LOS ANGELES – Google's Stadia video game streaming service just got a hefty collection of games to attract newcomers to its forthcoming cloud-based subscription offering. But Ubisoft's announcement Monday that its new Uplay service with more than 100 games will be available on Stadia, may have clarified – or confused – players about what's to come. Ubisoft will be making its new Uplay all-you-can-eat PC video game service ($14.99 monthly), which launches Sept. 3 with 100-plus games including "Assassin's Creed" and "Rainbow Six" titles, available to Stadia users next year. This will make it easier for players to play Ubisoft's games, said Brenda Panagrossi, the publisher's vice president of platform and product management. "Stadia is a new generation platform where you can play our games on any device," she said.

The Avengers assembled again, only it wasn't on a movie screen. On Monday night, video game publisher Square Enix revealed the first details of "Marvel's Avengers," which will launch on May 15, 2020. The video game will be available for PC, PlayStation 4, Xbox One, and Google's new Stadia streaming service. Among the game studios working on the Avengers game are Crystal Dynamics, who previously worked on the Tomb Raider franchise; and Eidos Montreal, best known for their work on the popular Deus Ex series. What should video game players expect when they don the role of an Avenger next year?

The Atari VCS, a new video game system that plays 100-plus games originally played on the '70s console, is due in spring 2019. Pre-orders starting at $199 begin May 30. As video game fans get excited about PlayStation, Xbox, and Nintendo Switch games during this week's Electronic Entertainment Expo (E3), a classic name is poised for a comeback. Atari announced Tuesday its VCS video game system will open up for preorders this week, with retailers GameStop and Walmart serving as exclusive partners. Pricing for the console starts at $249.99, with a top price of $389.99 for system bundles, reads a press release from Atari.

While supervised learning has tremendously improved AI performance in image classification, a major drawback is its reliance on large-scale labeled datasets. This has prompted researchers to explore the potential of unsupervised learning and semi-supervised learning -- techniques that forego data annotation but have their own drawback: diminished accuracy. A new paper from Google's UK-based research company DeepMind addresses this with a model based on Contrastive Predictive Coding (CPC) that outperforms the fully-supervised AlexNet model in Top-1 and Top-5 accuracy on ImageNet. CPC was introduced by DeepMind in 2018. The unsupervised learning approach uses a powerful autoregressive model to extract representations of high-dimensional data to predict future samples.

Collaborative robots, or cobots, have been working with humans on the factory floor for years, but when it comes to the large-scale industrial robots that can lift and move massive pieces of manufacturing, the danger to human workers is so great that the robots are bolted down to the factory floor behind fences so a human never comes near them. That is starting to change as robotics becomes more widespread across industries. Today there are, on average, 84 robots for every 10,000 workers in the U.S., according to the International Federation of Robotics. This places the U.S. second to Europe, at 99 units, and ahead of Asia, which to date averages 63 units (though the most roboticized country in the world is South Korea). While these next-generation robots are revolutionizing companies and expanding their bottom line, there is one very real caveat: Their increasing interactivity and mobility opens up the possibility of injury to human co-workers.

Noelia Jiménez Martínez is Head of Data Science and Astrophysics at Unbound. She holds a PhD in Numerical Astrophysics from the UNLP (La Plata, Argentina) applied to Galaxy Formation and Chemical Evolution. Before transitioning from Academia, she was an Astrophysics Researcher at the University of St Andrews (Scotland), and previously had several postdocs positions in different universities across Europe that gave her the chance to collaborate with a huge diversity of people from several fields and backgrounds. Prior to joining Unbound she worked as a Data Science Consultant (Pivigo) in London, where she managed several data science teams working with big-to-small companies (Barclays, Criteo, Royal Mail, startups, etc) and lectured academics transitioning to Industry in the S2DS (science to data science school) in fields as Machine Learning, Statistics and Deep Learning. She is also the author of a book exploring/building empathy and social skills among academics from'hard' sciences: 'Data: A Guide to Humans'.

No one wants to miss out on the A.I. revolution. Leery to their lose edge or fall behind competitors, companies big and small are scrambling to deploy artificial intelligence. That was the consensus of a room of top executives gathered at Fortune's CEO Initiative in New York City on Monday afternoon. Though many noted their companies are working to enhance business processes or consumer experience with A.I., the business leaders identified a variety of challenges to those efforts. "The biggest hurdle is talent and the skill of the leadership team," said Daniel Pacthod, a senior partner at consulting giant McKinsey & Co. "It has to be a top-three CEO topic. The CEO then has to say, 'I have to retrain my leadership team, not only at the analytics level but from top to bottom.'"

Robots must be smarter if they're going to pack boxes in warehouses, scan inventory in stores, and even care for the elderly. The rise of machine learning in recent years is making that possible. Steady innovation has led to robots that can independently "learn" to navigate tight corridors and grasp delicate objects without crushing them. Some of the leading American and Japanese robotics companies and investors recently gathered in Menlo Park, Calif. to discuss artificial intelligence in robotics and its impact on business. But it may require some cooperation between the U.S. and an important overseas ally.

Just because we can use it, should we? That's the question more and more people are asking about face recognition technology, software that's already in our phones and our social media feeds and many security systems. San Francisco leaders have voted to ban the police from using it, and even some in the tech industry say there should be limits. BRAD SMITH: It's the kind of technology that can do a lot of good for a lot of people, but it can be misused. It can be used in ways that lead to discrimination and bias.

Much as robots have transformed entire swaths of the manufacturing economy, artificial intelligence and automation are now changing information work, letting humans offload cognitive labor to computers. In journalism, for instance, data mining systems alert reporters to potential news stories, while newsbots offer new ways for audiences to explore information. Automated writing systems generate financial, sports and elections coverage. A common question as these intelligent technologies infiltrate various industries is how work and labor will be affected. In this case, who – or what – will do journalism in this AI-enhanced and automated world, and how will they do it?