With so much talk about cancer-sniffing dogs, I've been wondering why there hasn't been more work on machine-based olfactory diagnoses. Here's an article about someone working on it.

“We’ve trained a neural network called DALL·E that creates images from text captions for a wide range of concepts expressible in natural language.

Need an illustration of a baby daikon radish in a tutu walking a dog, or a stained glass window with an image of a blue strawberry? DALL·E will generate one for you!

Good podcast for Japanese listening practice, with transcripts here.

“As face masks became mandatory at different points in time across German regions, we can compare the rise in infections in regions with masks and regions without masks. Weighing various estimates, we conclude that 20 d after becoming mandatory face masks have reduced the number of new infections by around 45%. As economic costs are close to zero compared to other public health measures, masks seem to be a cost-effective means to combat COVID-19.

“Artificial intelligence (AI) has solved one of biology’s grand challenges: predicting how proteins curl up from a linear chain of amino acids into 3D shapes that allow them to carry out life’s tasks. Today, leading structural biologists and organizers of a biennial protein-folding competition announced the achievement by researchers at DeepMind, a U.K.-based AI company. They say the DeepMind method will have far-reaching effects, among them dramatically speeding the creation of new medications.

For some reason, the number of Amazon reviews of scented candles that complain about the candles lacking scent increased during April, decreased during the summer, and then skyrocketed during October and November.

“The city of Takikawa, Japan, deployed these robowolves to prevent bear attacks.

“FrankMocap provides state-of-the-art 3D pose estimation outputs for body, hand, and body+hands in a single system. The core objective of FrankMocap is to democratize the 3D human pose estimation technology, enabling anyone (researchers, engineers, developers, artists, and others) can easily obtain 3D motion capture outputs from videos and images.

 “Open a new window somewhere in the world

“We show that temporal adversarial learning is key to achieving temporally coherent solutions without sacrificing spatial detail.