Parag Mital is director of machine intelligence at Kadenze, as well as an artist and interdisciplinary researcher obsessed with the nature of information, representation and attention. Artificial intelligence allows machines to reason and interact with the world, and it's evolving at a breakneck pace. Many advances in AI can be attributed to machine learning, which works by tapping massive computing power to crunch through enormous amounts of digitized data. Now consider that most of our data, the best minds in the business and more computing power than you could ever imagine sit with just a handful of companies. For these reasons, only a few companies in the world are best situated to understand the true potential -- and the current limits -- of AI.

Times Higher Education recently asked whether universities needed to rethink what they do and how they do it, given that artificial intelligence is beginning to take over many post-university careers. With that in mind, here are four examples of how AI can benefit universities. First, there is a new role for higher education, which is to equip graduates to work effectively alongside artificially intelligent systems. The onslaught of AI on white-collar jobs is likely to lead to the AI augmentation of human intelligence, rather than the total replacement of human workers with machine workers. We need workers who understand how to make the best use of the power that AI automation can bring to industry and commerce.

It seems to me that the hype about AI makes really difficult for experienced investors to understand where the real value and innovation are. I would like then to humbly try to bring some clarity to what is happening on the investment side of the artificial intelligence industry. We have seen as in the past the development of AI has been stopped by the absence of funding, and thus studying the current investment market is crucial to identify where AI is going. First of all, it should be clear that investing in AI is extremely cumbersome: the level of technical complexity goes out of the pure commercial scope, and not all the venture capitalists are able to fully comprehend the functional details of machine learning. This is why the figures of the "Advisors" and "Scientist-in-Residence" are becoming extremely important nowadays.

Apple CEO Tim Cook says you won't have to give up your privacy to have a great AI assistant Tim Cook on A.I.: "I Don't Think We Have to Throw Our Privacy Away" Now AI is Deliberately Trying to Scare Us, if We Aren't Already TIM COOK: Here's why assistants on phones are better than home speakers like the Echo Machine Learning Veterans Launch'Element AI' - A Montreal Based Artificial Intelligence Startup ... Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Late last month it was revealed that Apple is quietly working on the iPhone 8 in its Herzliya, Israel offices. Today, it's been revealed that the Cupertino giant is working on its car operating software in its Kanata, Canada facility. The location is somehow strategic, since the tech company hired ex-employees of its former rival, BlackBerry, to work on this project. According to MacRumors, Apple's R&D facility in Canada is focused on the "software core" of its upcoming self-driving car program that is currently being developed by a separate Project Titan team. The car operating system is said to come with many features, such as a heads-up display that would be very useful to drivers who want to access Maps via Apple's digital assistant, Siri.

Slack is going to tap into IBM pet Watson and its cognitive computing skills, covering both bots and other conversation inferences. Slack's own Slackbot will be the first to get the intelligence makeover, with IBM and Slack looking to share what they learn from the experience with other developers. The companies believe integrating Watson will improve accuracy and efficiency of troubleshooting with the bot. IBM is also working on a Watson-powered Slack chatbot specifically for IT and network issues. IBM's Watson is really sharing its wisdom around: it's just joined the Weather Channel's bot on Facebook Messenger, where it will learn your preferences and offer up personalized forecasts and even news for to US-based bot chatters.

The company's scientists think its new AI-based factotum will be the biggest thing since search. It is the day after Google's big hardware event in San Francisco, when the company formally unveiled a new phone (a jab to the iPhone) and a voice-activated speaker (a gut punch to Amazon's Echo). Word of mouth is already tracking positive; a countdown to ecstasy, in the form of upcoming rhapsodic reviews of the Pixel phone, has already begin. But in a conference room on the company's sprawling Mountain View campus, Fernando Pereira, who leads Google's projects in natural language understanding, is less excited about his company's shiny new devices than he is about what will happen when people use them. "Let me tell you a little bit about The Transition," he says.

Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time. In my three decades in the computer industry, none has held more potential, or been more fun. The era of AI has begun.

Databricks Inc., the primary commercial steward behind the popular open source Apache Spark data processing framework for Big Data analytics, published a new report indicating the technology is still red-hot, driven by more use of SQL, streaming analytics and machine learning. The company this summer polled more than 900 organizations and solicited data from 1,615 respondents -- mostly Spark users -- coming from the ranks of data scientists, data engineers, architects and others, and last week published the results in the Apache Spark Survey 2016 Report (free download upon providing registration info). The report follows up on a similar survey last year, confirming the technology's widespread popularity as the most active open source project in the Big Data space. "As in 2015, which was a tremendous year in growth for Apache Spark, this year, too, its growth remains unabated -- not only in areas like the public cloud, but also with the increased use of Spark Streaming and the use of machine learning," the report states. "2016 also shows Spark's robust adoption across a variety of organizations and users from many functional roles to build complex solutions, using multiple Spark components."