Researchers at MIT in the US and the Technische Universitat Berlin have built a optical neural network processor with embedded lasers that slashes the power consumption of large language model AI such as GPT4.0. Chen, Hamerly, and Englund have filed for a patent on the work, which was sponsored by the US Army Research Office […]
Optical AI processor to cut data centre power consumption Read More »
TOKYO – Aug 29, 2023 – NTT DATA, a global digital business and IT services leader, today announced that the University of Technology Sydney (UTS) and NTT DATA, together with NTT Research, Inc., NTT Ltd. and NTT DATA Romania, have agreed to partner and utilise NTT’s commercialised cryptography technology, Attribute Based Encryption (ABE) solution to
MIT system demonstrates greater than 100-fold improvement in energy efficiency and a 25-fold improvement in compute density compared with current systems. The current work is the latest achievement in a drumbeat of progress over the last few years by Englund and many of the same colleagues. For example, in 2019 an Englund team reported the
The surge of interest in the overall category of digital twins has led to some confusion, as tends to happen during “hype” cycles. A closer look at the cardiovascular bio-digital twin (one area of focus for my research organization) can help clarify matters. First, the existence of this niche says something. A bio-digital twin does
Bio-Digital Twin: Getting The Heart Right Read More »
NTT and NTT Research Also Contribute 15 Papers to Crypto 2023 Sunnyvale, Calif. – August 17, 2023 – NTT Research, Inc., a division of NTT (TYO:9432), today announced that a paper co-authored by Distinguished Scientist and Director of the Cryptography and Information Security (CIS) Lab Brent Waters has won an International Association for Cryptologic Research
PHI Lab Delivers 12 High-Impact Papers, 19 Talks in Three Months Sunnyvale, Calif. – August 10, 2023 – NTT Research, Inc., a division of NTT (TYO:9432), today announced that its Physics & Informatics (PHI) Lab continues to advance basic scientific knowledge in the areas of neural network, photonics and quantum science. In a three-month span,
A new processor that uses light, instead of electrons, has the potential to perform its computations up to 100 times more powerfully and efficiently than existing processors inside machine-learning computer systems. That’s according to a new USC and MIT study published in the journal Nature Photonics. Zaijun Chen of USC, Ryan Hamerly of NTT Research,
New Laser-Array Processor Could Vastly Improve AI Computing Efficiency Read More »
