Lifeboat Foundation

Xiaomi has a couple of new products out in Walmart and gave press the rundown today at an event in New York City. The first is a 150-inch laser projector going for $1,999.99 at Walmart doubles up as a television with Android TV. It may seem overpriced for what it is, but it also marks one of Xiaomi’s infrequent expansions into American offerings.

There are a couple of things to break down here, namely that projector is oddly expensive for a 1920 × 1080p screen. Xiaomi says it has no concrete plans to bring a 4K version to the US, and that this is the same model it’s sold in China. You could have found cheaper 1080p projectors back in 2016.

Still, the laser projector has a number of positives including an ultra-short throw, so it can be placed 20 inches from the wall and still display a bright, colorful image, in contrast with other projectors that might need to be placed at the back of a room and show a more faded image. There’s also a detector on top of the projector so if you get too close to the laser, the projector will shut off its light automatically to prevent you from damaging your eyes. The device also comes with a corresponding remote control with which you can summon Google Assistant.

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Researchers from the Departments of Chemistry and Engineering Science at the University of Oxford have found a general way of predicting enzyme activity. Enzymes are the protein catalysts that perform most of the key functions in Biology. Published in Nature Chemical Biology, the researchers’ novel AI approach is based on the enzyme’s sequence, together with the screening of a defined ‘training set’ of substrates and the right chemical parameters to define them.

William (“Whurley”) Hurley Contributor

Biometric features like fingerprint sensors and iris scanners have made it easier to securely unlock phones, but they may never be as secure as a good old-fashioned password. Researchers have repeatedly worked out methods to impersonate registered users of biometric devices, but now a team from New York University and the University of Michigan has gone further. The team managed to create so-called “DeepMasterPrints” that can fool a sensor without a sample of the real user’s fingerprints.

Past attempts to bypass biometric systems usually involve getting access to a registered individual’s data — that could be a copy of their fingerprint or a 3D scan of their face. DeepMasterPrints involves generating an entirely new fingerprint from a mountain of data that’s close enough to fool the sensor. Like so many research projects these days, the team used neural networks to do the heavy lifting.

The process started with feeding fingerprints from 6,000 people into a neural network in order to train it on what a human fingerprint looks like. A neural network is composed of a series of nodes that process data. It feeds forward into additional “layers” of nodes if the output meets a certain threshold. Thus, you can train the network to get the desired output. In this case, the researchers used a “generative adversarial network” to tune the system’s ability to generate believable fingerprints. The network used its understanding of prints to make one from scratch, and then a second network would determine if they were real or fake. If the fingerprints didn’t pass muster, the network could be re-tuned to try again.

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En Taro AI

The latest results in a long-running contest of video-game-playing AIs reveal how hard it is for machines to master swarming insectoid Zergs or blitzing Protos. They also show that even old-school approaches can still sometimes win out.

The AIIDE Starcraft Contest has been running at Memorial University in Newfoundland, Canada, since 2010. Participating teams submit bots that play an original version of Starcraft, a sprawling sci-fi-themed game, in a series of one-on-one showdowns.

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It’ll be ready for launch by the mid-2020s.

On-Earth manufacturing isn’t the only kind being automated.

It is predicted that artificial intelligence (AI) will transform many aspects of our life including healthcare and genomics. AI and machine learning have helped us to understand the genome of organisms and will potentially change the way we treat disease, determine effective drugs and edit genes.

Google’s deep learning AI called LYNA able to correctly identify tumorous regions in lymph nodes 99 per cent of the time.