Stephen Salter, who has died aged 85, was the inventor of the Salter's Duck, a wave-power device that was the first of its kind and promised to provide a new source of renewable energy for the world – until it was effectively killed off by the nuclear industry. In 1982, after eight years of development under Salter's direction at Edinburgh University, the United Kingdom Atomic Energy Authority (UKAEA) was asked by the government to see if the duck might be a cost-effective way of making large quantities of electricity. To the great surprise of Salter, and others, the UKAEA came to the conclusion that it was uneconomic, and that no further government funding should be given to the project. A decade later it emerged that thanks to a misplaced decimal point, the review had made Salter's duck look 10 times more expensive than the experiments showed it was likely to be. The UKAEA claimed this was just a mistake, but Salter, who had never been allowed to see the results of the secret evaluation, put it another way: asking the nuclear industry to evaluate an alternative source of energy was like putting King Herod in charge of a children's home, he suggested.

Now that generative AI models can produce photorealistic, fake images of child sexual abuse, regulators and child safety advocates are worried that an already-abhorrent practice will spiral further out of control. But lost in this fear is an uncomfortable possibility--that AI-generated child pornography could actually benefit society in the long run by providing a less harmful alternative to the already-massive market for images of child sexual abuse. The growing consensus among scientists is that pedophilia is biological in nature, and that keeping pedophilic urges at bay can be incredibly difficult. "What turns us on sexually, we don't decide that--we discover that," said psychiatrist Dr. Fred Berlin, director of the Johns Hopkins Sex and Gender Clinic and an expert on paraphilic disorders. "It's not because [pedophiles have] chosen to have these kinds of urges or attractions. They've discovered through no fault of their own that this is the nature of what they're afflicted with in terms of their own sexual makeup … We're talking about not giving into a craving, a craving that is rooted in biology, not unlike somebody who's having a craving for heroin."

We spend a lot of time talking to researchers here at WIRED Transport. Those are the gals and guys filling the spreadsheets, tapping out the algorithms, and splaying in fear as they ride yet another roller coaster for science. This week, we spoke to engineers and developers who have sacrificed mind and body to solve problems, ones like car sickness and unfair school bus schedules. They want to create tools that work for disabled farmers, and electric trucks that drive themselves. Hard stuff, sure, but there's fun to be had along the way.

Apple's first iPhone launched in 2007, decades after the concept of machine learning -- a subset of artificial intelligence (AI) that employs mathematical techniques that "teach" software to make sense of complicated datasets -- rose to prominence. But it was only recently that the two collided. Apple launched Core ML, a framework designed to speed up machine learning tasks, alongside iOS 11 in May 2017. The Cupertino company shipped its first chip purpose-built for AI, the A11 Bionic, in last year's iPhone X. And at the 2018 Worldwide Developers Conference (WWDC), it took the wraps off Core ML 2, a new and improved version of Core ML; and Create ML, a GPU-accelerated tool for native AI model training on Macs.