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This small, secure identification label can verify almost anything.

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, UncategorizedMay 23, 202476Views0Likes0Comments
Researchers at MIT have developed a cryptographic ID tag that is significantly smaller, cheaper, and more secure than traditional radio frequency identification (RFID) tags. The new tag is based on the use of terahertz waves which are smaller and have much higher frequencies than radio waves. The innovation overcomes a major security flaw common with…

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This small, secure identification label can verify nearly everything.

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, UncategorizedMay 22, 202460Views0Likes0Comments
MIT researchers have created a secure and portable ID tag, utilizing terahertz waves, a technology considered superior compared to traditional RFIDs due to the improved security it offers. The team has bypassed the significant vulnerability of both RFID and terahertz tags, where a counterfeiter can remove the tag from an original item and transfer it…

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Method allows AI in peripheral devices to continuously update its knowledge over time.

Algorithms, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Internet of things, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Mobile devices, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedMarch 7, 202472Views0Likes0Comments
Machine learning models are widely used today in smart devices like smartphones, with diverse applications like autocorrecting keyboards or improved chatbot responses. However, fine-tuning these models requires considerable computational resources and transfers of data to and from cloud servers – which can pose both energy and security issues. The team of researchers from MIT and…

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