1 – Preparing for the Future of Artificial Intelligence

On Monday, The White House announced plans to co-host four upcoming public workshops on various AI topics to “spur public dialogue on artificial intelligence and machine learning and identify challenges and opportunities related to this emerging technology.” Spearheaded by the Office of Science and Technology Policy, the workshops will be rolled out over the next few months  (May to July) and will cover topics including implications in law and government, as well as the social and economic impacts. Workshop co-hosts include academic and non-profit institutions, as well as the National Economic Council. In addition, a new National Science and Technology Council (NSTC) subcommittee on machine learning and artificial intelligence will meet for the first time next week. The NSTC is currently working to leverage AI and machine learning technology in a variety of government services.

(Read the full article on The White House blog)

2 – eBay Acquires AI Startup ExpertMaker, Will Shut it Down Later this Quarter

eBay announced on Thursday its acquisition of ExpertMaker, a company that specializes in the use of AI to develop search tools for developers; the company also licenses its tools to firms looking to build subject-specific searches. The purchase aligns with eBay’s desire to integrate more artificial intelligence, machine learning, and big data analysis into its online services. Though financial terms were not disclosed, the deal is expected to close in the second quarter. At that time, ExpertMaker’s employees will become part of eBay’s structured data product and technology team; the San Jose-based tech company will also absorb any existing arrangements and customers that ExpertMaker has at the close of the deal.

(Read the full article on Venture Beat)

3 – Google is Feeding Romance Novels to Its Artificial Intelligence Engine to Make Its Products More Conversational

Google is using romance novels as a method for enlivening and making more realistic the conversational capabilities of its AI engine. The research team recently got results when their AI system was able to write sentences similar to those in the books. Why romance novels? Andrew Dai, the software engineer leading the project, says this genre is great for training because there is often a repeated or similar plot but with different sets of word choice. By reading thousands of these books, the AI was better able to detect sentences with similar meanings and gain a better understanding of language. Google’s AI engine completed cycles of writing its own sentences, evaluating new sentences against the original text, and then repeating the process over and over until it was able to write similar sentences on its own. Outside of search queries, Dai said this conversational technology could be applied to Google Inbox’s ‘Smart Reply’ product, which suggests responses to Google emails.

(Read the full article on BuzzFeed)

4 – Siri’s Creators Say They’ve Made Something Better that Will Take Care of Everything for You

Siri’s original creators have created a new virtual assistant app that can order custom takeout through speech recognition – all without downloading an app or doing any typing at all. Viv is the new vision of what Siri was meant to be when released as an independent app back in 2010. The now well-known chat bot was pioneered by Dag Kittlaus and Adam Cheyer. At the time of Siri’s creation, Cheyer was leading a 300-person team at SRI International, a nonprofit, government-funded research lab based in Palo Alto. Upon the initial release, Siri was much more ‘helpful’, able to skip search pages and other downloaded apps but still meet a range of commands, from buying tickets to reserving tables. Kittlaus had established service relationships with over 42 web service partnerships, all of which were essentially dissolved when Apple took over in 2011. Viv is the open system that Siri’s creators originally envisioned, and their next big challenge is to find a distribution model that gets Viv into the public’s hands in their originally intended image.

(Read the full article on The Washington Post)

5 – Building AI Is Hard—So Facebook Is Building AI That Builds AI

Building AI engines and systems is a specialized field (only a few hundred people worldwide are really driving these cutting-edge systems) and is a costly investment. Furthermore, building the systems requires researchers to go through quite a few hits and misses before getting the technology to work the way it’s intended to do so. In order to bypass some of the trench work, many leading tech companies are pioneering AI algorithms that help build AI models. Facebook engineers are designing an “automated machine learning engineer,” which stems from the Flow product that was originally designed to help engineers design, test, and implement machine learning algorithms on a large scale. Facebook’s machine-learning “engineer” is called Asimo; Facebook Engineer Hussein Mehanna, whose team pioneered Flow, said,. “It cannot yet invent a new AI algorithm, but who knows, down the road…” Facebook is not alone in this pursuit. Last year, Twitter purchased the startup WhetLab, which specializes in this type of AI system, and Microsoft is also testing similar models in what it calls “human-assisted search.”

(Read the full article on Wired)

Image credit: Time

 

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