

MIT engineers grow “high-rise” 3D chips

An electronic stacking technique could exponentially increase the number of transistors on chips, enabling more efficient AI hardware.

Artificial Intelligence Computer chips Computer science and technology Data Electrical engineering and computer science (EECS) Electronics machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Optics Photonics Research Research Laboratory of Electronics School of Engineering

Photonic processor could enable ultrafast AI computations with extreme energy efficiency

This new device uses light to perform the key operations of a deep neural network on a chip, opening the door to high-speed processors that can learn in real-time.

Artificial Intelligence Computer chips Computer science and technology Electrical Engineering & Computer Science (eecs) Electronics Internet Of Things machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research Research Laboratory of Electronics School of Engineering sensors Supply chains

This tiny, tamper-proof ID tag can authenticate almost anything

MIT engineers developed a tag that can reveal with near-perfect accuracy whether an item is real or fake. The key is in the glue on the back of the tag.

Artificial Intelligence Computer chips Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology cybersecurity Data Electrical Engineering & Computer Science (eecs) Electronics machine learning MIT Schwarzman College of Computing Privacy Research School of Engineering

Accelerating AI tasks while preserving data security

The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.