Combining machine learning method -- a type of artificial intelligence -- with a special MRI technique may help physicians predict who is more likely to develop Alzheimer's disease, a study says. Machine learning is a type of artificial intelligence that allows computer programmes to learn when exposed to new data without being programmed. "With standard diagnostic MRI, we can see advanced Alzheimer's disease, such as atrophy of the hippocampus," said principal investigator Alle Meije Wink from VU University Medical Centre in Amsterdam. "But at that point, the brain tissue is gone and there's no way to restore it. It would be helpful to detect and diagnose the disease before it's too late," Meije Wink explained.

I've just run my second briefing on intelligent assistance. Much happened in the few months between sessions. This time, the second half of the day was dominated with stories about bots and their use cases on messaging platforms. It also included the amazing things now possible via automated voice which Amazon's Alexa Challenge exemplifies. Meanwhile IBM's Watson continues its conquest of carbon life forms with the trashing of an extraordinarily talented Go grand master.

When a cyclist signals, its hand motion is registered and the system is able to make an educated guess as to its intended direction. Bicyclists require special on-road considerations that other cars do not, and those considerations aren't limited to humans. Google's own self-driving cars, in fact, have a whole set of unique operations devoted solely to identifying and accommodating our two-wheeled compatriots. Google's monthly self-driving car report focuses on bikes this month. It explains how Big G's cars are able to work alongside cyclists.

As financial services organisations predict and plan for the way consumers will manage their money in the future, artificial intelligence (AI) is high on the business development strategy for 2016 and beyond, says Gideon Hyde from design consultancy Market Gravity. The co-founder shares his thoughts on the emerging technology and explains how businesses can embrace AI to enhance their offerings, meet consumer demand for speed, personalisation and convenience, and launch new products and services to stand out in the competitive marketplace. AI is already around us and used every day within payments, money management and for robo-advice, particularly in the area of intelligent digital assistants that handle regular customer service enquiries and tasks. It can process'big data' far more efficiently than humans and can recognise speech, images, text, patterns of online behaviour, for example to detect fraud as well as appropriate advertisements for upselling. Smart machines and technology can turn data into customer insights and enhance service provisions, bringing the digital experience closer to the human interaction for consumers.

Artificial intelligence… Two words which together conjure up so much wonder and awe in the imagination of programmers, sci-fi fans and perhaps just about anyone with an interest in the fate of the world! Thanks to man's best friend the dog R2-D2, the evil Skynet, the fantastical 2001: A Space Odyssey, post-apocalyptical androids dreaming of electric sheep, and maybe also Gary Numan, everyone is pretty well familiar with the concept of artificial intelligence (AI). Yep, books, the big screen, comics, er… mashed potato advertisements – AI is in all of them in a big way. It also features heavily in the marketing materials of recently-appearing and exceptionally-ambitious cybersecurity companies. In fact, there's probably only one place today where you can't find it.

Google DeepMind and the NHS are developing a machine learning system with Moorfields Eye Hospital that can recognize sight-threatening conditions from just a digital scan of the eye. Mustafa Suleyman, Deepmind's co-founder, says this is the company's first foray into a purely medical research. In this new collaboration with Moorfields, an algorithm will be trained using one million anonymized eye scans to train to identify early signs of degenerative eye conditions such as wet age-related macular degeneration and diabetic retinopathy. "If you have diabetes you're 25 times more likely to go blind. If we can detect this, and get in there as early as possible, then 98% of the most severe visual loss might be prevented," says Suleyman.

The makers of a new trend-forecasting platform claim they predicted the Rainbow Bagel before it was a thing. Santa Monica, California-based Tilofy is currently in a private, invitation-only beta of its new platform, which it says is the first automated trend forecaster. Unlike services that, say, spot current trends in social media, Tilofy utilizes machine learning, artificial intelligence and machine vision of imagery to forecast trends weeks or months before they become mainstream. "There's a bagel store in Brooklyn that was doing something interesting, tapping into the LGBT community" by creating a rainbow-colored bagel, CEO and founder Ali Khoshgozaran told me. He recalled that Tilofy predicted the future mainstream popularity of the Rainbow Bagel in November of last year. In February, The Wall Street Journal wrote an article about it, and now The Bagel Store is restructuring around its hit product.

A major study into the use of mobile phone data as a tool for predicting clinical decisions, came to a scathing conclusion, characterising the practice as "voodoo machine learning". The widespread use of smartphones to collect healthcare data has been thrown into doubt by a couple of recent studies. In some fields, such as the management of chronic diseases and mental health monitoring smartphones have enabled a greater level of patient self-control, and personalised clinical intervention. Success in one area, however, does not imply success in all – especially as smartphone health apps are often rolled out before evidence of their effectiveness has been rigorously analysed. A major study into the use of mobile phone data as a tool for predicting clinical decisions, released in June, came to a scathing conclusion, characterising the practice as "voodoo machine learning".

Kitten videos are harmless, right? Except when they take over your phone. Researchers have found something new to worry about on the internet. It turns out that a muffled voice hidden in an innocuous YouTube video could issue commands to a nearby smartphone without you even knowing it. The researchers describe the threat in a research paper to be presented next month at the USENIX Security Symposium in Austin, Texas.

The National Highway Traffic Safety Administration is reportedly investigating whether Tesla Motor's autopilot feature was engaged during a non-fatal July 1 crash – what would be the agency's second inquiry into the automaker's self-driving technology in as many weeks. The wreck involved a Tesla Model X in Pennsylvania. Last week, the agency disclosed a separate investigation into a fatal crash in Florida in May that involved a Tesla Model S. The driver in that collision was using Tesla's assisted driving feature at the time of the incident, which helps motorists steer and stay in lanes. The electric car manufacturer said Wednesday in a prepared statement that it received a message from the vehicle's computer July 1 indicating a crash had occurred, but more detailed logs were never transmitted. "We have no data at this point to indicate that Autopilot was engaged or not engaged," a Tesla spokesperson said in a statement.