Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge MA 02139 USA Recent progress implies that a crossover between machine learning and quantum information processing benefits both fields. Traditional machine learning has dramatically improved the benchmarking and control of experimental quantum computing systems, including adaptive quantum phase estimation and designing quantum computing gates. On the other hand, quantum mechanics offers tantalizing prospects to enhance machine learning, ranging from reduced computational complexity to improved generalization performance. The most notable examples include quantum enhanced algorithms for principal component analysis, quantum support vector machines, and quantum Boltzmann machines. Progress has been rapid, fostered by demonstrations of midsized quantum optimizers which are predicted to soon outperform their classical counterparts. Further, we are witnessing the emergence of a physical theory pinpointing the fundamental and natural limitations of learning. Here we survey the cutting edge of this merger and list several open problems. Machine learning has fundamentally changed the way humans interact with and relate to data. Applications range from self-driving cars to intelligent agents capable of exceeding the best humans at Jeopardy and Go. These applications exhibit large data sets and push current algorithms and computational resources to their limit. Information is fundamentally governed by the laws of physics. The laws are quantum mechanical at the scales of present day information processing technology, in contrast to the more familiar'classical' physics at the human scale. The interface of quantum physics and machine learning naturally goes both ways: machine learning algorithms find application in understanding and controlling quantum systems and, on the other hand, quantum computational devices promise enhancement of the performance of machine learning algorithms for problems beyond the reach of classical computing.

When the world shifted from desktop to smartphones, one thing didn't change: the existence of a screen on both devices. The screen shrank, but it remained the medium through which we interact with computers. For Google, that meant its core online advertising business -- visible search ads on a webpage -- remained intact and lucrative. Today, Google may be at the beginning of a new shift -- one toward artificially intelligent virtual assistants, in which we use our voice to interact with technology instead of our eyes. The problem with voice assistants is they don't have a screen on which to display ads.

Nintendo Reports Second Quarter Losses But 3DS Sales Are Up Thanks To'Pokmon GO' Increasingly, the world is becoming an intelligent, digitally enabled mesh of people, things and services. Technology will be embedded in everything in the digital business of the future, and ordinary people will experience a digitally-enabled world where the lines between what is real and what is digital blur. Rich digital services will be delivered to everything, and intelligence will be embedded in everything behind the scenes. We call this mesh of people, devices, content and services the intelligent digital mesh, and this forms the basis for our Top 10 Strategic Technology Trends for 2017. Artificial Intelligence (AI) and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application.

Facebook has snapped up a facial recognition startup to help it win the war it waged against Snapchat. The social network has acquired FacioMetrics, a Carnegie Mellon University spinoff that developed a few face detection apps, including one that can recognize seven different emotions in human faces. Those applications are no longer available in any app store. A Facebook spokesperson told TechCrunch that the company plans to use the startup's technology to enhance its Snapchat-like AR filters for Facebook videos and Live broadcasts. It could lead to new AR masks, new special effects and even new ways to trigger their animations.

SALT LAKE CITY, UT--(Marketwired - Nov 15, 2016) - At SC16, AMD (NASDAQ: AMD) announced that Radeon GPU technology will be available to Google Cloud Platform users worldwide. Starting in 2017, Google will use AMD's fastest available single-precision dual GPU compute accelerators, Radeon-based AMD FirePro S9300 x2 Server GPUs, to help accelerate Google Compute Engine and Google Cloud Machine Learning services.(1) AMD FirePro S9300 x2 GPUs can handle highly parallel calculations, including complex medical and financial simulations, seismic and subsurface exploration, machine learning, video rendering and transcoding, and scientific analysis. Google Cloud Platform will make the AMD GPU resources available for all their users around the world. "Graphics processors represent the best combination of performance and programmability for existing and emerging big data applications," said Raja Koduri, senior vice president and chief architect, Radeon Technologies Group, AMD.

