Event detection (ED) identifies and classifies event triggers from unstructured texts, serving as a fundamental task for information extraction. Despite the remarkable progress achieved in the past several years, most research efforts focus on detecting events from formal texts (e.g., news articles, Wikipedia documents, financial announcements). Moreover, the texts in each dataset are either from a single source or multiple yet relatively homogeneous sources. With massive amounts of user-generated text accumulating on the Web and inside enterprises, identifying meaningful events in these informal texts, usually from multiple heterogeneous sources, has become a problem of significant practical value. As a pioneering exploration that expands event detection to the scenarios involving informal and heterogeneous texts, we propose a new large-scale Chinese event detection dataset based on user reviews, text conversations, and phone conversations in a leading e-commerce platform for food service. We carefully investigate the proposed dataset's textual informality and multi-source heterogeneity characteristics by inspecting data samples quantitatively and qualitatively. Extensive experiments with state-of-the-art event detection methods verify the unique challenges posed by these characteristics, indicating that multi-source informal event detection remains an open problem and requires further efforts. Our benchmark and code are released at \url{https://github.com/myeclipse/MUSIED}.

Slate is making its coronavirus coverage free for all readers. Subscribe to support our journalism. I've been single for about two and a half years. Not unhappily so, but I keep a busy schedule that allows me time to go out and meet new people or to go on dates, but rarely both. Despite that, I've been able to maintain a rather pleasing love life, thanks in great part to the apps. Obviously, I haven't yet settled down with Mr. Right Enough just yet, but I've connected with great friends, met remarkable lovers, and explored both fleeting and long-term romance on my own terms.

AXA UK claims handlers are piloting a machine-learning tool to support the firm in making quicker and more accurate decisions regarding motor claims. It then assesses how much it would cost to fix or write off vehicles, aiming to make the right decision as soon as the claim is notified. The pilot starts today (10 February) in AXA's Ipswich office, and the plan is to integrate RoRI into the Guidewire software used by AXA later this year. Waseem Malik, executive managing director, claims, said: "Claims analytics is at the centre of our business strategy, which relies on data-driven insights. Our ambition is to have seamless interactions with our customers. We believe that by empowering our people through technology, we will get closer to our customers."

Artificial intelligence has already permeated our lives as consumers. The transformation was discreet, but it has made things better in every way. The last time you used Netflix, an AI helped you decide what to watch, when you shopped on Amazon, an artificial intelligence influenced what you purchased, and when you ordered that Uber, an AI helped find the best driver for you. In all of these instances, artificial intelligence improved the way in which you interacted with the product or service. Ultimately, the positive interaction that was generated when you found the perfect show to binge-watch, toaster to purchase, or got a ride, was due to an AI that optimized your experience.

New technologies don't just change the world, they change our language too. The automobile era gave us over a thousand new words and phrases such as limousine, drive through, hot rod, tailgate, and muscle car. Computers gave us chips, CPUs, beta testers, operating systems, programs and bugs. The Internet has already contributed hundreds of new words and new meanings to old words, including spam, meme, hashtag and trolling. Technology gives us new experiences, new abilities, and new problems.

Artificial Intelligence is an industry which is growing permanently, and there has been significant investment in the space in the last years. The market value of AI is expected to reach $38bn in 2025. Here's a list of the top five sales and marketing companies that use Artificial Intelligence to power up businesses. Invoca provides software for sales and marketers looking for call tracking and analytics. With Invoca, you can drive, track and automate inbound calls.

Google demonstrated a jaw-dropping new capability in Google Assistant earlier this month, allowing the Assistant to make calls on your behalf. While Google Duplex generated controversy and discussion around artificial intelligence, Microsoft has been testing similar technology with millions of people in China. At an AI event in London today, Microsoft CEO Satya Nadella showed off the company's Xiaoice (pronounced "SHAO-ICE") social chat bot. Microsoft has been testing Xiaoice in China, and Nadella revealed the bot has 500 million "friends" and more than 16 channels for Chinese users to interact with it through WeChat and other popular messaging services. Microsoft has turned Xiaoice, which is Chinese for "little Bing," into a friendly bot that has convinced some of its users that the bot is a friend or a human being.

Google CEO Sundar Pichai demonstrated new AI technology that can use human-like speech to carry on phone conversations at the Google I/O 2018 Conference on Tuesday in Mountain View, Calif. Google CEO Sundar Pichai demonstrated new AI technology that can use human-like speech to carry on phone conversations at the Google I/O 2018 Conference on Tuesday in Mountain View, Calif. On the first day of Google's annual conference for developers, the company showed off a robot with a voice so convincingly human that it was able to call a salon and book a haircut – never revealing that it wasn't a real person making the call. CEO Sundar Pichai demonstrated the new AI technology on Tuesday at the Google I/O conference, playing audio of a female-voiced bot speaking with a receptionist over the phone, and then a male-voiced bot making a restaurant reservation. The bot peppers its speech with "um", "uh", and "mmm hmm" in order to imitate the tics and rhythms of human speech.

Twenty-five years ago, Nikos Papanikolopoulos started his work in the University of Minnesota's Artificial Intelligence, Robotics and Vision lab. For the first five years, the lab researched and developed robotics that were largely unheard of. In 1997, his lab had its landmark moment, when the U.S. Military used his lab's Scout robot to survey dangerous war zones in lieu of humans. It built the lab's reputation into a national standout. Today, Papanikolopoulos and his lab are part of a rapidly emerging field of science fusing yesterday's unbelievable with today's uncharted -- artificial intelligence.

With Elon Musk and Mark Zuckerberg sparring over its ethics and China announcing its intention to create a $150 billion domestic industry based on it, Artificial Intelligence is perhaps the most discussed topic in the tech news cycle. It's likely to be a talking point no matter what your favourite watering hole for tech news. Billions of dollars have been invested by VCs in AI since 2016 with the US and China leading the race in record funding in terms of deals and dollars. In sharp contrast, Indian startups have collectively raised less than $100 million from (2014-2017YTD), according to data from startup analytics firm Tracxn -- that's smaller than Andrew Ng's recently launched $150 million VC fund. Another way to look at it: Grammarly, a Valley-based spell check tool raised more dollars than all of India's AI startups put together in the past three and a half years.