Operational AI systems (for example, self-driving cars) need to obey both the law of the land and our values. We propose AI oversight systems ("AI Guardians") as an approach to addressing this challenge, and to respond to the potential risks associated with increasingly autonomous AI systems.a These AI oversight systems serve to verify that operational systems did not stray unduly from the guidelines of their programmers and to bring them back in compliance if they do stray. The introduction of such second-order, oversight systems is not meant to suggest strict, powerful, or rigid (from here on'strong') controls. Operations systems need a great degree of latitude in order to follow the lessons of their learning from additional data mining and experience and to be able to render at least semi-autonomous decisions (more about this later).

Ashok Goel is a professor in the School of Interactive Computing. Soon scientists and the public will have the chance to easily test hypotheses about America's ecological challenges with the help of an ensemble of technologies, including artificial intelligence. Researchers at Georgia Institute of Technology will link their technology for systems thinking with IBM Watson and the Encyclopedia of Life at the Smithsonian. Scientists will then be able to use the information to create their own models about the environment and efficiently test them. The project is one of 10 "Big Data Spokes" announced by the National Science Foundation (NSF).

Nvidia's current Pascal GPUs are generating a lot of enthusiasm, but their successor, the Volta GPU architecture, is on its way next year, and there's a lot to be excited about. Nvidia unveiled Volta in a new Xavier supercomputer chip designed for self-driving cars, with the small surprising coming Wednesday at the company's GPU Technology Conference in Amsterdam. Xavier provides unprecedented computing horsepower, allowing cars to recognize images, analyze on-road situations, and take action. Much of the processing will happen on an integrated 512-core Volta GPU. Xavier will power the successor to Nvidia's current self-driving car computer called Drive PX 2. It has dual 8K HDR video recording capabilities, suggesting the new GPU architecture will explore areas beyond 4K graphics.

SAS announced a new open, "cloud-ready" machine learning, cognitive computing, analytics platform. Recently, Customer Think wrote: The idea is to bring together the SAS portfolio, built over some 40 years, into one platform that can be used by data scientists and other analytics professionals; business users and IT management; and senior management. Customer Think stated, SAS is also working harder to be more "open" -- in the sense of being interoperable with other enterprise systems. This is hugely important in the age of cloud-based systems and infrastructure services like Amazon Web Services and Microsoft Azure. If you can't access a key functionality via a cloud-based API, it might as well not exist.

Imagine wanting a cup of coffee and suddenly finding it before you, freshly prepared to your exacting standards. In the not-so-distant future, this will be reality for Muggles, too. In fact, thanks to a surge in consumer data, brands and marketers can already make better inferences about consumer wants and needs, but as AI and machine learning are more deftly integrated, insights will only get better, as will the ability to anticipate consumer needs – and to even make decisions on behalf of consumers without any input from them whatsoever. Like, say, ordering a cup of coffee. As it stands, digital enables brands to customize offers for specific users rather than provide generic solutions.

What is a technological singularity? Scientifically the word singularity is used in a few distinctly different ways. Modern general relativity defines a space-time singularity -- also known as a gravitational singularity -- as a point that contains huge mass in infinitely small space, where the laws of physics as we know them cease to operate. The state of the Universe at the beginning of the Big Bang was a space-time singularity. Black holes are said to contain gravitational singularities.

The technology (and market impact) is very real. AI and ML are the latest buzzwords, but unlike most corporate cliches, there's a robust market for AI tech–both in the form of internal R&D and big corporate interest–in the realm of startup work and venture funding. But it's taken a while to get here. According to a report about investment into AI startups by VentureScanner, funding into AI startups nearly doubled between 2013 and 2015. And according to our analysis of companies in Mattermark's database that are tagged with "Artificial intelligence," "Machine learning," "Computer vision," and other related tags, it's easy to see that founding activity in the artificial intelligence space has really exploded in recent years.

David Siegel, a quantitative hedge fund pioneer, issued a warning to investors: Artificial intelligence lacks common sense. Siegel, who has used AI to build his Two Sigma Investments into a 37 billion hedge fund firm, said algorithms are limited by the scant amount of training data available to instruct them on how to identify everything from objects in images to trading opportunities. Hedge funds are embracing a form of AI called machine learning years after Two Sigma deployed the technology and as stock and bond pickers struggle to outperform markets. A unit of the firm, called Two Sigma Ventures, seeks to invest in companies focused on data science, machine learning, artificial intelligence and advanced hardware.

The deep-learning software driving the modern artificial intelligence revolution has mostly run on fairly standard computer hardware. Some tech giants such as Google and Intel have focused some of their considerable resources on creating more specialized computer chips designed for deep learning. But IBM has taken a more unusual approach: It is testing its brain-inspired TrueNorth computer chip as a hardware platform for deep learning. Deep learning's powerful capabilities rely on algorithms called convolutional neural networks that consist of layers of nodes (also known as neurons). Such neural networks can filter huge amounts of data through their "deep" layers to become better at, say, automatically recognizing individual human faces or understanding different languages. These are the types of capabilities that already empower online services offered by the likes of Google, Facebook, Amazon, and Microsoft.

Banks are positioned to pioneer the use of artificial intelligence to help them retain clients in an era of technological disruption, IBM Chief Executive Officer Ginni Rometty said at a conference in Geneva. "Financial services, I believe, can and will lead the world into this era," Rometty said at the Sibos conference on Wednesday, sharing a panel with Sergio Ermotti, CEO of UBS Group AG. "The ultimate competitive advantage is being cognitive." International Business Machines Corp. has touted its "cognitive solutions" unit and its Watson artificial intelligence platform as crucial to future growth. Revenue at that unit increased 3.5 percent to 4.7 billion in the second quarter, following five straight quarterly declines, the company reported in July.