Stockholm-based Now Interact has raised $5 million A round from SEB Venture Capital, Inventure, and Industrifonden to develop the product and drive U.S. expansion. Now Interact says it has created the first platform that optimizes the bridge between online and offline channels, including the contact center, telesales and bricks & mortar stores. Businesses can better leverage data to deliver a more personalized customer experience, generate maximum profit, and accelerate the digitalization of sales and service. SEB s investment in Now Interact can be seen as part of the bank s ongoing digital transformation, while Inventure is a leading early-stage venture capital firm in the region which supports early-stage entrepreneurs in the region in expanding their businesses globally. "We are very excited about the opportunity that Now Interact presents to the market as we believe that Artificial Intelligence is about to redefine how companies interact with their online visitors. Now Interact has created an advanced platform that will change the way users flow from online to offline channels," said Ulf Lewander of SEB.

My name is Victoria, and I'll be your conference operator today. Welcome you to the NVIDIA Financial Results Conference Call. All lines have been placed on mute. After the speakers' remarks there will be a question-and-answer period. I will now turn the call over to Arnab Chanda, Vice President of Investor Relations at NVIDIA. You may begin your conference. With me on the call today from NVIDIA are Jen-Hsun Huang, President and Chief Executive Officer, and Colette Kress, Executive Vice President and Chief Financial Officer. I'd like to remind you that our call is being webcast live on NVIDIA's Investor Relations website. You can hear a replay by telephone until the 17 November, 2016. The webcast will be available for replay up until next quarter's conference call to discuss Q4 financial results. The content of today's call is NVIDIA's property. It cannot be reproduced or transcribed without our prior written consent. During this call, we may make forward-looking statements based on current expectations. These forward-looking statements are subject to a number of significant risks and uncertainties and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release, our most recent Form 10-K and 10-Q, and the reports that we may file on Form 8-K with the Securities and Exchange Commission. All of our statements are made as of today, the 10th of November, 2016 based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non-GAAP financial measures. You can find a reconciliation of these non-GAAP financial measures to GAAP financial measures in our CFO commentary which is posted on our website. Revenue reached a record in the third quarter, exceeding $2 billion for the first time. Driving this was success in our Pascal-based gaming platform and growth in our datacenter platform, reflecting the role of NVIDIA's GPU as the engine of AI computing.

GE Digital today announced that it has acquired Wise.io, a machine-learning powered service that helps businesses find patterns and trends in their vast data stores. At first glance, that may seem like an odd acquisition for a company like GE. It's important to keep in mind, though, that with Predix, GE already offers its customers a service that focuses on helping them monitor their equipment, whether that's an industrial tool or an aircraft engine, and predict issues based on the monitoring data. As GE CIO Jim Fowler told me, the company's developers wrote a few hundred different models for lots of different assets in Predix. The service has some rudimentary AI capabilities, but the addition of Wise.io's technology -- which can find patterns on its own -- and its team will allow GE to offer a far more flexible model.

The social robot startup Jibo has raised $13.1 million from investors, but a filing with the Securities and Exchange Commission shows the company is looking to raise a total of $28 million.

Samsung Electronics Co. is making a drive for control of the car. The South Korean smartphone maker said Monday that it would buy U.S. auto-parts supplier Harman International Industries Inc., based in Stamford, Conn., for $8 billion in an all-cash deal that instantly makes Samsung a major player in the world of automotive technology. The deal -- Samsung's biggest acquisition in its history -- reshapes the pecking order in the global automotive supply chain, reflecting a quickening pace of innovation and an increased role for companies with deep pockets and a keen understanding of mobile services. Harman, an audio pioneer that dates back to 1953, has in recent years pushed aggressively into the automotive world under CEO Dinesh Paliwal, and has secured billions in new business, including big contracts with General Motors Co. and Fiat Chrysler Automobiles NV. It has projected an order backlog of $24 billion, more than three times annual revenue, and about two-thirds of its current sales come from auto makers.