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Food contains many bioactive molecules similar to anti-cancer drugs. ML can discover such components and design cancer-beating hyperfoods.


The food we eat contains thousands of bioactive molecules, some of which are similar to anti-cancer drugs. Modern machine learning techniques can help discover such components and help design “hyperfoods” that will let us live longer and healthier.

This autumn Kotaro Ando, a forty year-old farmer from Tara Town, Saga City (Japan) became the first customer to lease an asparagus picking robot from local agricultural high-tech startup Inaho Co. Ltd. Founded in 2017 and located in the coastal town of Kamakura, Inaho develops robots for agricultural and non-agricultural use. In January 2019, the company opened an office in Kashima (about 110 km from Tokyo) to market their autonomous robot to asparagus and cucumber farmers in Saga City and its surrounding areas. Kotaro Ando was one of these lucky asparagus farmers.

Researchers at the Samsung AI Center in Moscow (Russia) have recently presented interesting work called Living portraits: they made Mona Lisa and other subjects of photos and art alive using video of real people. They presented a framework for meta-learning of adversarial generative models called “Few-Shot Adversarial Learning”.

You can read more about details in the original paper.

Here we review this great implementation of the algorithm in PyTorch. The author of this implementation is Vincent Thévenin — research worker in De Vinci Innovation Center.

September 14, 2020 — The use of artificial intelligence (AI) in radiology to aid in image interpretation tasks is evolving, but many of the old factors and concepts from the computer-aided detection (CAD) era still remain, according to a Sunday talk at the Conference on Machine Intelligence in Medical Imaging (C-MIMI).

A lot has changed as the new era of AI has emerged, such as faster computers, larger image datasets, and more advanced algorithms — including deep learning. Another thing that’s changed is the realization of additional reasons and means to incorporate AI into clinical practice, according to Maryellen Giger, PhD, of the University of Chicago. What’s more, AI is also being developed for a broader range of clinical questions, more imaging modalities, and more diseases, she said.

At the same time, many of the issues are the same as those faced in the era of CAD. There are the same clinical tasks of detection, diagnosis, and response assessment, as well as the same concern of “garbage in, garbage out,” she said. What’s more, there’s the same potential for off-label use of the software, and the same methods for statistical evaluations.

When Sartre said hell is other people, he wasn’t living through 2020. Right now, other people are the only thing between us and species collapse. Not just the people we occasionally encounter behind fugly masks—but the experts and innovators out in the world, leading the way. The 17-year-old hacker building his own coronavirus tracker. The Google AI wonk un-coding machine bias. A former IT guy helping his community thwart surveillance. There are people everywhere, in and out … See More.


The scientists, technologists, artists, and chefs who are standing between us and species collapse.