One of the newest approaches is centered on a dating platform driven by algorithms to help establish a relationship that will last. This provides important personal details for the user. These sites then obtain permission for the user to get more insight through social media platforms, online shopping histories, streaming sites and preferences. This data offers a lot of information about the user. This is important because many people are not completely honest when they fill out the questionnaire.

You've seen the ways AI has been leveraged in recent years: Tesla has self-driving cars, chatbots answer customer service queries, and Siri can send a text for you or set a reminder. In 2018 we're likely to see AI permeate our daily lives in much more real ways. Everything from the way we make purchases to the way we create content is likely to see a significant transformation. Here are five artificial intelligence advancements that will work their way further into your life in 2018. Sure, you can already unlock the latest iPhones and confirm some payments with your face.

What if we delegated so much to autonomous AI and intelligent machines that They passed a law that forbids humans to carry out a number of professions? We conceive the plot of a new episode of Black Mirror to reflect on what might await us and how we can deal with such a future.

Due to recent explosion of text data, researchers have been overwhelmed by ever-increasing volume of articles produced by different research communities. Various scholarly search websites, citation recommendation engines, and research databases have been created to simplify the text search tasks. However, it is still difficult for researchers to be able to identify potential research topics without doing intensive reviews on a tremendous number of articles published by journals, conferences, meetings, and workshops. In this paper, we consider a novel topic diffusion discovery technique that incorporates sparseness-constrained Non-negative Matrix Factorization with generalized Jensen-Shannon divergence to help understand term-topic evolutions and identify topic diffusions. Our experimental result shows that this approach can extract more prominent topics from large article databases, visualize relationships between terms of interest and abstract topics, and further help researchers understand whether given terms/topics have been widely explored or whether new topics are emerging from literature.

Now that Google Assistant has a slew of voices to choose from, shouldn't you have an easy interface for picking one of those voices? Google is rolling out an update that gives US users a new, simple interface for changing Assistant's voice. It's very colorful, to put it mildly: you just tap on a color associated with a given voice (Google told us it chose them at random) and listen to be sure they're the dulcet tones you want to hear. The addition should be platform-agnostic and will be widely available in the US by the end of the week. It's not certain when other countries will receive the fresh interface, but that's also dependent on having multi-voice support in the first place.

In a market such as this, Sonos--with trailing 12-month sales now just topping $1 billion--would appear hopelessly outclassed. But papers for an initial public offering filed on Friday show that the maker of high-end wireless speakers still has a hand it can play. After being caught flat-footed by the surging popularity of Amazon Echo speakers in late 2015, Sonos shifted its approach. The company struck a deal to embed Amazon's Alexa voice technology into its own line of smart speakers, the first of which began shipping late last year. That helped Sonos deliver a 36% jump in device unit sales year over year for the first quarter ended December, with revenue rising 26% to $469 million.

Apple is creating a new AI/ML team that brings together its Core ML and Siri teams under one leader in John Giannandrea. Apple confirmed this morning that the combined Artificial Intelligence and Machine Learning team, which houses Siri, will be led by the recent hire, who came to Apple this year after an eight-year stint at Google, where he led the Machine Intelligence, Research and Search teams. Before that he founded Metaweb Technologies and Tellme. The internal structures of the Siri and Core ML teams will remain the same, but they will now answer to Giannandrea. Apple's internal structure means that the teams will likely remain integrated across the org as they're wedded to various projects, including developer tools, mapping, Core OS and more.

Apple has selected former Google executive John Giannandrea to lead a new artificial intelligence and machine learning team, the company confirmed on Tuesday.

AI continues to evolve and pervade business functions and applications across industries. In retail, AI's use has moved well beyond warehouse management and e-commerce algorithms. Companies are now deploying it to help solve far more complex problems and facilitate functions across their businesses. In this report, our second in the Artificial Intelligence in Retail series, we outline some of the key areas in which 30 global retailers are using AI across business functions. We also examine in detail how two of the largest global technology-led retailers, Amazon and Alibaba Group, are using AI in alignment with our proprietary CORE framework.

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