Medical imaging generates an enormous amount of data that is impossible to manually analyze. With advances in artificial intelligence (AI) researchers are now looking at how this technology can be used to help manage and simplify the analysis of large 3D microscopy image datasets. In this SelectScience article, we speak with Jianxu Chen, head of the new Analysis of Microscopic BIOMedical Images (AMBIOM*) group at ISAS. Chen discusses how his group is developing scalable, AI-based image analysis algorithms to help support disease studies. Chen also explores some current trends in laboratories adopting AI and machine learning.

Machine Learning is the most significant consumer of 21st-century art. Human has moved to the back of the audience. The story concerns the unlimited consumption of art by machine learning models. Art datasets are "swallowed" thoughtlessly by AI models. The generated images and compositions are pure visual cocaine for the eyes.

According to several studies by Intel spanning 2018, 2019, and 2020, AI and edge computing make it possible to positively identify up to 99% of visible manufacturing defects before a product ever leaves the line. "One of the most important things manufacturers care about is product quality," says Brian McCarson, Vice President and Senior Principal Engineer, Internet of Things Group (IOTG) at Intel Corporation and a featured speaker at Transform, VentureBeat's upcoming digital conference. "Manufactures prefer throwing away fewer defective products. They strive to have less rework and fewer customer returns. They also want to reduce the cost of their operations by making their tools and processes more efficient, and improve the reliability of their machines so they can proactively do maintenance before it is too late and have more predictable uptime."

I just dragged my sorry sack of cells around the Consumer Electronics Show 2020 for two days; it was hard work. Here are some notes of the things I saw during my visit. It's not intended to be a comprehensive review (nor an unbiased one), I'll leave that up to the professional journalists. This posting is just about what I happened to stroll into and piqued my interest. For the last few years I've done a write up on the show. Here are links to some of the previous years' reviews: What is better than a 4k TV? I think every major manufacturer had an 8k TV on display.

High-definition cameras can detect details even our eyes can't, and fast processors should make interpreting images simple. However, computer vision has long been a hurdle for computer science, and we're only now on the verge of making significant progress in some areas. We tend to underestimate just how much information our eyes and brains have to interpret to achieve human-like vision. A recent report by Tractica, predicts the computer vision hardware and software market will grow from $6.6 billion in 2015 to $48.6 billion annually by 2022. According to Anand Joshi, principal analyst at Tractica "the computer vision market remains ripe for innovation and open to the emergence of new applications as well as new industry participants".