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The latest bombshell to hit the ChatGPT spectrum is a report that as of mid-February, the AI has 200 or more books under its virtual belt published in Amazon’s Kindle store. Reuters notes that some titles are “co-authored,” but many are published as-is with no human intervention other than to submit the content and collect the money.

As far as anyone can tell, Amazon is trying to be as transparent as possible with AI-generated titles by tagging them ChatGPT and creating an entirely new section called “Books about using ChatGPT, written entirely by ChatGPT.” However, those are just books that content creators admitted to using AI to complete the work. There could be hundreds more pumped out by less scrupulous “authors.”

Despite the transparency, some in the industry fear that real authors will be hurt by a tidal wave of quickly produced mediocre books that water down the pool of quality work published by human writers. One writer Reuters spoke with went from concept to published work in a matter of a few hours. It was a children’s book with ChatGPT producing the text, and another AI to generating “crude” drawings.

The days of ripping off a Band-Aid could soon be in the past, with scientists creating a new affordable, flexible electronic covering that not only speeds and wirelessly monitors healing but performs a disappearing act by being harmlessly absorbed into the body when its job is done.

“Although it’s an electronic device, the active components that interface with the wound bed are entirely resorbable,” said Northwestern University’s John A. Rogers, who co-led the study. “As such, the materials disappear naturally after the healing process is complete, thereby avoiding any damage to the tissue that could otherwise be caused by physical extraction.”

Electronic bandages are an emerging but by no means new technology, with earlier developments into bacteria-killing patches, motion-powered covers and even forays into smart dressings. But this dressing is the first bioresorbable bandage of its kind, delivering electrotherapy to wounds to accelerate healing by up to 30 per cent, and relaying data on the injured site’s condition to allow monitor of it from afar. The Northwestern scientists believe it could be a game-changer for diabetics and others who face serious complications from frequent and slow-healing sores.

The CRYSTALS-Kyber public-key encryption and key encapsulation mechanism recommended by NIST in July 2022 for post-quantum cryptography has been broken. Researchers from the KTH Royal Institute of Technology, Stockholm, Sweden, used recursive training AI combined with side channel attacks.

A side-channel attack exploits measurable information obtained from a device running the target implementation via channels such as timing or power consumption. The revolutionary aspect of the research (PDF) was to apply deep learning analysis to side-channel differential analysis.

“Deep learning-based side-channel attacks,” say the researchers, “can overcome conventional countermeasures such as masking, shuffling, random delays insertion, constant-weight encoding, code polymorphism, and randomized clock.”

For the first time, scientists have used machine learning to create brand-new enzymes, which are proteins that accelerate chemical reactions. This is an important step in the field of protein design, as new enzymes could have many uses across medicine and industrial manufacturing.

“Living organisms are remarkable chemists. Rather than relying on toxic compounds or extreme heat, they use enzymes to break down or build up whatever they need under gentle conditions. New enzymes could put renewable chemicals and biofuels within reach,” said senior author David Baker, professor of biochemistry at the University of Washington School of Medicine and recipient of the 2021 Breakthrough Prize in Life Sciences.

As reported Feb, 22 in the journal Nature, a team based at the Institute for Protein Design at UW Medicine devised algorithms that can create light-emitting enzymes called luciferases. Laboratory testing confirmed that the new enzymes can recognize specific chemicals and emit light very efficiently. This project was led by two postdoctoral scholars in the Baker Lab, Andy Hsien-Wei Yeh and Christoffer Norn.