Artificial intelligence inside Adobe Creative Cloud could soon help creatives, well, spend more time being creative. At Adobe's 2016 MAX Conference, which starts on November 2, the company announced a new framework for Creative Cloud using artificial intelligence, called Adobe Sensei. Along with the new AI additions, Adobe unveiled several new programs and updates that show where the design software giant is headed in the next several months. Highlights of the company's first-day announcements include enhanced virtual reality tools inside Adobe Premiere Pro, design tools for merging 2D and 3D design, expansion of the Adobe Stock platform, and several other Creative Cloud updates from Adobe Experience Design to Photoshop. Adobe Sensei is expected to take the artificial intelligence that Adobe is already using – like facial recognition and the content-aware tools inside Photoshop, for example – and leverage additional machine learning techniques to automate the more mundane tasks inside the Creative Cloud, Adobe Document Cloud, and Adobe Marketing Cloud.

Machine learning, which is the basis for most commercial artificial-intelligence systems, is intrinsically probabilistic. An object-recognition algorithm asked to classify a particular image, for instance, might conclude that it has a 60 percent chance of depicting a dog, but a 30 percent chance of depicting a cat. At the Annual Conference on Neural Information Processing Systems in December, MIT researchers will present a new way of doing machine learning that enables semantically related concepts to reinforce each other. So, for instance, an object-recognition algorithm would learn to weigh the co-occurrence of the classifications "dog" and "Chihuahua" more heavily than it would the co-occurrence of "dog" and "cat." In experiments, the researchers found that a machine-learning algorithm that used their training strategy did a better job of predicting the tags that human users applied to images on the Flickr website than it did when it used a conventional training strategy.

It wasn't done in a day or a week or over a few months. Almost since the day Apple introduced its voice assistant on October 4, 2011, Siri has undergone an almost continual series of brain transplants that shifted its silicon-powered mind from pure Artificial Intelligence to AI powered, in part, by machine learning. SEE ALSO: Here's how to use apps with Siri in iOS 10 Apple recently shared with me its perspectives on artificial intelligence, where it fits in the Apple ecosystem, which is, apparently, everywhere, and how it can be grown while respective users' privacy. In particular, though, they focused on how the introduction of machine learning transformed its now five-year-old digital assistant. Machine learning is considered a toolset within AI.

IBM Chief Executive Officer Ginni Rometty sees proprietary data combined with artificial intelligence technology as the competitive advantage for companies going forward. When IBM works with clients, it trains a unique version of its artificial intelligence technology, Watson, using proprietary data, and that information creates individual business insights that stay with the customer, Rometty said. That's how Watson is different from its competitors that offer similar services around data analytics and machine learning, she said last week in a speech at the company's World of Watson event in Las Vegas. "We made an important architectural decision for all our clients--all their data, it's their accumulated knowledge," she said. Rometty envisions a future in which all enterprises will add artificial intelligence to help automate business processes, improve productivity and increase sales--and she believes that they're likely to turn to IBM to provide that AI software.

Artificial intelligence can thank Hollywood for its bad rep. Movies like "Ex Machina" and the "Terminator" series conjure up futuristic doomsday scenarios where intelligent machines wreak havoc on humans. However, in real life, humans are already surrounded by artificial intelligence. Amazon and Netflix recommendation engines suggest books or movies based on previous selections, Google Now reroutes drivers around traffic accidents on the commute home, and smartphone digital assistants like Apple's Siri and Microsoft's Cortana answer questions about the weather and sports scores. Brands are using artificial intelligence to build better customer experiences and they're just getting started.

Did Artificial Intelligence Just Make a Major Advance? Are the Experts Worried About the Existential Risk of Artificial Intelligence? Humans does A.I. better than Westworld without resorting to nudity and orgies Here's how close AI is to beating humans in different games'Nightmare Machine' is an AI project that uses our own fears against us 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.

Oren Etzioni, a well-known AI researcher, complains about news coverage of potential long-term risks arising from future success in AI research (see "Are Experts Worried About the Existential Risk of Artificial Intelligence?"). After pointing the finger squarely at Oxford philosopher Nick Bostrom and his recent book, Superintelligence, Etzioni complains that Bostrom's "main source of data on the advent of human-level intelligence" consists of surveys on the opinions of AI researchers. He then surveys the opinions of AI researchers, arguing that his results refute Bostrom's. It's important to understand that Etzioni is not even addressing the reason Superintelligence has had the impact he decries: its clear explanation of why superintelligent AI may have arbitrarily negative consequences and why it's important to begin addressing the issue well in advance. Bostrom does not base his case on predictions that superhuman AI systems are imminent.

Despite predictions of a tech slowdown, big-name businesses like Facebook, Apple, and IBM are pouring resources into artificial intelligence (AI), changing the field and gaining the interest of venture capitalists everywhere. As investors actively seek innovative players in the AI space, more entrepreneurs are gravitating toward the technology as they build and grow their own companies. Businesses such as Sentient, Context Relevant, and Scaled Inference all continue to work on their own multifunction AI platforms for computation and analysis, but this is only a small segment of the AI market. Multiple businesses now invest time and effort into purpose-built AI products. Here are a few of the businesses that are capturing attention in their respective industries for their AI work. With total capital of $58 million, AI specialist Kensho is already showing just how serious investors are about the technology.

A lot of the press we see on AI tends to be of the big iron variety recognition algorithms for Facebook images, Google TensorFlow and IBM Watson systems. But AI is already on edge-nodes such as smartphones and home automation hubs, for functions like voice-recognition, facial recognition and natural language understanding. Qualcomm believes there are good reasons for functions like this not only to stay on the edge but to continue to evolve there. I talked with Gary Brotman, director of product management at QTI to understand what s driving this trend. Part of the reason is availability.

A battle between the U.S. government and China is now brewing in the market for semiconductors, the foundation of electronics. The U.S. alleges that China is rigging the semiconductor market in its favor by indulging in unfair trade practices. "This unprecedented state-driven interference can distort the market and undermine the innovation ecosystem," Penny Pritzker, U.S. secretary of commerce, said during a Wednesday event organized by the Center for Strategic and International Studies. The Chinese government is using its own resources to artificially reduce chip prices, which is hurting global competition, the U.S. alleges. Pritzker called on China to play fair and in accordance with "global trading rules," with healthy competition and free and fair trade, not through state investments aimed at distorting global markets.