GE machine learning expert Colin Parris met with USA TODAY tech reporter Marco della Cava to talk about the coming age of AI. (Photo: Marco della Cava, USA TODAY) SAN FRANCISCO - Look for the so-called industrial Internet to reshape how machines are maintained, with one by-product of artificial intelligence being growing challenges in the employment sector. That's the opinion of Colin Parris, GE's vice president of software and analytics research, who joined USA TODAY Tech for a podcast Tuesday. Parris listed many ways in which powerful algorithms yoked to cloud computing will increasingly streamline the way devices such as airplane engines and off-shore oil rigs are maintained. But he adds that one likely byproduct will be less reliance on armies of human workers. So, he adds, "learning cycles will have to change. We think we learn (in our youth) and then stop," says Parris.

IMAGE: Insilico Medicine will present their results in applying deep learning to biomarker development and cosmetics applications at the INNOCOS World Beauty Innovation Summit in Vienna 9-10th of June. Insilico Medicine to present their results in applying deep learning to biomarker development and cosmetics applications at INNOCOS World Beauty Innovation Summit in Vienna 9-10th of June. INNOCOS is one of the largest annual events in the beauty industry bringing together top experts from many areas of research, R&D heads of the cosmetics conglomerates, innovation and strategy professionals and digital media experts. In addition to heading Insilico Medicine, Inc, a big data analytics company focused on applying advanced signaling pathway activation analysis and deep learning methods to biomarker and drug discovery in cancer and age-related diseases, Alex Zhavoronkov, PhD is the co-founder and principal scientist of Youth Laboratories, a company focusing on applying machine learning methods to evaluating the condition of human skin and general health status using multimodal inputs. The company developed an app called RYNKL, a mobile app for evaluating the effectiveness of various anti-aging interventions by analyzing "wrinkleness" and other parameters.

Consistently predicting the next disruptive company is the holy grail if you are interested in start-ups. We've been testing out some Deep Learning techniques on our data to help make such predictions, and have had some interesting early results we thought we'd share. Word2vec is a Deep Learning technique first described by Tomas Mikolov and his team at Google in 2013, and in basic terms it allows a model to be built for a particular dataset (or corpus) in which words are represented as vectors. One of the most interesting outcomes of this approach is that we can gain insights about text by analysing word vectors arithmetically. In a classic example of the power of Word2Vec (trained on a large dataset), the vector of Queen is found to be almost equal to King Woman – Man.

Matching demand and supply seems mundane, but it takes a lot of work to actually make it happen. As we pointed out before in The Evolution of Marketplaces, marketplaces have evolved dramatically from horizontal listing based models like Craigslist to vertical transactional end-to-end marketplaces like Uber today. Every few years there are technological breakthroughs that allow entrepreneurs to adjust the dynamics of online marketplaces to make them more efficient. Native mobile apps, seamless payments and GPS tracking are just a few of the examples that have improved marketplaces substantially during the last two decades. Today, we are at the beginning of the next evolution: AI-powered marketplaces.

In a first, a team of physicists is using artificial intelligence (AI) to run a complex experiment to create an extremely cold gas trapped in a laser beam known as a Bose-Einstein condensate -- thus replicating the experiment that won the 2001 Nobel Prize. Bose-Einstein condensates are some of the coldest places in the universe -- far colder than outer space and typically less than a billionth of a degree above absolute zero. They can be used for mineral exploration or navigation systems as they are extremely sensitive to external disturbances, which allows them to make very precise measurements such as tiny changes in the Earth's magnetic field or gravity. Indian physicist Satyendra Nath Bose, along with German-born theoretical physicist Albert Einstein, founded the basis for Bose-Einstein statistics. It describes the statistical distribution of identical particles with integer spin, now called subatomic particle or the "God particle" Boson.

The idea of cyborgs running the world may seem like science fiction but may be becoming reality sooner than you think. No, there will not be an epic world war of us versus them. Instead, the shift from human to automation is slowly creeping into our society. Automation is already running assembly lines and even surgeries. From ATM's, pay-at-the-pump, self check-out, self-serve kiosks, order and pay at the table in restaurants, and all of the banking, shopping, record sharing, reading, socialization that takes place online, computers are already taking the place of humans.

Seeking to catch up to rivals in the realm of voice-controlled services, Apple soon will allow software developers to connect their apps to its Siri digital assistant for the first time, according to a report on Tuesday. Apple also may offer a device similar to the Amazon Echo voice-controlled speaker, according to the report on The Information tech news web site. The report, citing anonymous sources, said Apple will soon release a software development kit allowing other companies to integrate their apps and services with Siri, while the company is still developing the "smart" speaker project. Amazon, by contrast, has partnered with numerous other companies so that owners of its Echo speaker can use the device to call an Uber car, order a Domino's pizza or play music from Spotify. Google last week announced it too would offer a voice-controlled speaker device, dubbed Google Home, that would also be open to third party services.

Like any proud father, Gary Marcus is only too happy to talk about the latest achievements of his two-year-old son. More unusually, he believes that the way his toddler learns and reasons may hold the key to making machines much more intelligent. Sitting in the boardroom of a bustling Manhattan startup incubator, Marcus, a 45-year-old professor of psychology at New York University and the founder of a new company called Geometric Intelligence, describes an example of his boy's ingenuity. From the backseat of the car, his son had seen a sign showing the number 11, and because he knew that other double-digit numbers had names like "thirty-three" and "seventy-seven," he asked his father if the number on the sign was "onety-one." "He had inferred that there is a rule about how you put your numbers together," Marcus explains with a smile.

People don't want cars, they want rides. And they're scrambling to do something about it. Just months after GM poured money into Lyft (the one with the pink mustasche), Toyota and Volkswagen both said today they were joining up with other ride-hailing rivals. Toyota, meanwhile, is partnering with Uber to, among other things, let people automatically deduct their car payments from the fares they make as Uber drivers. Clearly automakers have Silicon Valley envy.

Google introduced a new group dedicated to making artificial intelligence more creative at Moogfest, a four-day music and technology festival in Durham, North Carolina, Quartz first reported. Called Magenta, the group will use its AI system TensorFlow to see if AI can be trained to create its own art, music, and video. The ultimate goal is to see if AI could give a listener "musical chills" by generating entirely new pieces of music, Quartz reported. Google made TensorFlow open source in November so that any developer can use it. TensorFlow works by using deep learning, a process where machines learn to complete tasks all on their own, to recognize images.