PARKFIELD, Calif., July 9 (UPI) -- U.S. scientists say they observed changes in seismic wave speeds before two small California earthquakes -- a finding that might lead to quake forecasts. Study co-author Paul Silver of the Carnegie Institution said the discovery was made at the San Andreas Fault Observatory at Depth, located halfway between Los Angeles and San Francisco. The observatory consists of two holes drilled into the fault zone. The researchers told the BBC they generate seismic waves deep in one hole and then time their arrival at a seismometer in the other hole. The speed of the waves varies due to stress-induced cracks opening and closing in the rocks.

According to a study published in the journal Science, a honeycomb-pattern of tiny, nano-sized magnets that are submerged in a material known as spin ice could solve a complex computational problem in a single step. In fact, clusters of such magnet arrays function similar to a neural network: It is more "similar to how our brains work than to the way in which traditional computers process information," the researchers said. Exploiting the potential of magnets gets more difficult the closer they are located to each other as they interfere with their magnetic fields, the scientists found that their honeycomb patterns create competition between magnets and "reduces the problems caused by these interactions by two-thirds." It is good enough to store computable information and contents can be read by measuring the magnet's electrical resistance. So far, the researchers have succeeded in reading and writing data, but there has been no information about the data transfer rates. However, it seems as if speed isn't the key problem yet as their operating temperature is far more critical: At this time, the magnets only function well and "arrange themselves into patterns" at a temperature of -223 degrees Celsius.

What next for Google's DeepMind, now that the company has mastered the ancient board game of Go, beating the Korean champion Lee Se-Dol 4–1 this month? A paper from two UCL researchers suggests one future project: playing poker. And unlike Go, victory in that field could probably fund itself – at least until humans stopped playing against the robot. The paper's authors are Johannes Heinrich, a research student at UCL, and David Silver, a UCL lecturer who is working at DeepMind. Silver, who was AlphaGo's main programmer, has been called the "unsung hero at Google DeepMind", although this paper relates to his work at UCL.

Demis Hassabis has a modest demeanour and an unassuming countenance, but he is deadly serious when he tells me he is on a mission to "solve intelligence, and then use that to solve everything else". Coming from almost anyone else, the statement would be laughable; from him, not so much. Hassabis is the 39-year-old former chess master and video-games designer whose artificial intelligence research start-up, DeepMind, was bought by Google in 2014 for a reported $625 million. He is the son of immigrants, attended a state comprehensive in Finchley and holds degrees from Cambridge and UCL in computer science and cognitive neuroscience. A "visionary" manager, according to those who work with him, Hassabis also reckons he has found a way to "make science research efficient" and says he is leading an "Apollo programme for the 21st century". He's the sort of normal-looking bloke you wouldn't look twice at on the street, but Tim Berners-Lee once described him to me as one of the smartest human beings on the planet. Artificial intelligence is already all around us, of course, every time we interrogate Siri or get a recommendation on Android. And in the short term, Google products will surely benefit from Hassabis's research, even if improvements in personalisation, search, YouTube, and speech and facial recognition are not presented as "AI" as such. "It's just stuff that works.") In the longer term, though, the technology he is developing is about more than emotional robots and smarter phones.

Marvin Minsky, who has died aged 88, was a pioneer of artificial intelligence. In 1958 he co-founded the Artificial Intelligence Project at the Massachusetts Institute of Technology (MIT). Subsequently known as the AI Lab, it became a mecca for artificial intelligence research. His published works included Steps Toward Artificial Intelligence (1960), a manifesto that profoundly shaped AI in its earliest days, and Society of Mind (1985), which postulated that the brain is fundamentally an assembly of interacting, specialised, autonomous agents for tasks such as visual processing and knowledge management. That view of the architecture of the mind remains a cornerstone of AI research.

A committee of MPs has condemned police for continuing to upload custody photographs, including of people never charged, to a face recognition database, despite a high court judgement that ruled the practice was unlawful. In a report into use of biometric data, the Commons Science and Technology Committee said it was "dismayed" to learn that more than 12m photographs had been entered into the Police National Database without proper testing or oversight. It also noted that current practice appeared to flout a high court ruling from 2012 that said the contemporary policy of retaining custody photographs was unlawful. Some forces, including the Met, have stopped putting images on the national database until the law is clarified. But others have continued to upload photographs in the absence of any national guidance.

Nobody wants to confront the idea of their own obsolescence. Still, sitting across a desk from Kris Hammond, in his office overlooking the lake shore in Chicago, it is hard not to at least have a sense of the inevitable. Hammond is the co-founder and chief scientist of a company called Narrative Science, which, among other things, has worked out a way of teaching machines how to write journalism. At the moment, the computers' output is limited to basic sports reports and business news. But Hammond is convinced this is only the beginning.

Companies like Google and Tesla have held up autonomous vehicles as a panacea for road accidents, which claim over 32,000 American lives each year. This month, Obama put stock in that idea, signing a $305bn transportation bill that includes grants for self driving vehicles. That backs up 10 years of US Department of Transportation work on technical studies and policies surrounding autonomous cars. Many researchers say forecasting the impact of self-driving cars on reducing accidents is difficult because there just isn't enough real-life road testing and data to make a reliable forecast. The National Highway Traffic Safety Administration, however, found that over 90% of car crashes involve human error.

Loredana Paglialonga leans across her father's prone body and whispers in his ear: "Spinta, Papi, spinta" ("Push Daddy, push"). It is impossible to tell whether Anselmo Paglialonga, a former major in the Italian carabinieri, has heard. Paralysed from head to toe with amyotrophic lateral sclerosis (ALS), Anselmo is completely "locked in". Unable to speak or open his eyes, his only hope of communicating is via a state-of-the-art neuroheadset attached to his scalp. Designed by Emotiv Systems, a Californian neuroengineering company, the Epoc headset purports to give users the power to control objects with their thoughts and was a succès fou on Kickstarter, where users stumped up $1.6m to fund its development – 16 times Emotiv's original target. Indeed right now, I am told, the 14 marble-sized electrodes in the Epoc's plastic clip-on frame are monitoring the EEG signals from Anselmo's brain and sending them wirelessly to a control unit. By analysing those signals using a machine-learning algorithm, BrainControl, a Sienna-based developer, claims to be able to distinguish Anselmo's thoughts and intentions from other brain noise and use those signals to operate a cursor on a tablet computer.

The Moto X was Google's vision for the future of mobile technology. Billed as the world's first artificially intelligent phone, its permanent listening mode enabled it to serve up directions or give weather forecasts in response to spoken commands. That was until the search giant called an end to the adventure with the $2.9bn (£1.8bn) sale of Motorola to rising Chinese star Lenovo on Wednesday, a move that will free its engineers to focus on other revolutionary technologies. Google's recent acquisitions – from robot maker Boston Dynamics to a London company that aims to make computers think like humans – show how its ambitions stretch far beyond the smartphone. After all, mobile phones are now a low-margin, high-volume manufacturing business, which makes them a better fit for Lenovo than Google.