Apple is reportedly working on a dedicated artificial intelligence chip that would power AI-related tasks on mobile devices, according to a report from Bloomberg's Mark Gurman. The chip, which may be called the Apple Neural Engine, would be used to offload tasks that require sophisticated algorithms related to facial and speech recognition and augmented reality tasks that rely heavily on computer vision. This chip could improve the device's overall battery life, the report says, and potentially improve overall performance of Apple devices. It's unclear if the chip would make its way into devices this year, Bloomberg reports, but Apple has already started testing future iPhone prototypes with the chip. The ultimate goal would be to separate the most computationally intensive tasks from the iPhone's processor and graphics chip -- much in the same way Apple uses distinct chips to power motion sensing across its device line and the chip that helps its AirPods more easily sync wirelessly with the iPhone.

Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation.

A WBS Professor of Practice, Mark is an Experienced Professional Consultant with a track record in top 1000 Companies in over 20 countries and across multi public, private and start-up sectors. A recognized International thought leader in Digital, company strategy, Telecoms, Digital markets and M&A strategies, CxO practices and author of books and international papers. Mark's work and views have been published in the FT, NYT, WSJ, Washington Post, Bloomberg, AP, Mail, NewScientist, Nature, Scientific American and many channels around the world, TV and Radio including BBC, Sky, ITV, Al Jazeera and many others. Mark supports Warwick with industrial best practice through interests and expertise areas. In 2017 Mark is due to publish - The 4th Industrial Revolution: responding to the impact of artificial intelligence on business.

There's an anthill in the way, but the engineers don't care or even notice; they flood the area anyway, and too bad for the ants. Now replace the ants with humans, happily going about their own business, and the engineers with a race of superintelligent computers that happen to have other priorities. Just as we now have power to dictate the fate of less intelligent beings, so might such computers someday exert life-and-death power over us. That's the analogy the superstar physicist Stephen Hawking used in 2015 to describe the mounting perils he sees in the current explosion of artificial intelligence. And lately the alarms have been sounding louder than ever.

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At some point in the not-distant future, a patient is going to blame someone--perhaps a physician, maybe even a radiologist--for an injurious care decision made, recommended or otherwise nudged by artificial intelligence (AI). Who will be slapped with the suit? Taking up the riddle, a Quartz writer points out that the undiscoverable algorithmic rationale that usually drives AI's decision-making--its "black box"--will make it hard to pin down a human. "Even if it were possible for a technically literate doctor to inspect the process, many AI algorithms are unavailable for review, as they are treated as protected proprietary information," explains the writer, Robert Hart. "Further still, the data used to train the algorithms is often similarly protected or otherwise publicly unavailable for privacy reasons. This will likely be complicated further as doctors come to rely on AI more and more and it becomes less common to challenge an algorithm's result."

Are the humans of finance an endangered species? People are still the lubricant that oils the wheels of finance, toiling at innumerable tasks--executing and settling trades, writing analysis, monitoring risk. Squeezed by low interest rates, shrinking trading revenue, and nimbler technology-based competitors, banks are racing to remake themselves as digital companies to cut costs and better serve clients. In other words, they're preparing for the day that machines made by men and women take over more of what used to be the sole province of humans: knowledge work. Consider venerable State Street, a 224-year-old custody bank that predates the steam locomotive and caters to institutional investors such as pensions and mutual funds.

Time Budget: 30 seconds Hi, my name is Matthias Langer. I am currently a PhD student at La Trobe University. Today I would like to present to you Inferno, which is a deep learning system that we develop here in Melbourne and can run on top of Spark. Time Budget: 30 seconds My talk will be structured as follows: I will talk with you a little bit about DL. … then about DL and Spark… … our own DL system …. Time Budget: 30 seconds Talking Points: So without further ado, let's start… Time Budget: 1 minute So, what is deep learning? Deep learning is machine learning algorithm that tries to extract hierarchical features from input data. In itself that is kind of similar to how the brain does it in this slide. So how does that work: Let's say a stimulus (or input) comes from the eye and eventually ends up in region V1. There primitive features like edges are extracted.

You don't have to be a Go champion to have artificial intelligence change your game. You get in your car and your Apple iPhone tells you what traffic looks like where you're going--before you ask. We're all on the road with Tesla's self-driving cars, which are redefining what driving means. The artificial-intelligence, calendar-assistant "Amy" emails three of your friends to figure out a meeting time that works for everyone--and nails it. Thankfully, chatting with Amazon's Alexa is a lot more entertaining than, say, chatting would be with Hal, the fictional artificial intelligence from the film 2001: A Space Odyssey.