Star Trek's stories are infused with myriad, complex technologies -- many of which can't easily be explained even by engineers. But what if they break down or learn too much? In the second season of Star Trek: Discovery, a sophisticated computer program known as Control ran amok, bent on fulfilling its mission in a way its human designers never intended. It took over computer systems and eventually starships and space stations. It also hacked into a human-robot hybrid and deployed swarms of nanobots for nefarious purposes.

At last week's Conference on Computer Vision and Pattern Recognition, a team of researchers from Massachusetts Institute of Technology (MIT) presented an innovative artificial intelligence (AI) system that can learn to segment anatomical brain structures from a single segmented brain scan image along with unlabeled scans--automating neuroscientific image segmentation. This novel AI system for neuroscience originated from a very distant genre of smartphone and gaming. Amy Zhao, a graduate student in the Department of Electrical Engineering and Computer Science (EECS) and Computer Science and Artificial Intelligence Laboratory (CSAIL), and the first author on the research, initially sought to create an app using convolutional neural network technology that could provide detailed information in real-time about cards from the game "Magic: The Gathering" based on a picture taken on a smartphone. The challenge is that this computer vision task would require a data set of photos that contains not only each of the 20,000 cards, but also many more images of each card with variation in appearance and attributes such as lighting. Creating such a data set manually would be painstakingly tedious and extremely time-consuming.

Rocky Mountain Power said yesterday that an artificial intelligence (AI) Home Energy Reports solution helped 330,000 of its customers saved over 41 gigawatt-hours (GWhs) of energy since being introduced less than a year ago. The solution produced the savings at an average of approximately four cents per kilowatt hour, a roughly 25 percent cost reduction as compared to conventional Home Energy Reports. "We were searching for the next wave of customer engagement and a way to drive customers toward a digital, two-way dialogue with us," Clay Monroe, director of customer relations for Rocky Mountain Power, said. "With AI reports we are able to quickly shift from conventional methods of reporting, using general peer comparisons, to true energy empowerment with itemized energy bills and personalized savings tips, while at the same time moving customers to digital reports." In 2018, Rocky Mountain Power replaced its existing Home Energy Reports program with AI-powered reports called iHERs. Approximately 330,000 customers in Utah, Idaho, and Wyoming received itemized energy reports for the first time, and more than 50 percent of these customers moved to digital reports with the help of the iHER solution.

Artificial intelligence no longer is the "next new thing." AI, machine learning, deep learning and other forms of algorithmic-based, automated processes are now mainstream and on their way to being deeply integrated into a wide range of front office, back office and in-the-field operations. And we certainly have seen a lot of great examples of AI being used to spot potential cybersecurity threats and preventing their infection on an organization. As business leaders, you have given at least some consideration to the notion that AI will completely replace soon your security operations center (SOC). After all, you've probably calculated the money it takes to run your SOC 24/7/365, and what it means when your CISO comes to an executive lunch or the board meeting and explains that we need more resources – i.e., people, technology and money – to fight new and more security threats.

AltDeep is a weekly curated newsletter focused on microtrend-spotting in data science, machine learning, and AI. Curated posts aimed at spotting microtrends in data science, machine learning, and AI. Read together, these two posts bring you up to speed quickly. This is a good report, tying together items report here and elsewhere. It goes beyond the big research milestones to talk about broader trends in industry and across borders. These items jumped out at me.

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While we don't yet have the personal androids promised to us in sci-fi movies, artificial intelligence (AI) is increasingly a part of our everyday lives, with Forbes declaring 2019 "the year AI will move into the mainstream." Thanks to AI, you can use your smartphone to deposit checks. And AI makes recommendations on Amazon and Netflix based on your usage and preferences. With AI becoming more deeply integrated into our professional and personal lives, the Indeed analytics team crunched platform data to learn more about AI jobs in 2019. What are the top positions?

TECHNOLOGY has advanced so much that one can now produce or alter audio or video content to show or present something that actually didn't happen. With deepfake technology (which combines "deep learning" with "fake"), one can, for example, superimpose someone's face over another person's to create a video to support his or her own agenda. The video is then circulated online, with disastrous consequences on the victim if the purpose is vile in nature, such as the sex video that is currently doing its rounds on social media in Malaysia. Deepfake is artificial intelligence (AI) at work, and there is little you can do to prevent it from happening to you, as highly-paid Hollywood actress Scarlett Johansson lamented. The subject of a fake porn video, she told the Washington Post (Dec 31, 2018): "The truth is, there is no difference between someone hacking my account or someone hacking the person standing behind me on line at the grocery store's account. It just depends on whether or not someone has the desire to target you. "Obviously, if a person has more resources, they may employ various forces to build a bigger wall around their digital identity.

Have you ever had a legitimate credit card transaction declined on the Web or your smartphone? It's a real hassle, to be sure. But now, thanks to a new payment protocol being introduced by Mastercard that relies on deep learning to authenticate purchasers, you should see fewer false positives, less fraud, and faster approvals to boot. Billions of dollars are on the line in the battle for control of the nation's electronic payment byways. Fraudsters are eager to exploit any technological weakness to steal others' hard-earned money, while banks, retailers, and consumers just want to make transactions as simple and secure as possible.

Artificial Intelligence (AI) is a lot of things. It's a game changer for business, it can enable humans to work smarter and faster than ever before, and it could potentially have a significant impact on economies and the labor market. But at the root of it all – the function which gives AI value – is the ability to make predictions. Calculating – more quickly and accurately than has ever been possible – what the likelihood is of a particular outcome, is the fundamental advance which AI brings to the table. To start with, it's worth defining what we mean when we talk about AI.