The USC Center for Artificial Intelligence in Society (CAIS)--a joint venture of the USC Suzanne Dworak-Peck School of Social Work and USC Viterbi School of Engineering--will host its first Visiting Fellows Program this summer focused on employing AI to help solve complex societal problems. As part of the Fellows Program, visiting researchers from all over the world will come to USC this summer for up to three months to learn from a working model established by the Center's co-founders, Eric Rice of the USC Suzanne Dworak-Peck School of Social Work and Milind Tambe of the USC Viterbi School of Engineering. The two had successfully collaborated by employing AI to ensure that homeless youth shared important public health information among peers in the youths' own social networks. "Using artificial intelligence to promote the greater good is an emerging area of study with huge potential," said Eric Rice, co-director of CAIS and associate professor at the USC Suzanne Dworak-Peck School of Social Work. "Our goal in establishing this fellowship is to bring together the best and brightest scholars in artificial intelligence and social work to explore breakthrough solutions to age-old problems plaguing many of our cities and communities." Topics to be studied by fellows this summer include suicide prevention among college students; social support for North Korean refugees to help their integration into South Korean society; wildlife conservation through poaching prevention in developing nations' national parks; HIV and substance abuse prevention for homeless youth; and predicting and reducing gang violence in Los Angeles.

Topic models such as Latent Dirichlet Allocation (LDA) have been widely used in information retrieval for tasks ranging from smoothing and feedback methods to tools for exploratory search and discovery. However, classical methods for inferring topic models do not scale up to the massive size of today's publicly available Web-scale data sets. The state-of-the-art approaches rely on custom strategies, implementations and hardware to facilitate their asynchronous, communication-intensive workloads. We present APS-LDA, which integrates state-of-the-art topic modeling with cluster computing frameworks such as Spark using a novel asynchronous parameter server. Advantages of this integration include convenient usage of existing data processing pipelines and eliminating the need for disk writes as data can be kept in memory from start to finish. Our goal is not to outperform highly customized implementations, but to propose a general high-performance topic modeling framework that can easily be used in today's data processing pipelines. We compare APS-LDA to the existing Spark LDA implementations and show that our system can, on a 480-core cluster, process up to 135 times more data and 10 times more topics without sacrificing model quality.

If you get into a car accident in China, you can simply pull out your smartphone, take a photo, and file an insurance claim with an AI system. That system, from Ant Financial, will automatically decide how serious the ding was and process the claim accordingly with an insurer. It shows how the company--which already operates a hugely successful smartphone payments business in China--aims to upend many areas of personal finance using machine learning and AI. The e-commerce giant Alibaba created Ant in 2014 to operate Alipay, a ubiquitous mobile payments service in China. If you have visited the country in recent years, then you have probably seen people paying for meals, taxi rides, and a whole lot more by scanning a code with the Alipay app.

When it comes to online search, one company dominates like no other: Google parent Alphabet Inc. (NASDAQ:GOOGL) (NASDAQ:GOOG). In the first quarter of 2017, the company commanded a 79% worldwide market share of desktop search and a stunning 96% in the mobile and tablet category according to netmarketshare.com. Baidu, Inc. (NASDAQ:BIDU) has been called the "Google of China" and has followed its U.S. counterpart into a surprising number of emerging technologies, including artificial intelligence (AI) and autonomous driving. Baidu is the search leader on its home turf after Google abandoned China because of censorship in 2010. Baidu is considered to be among the forerunners in both AI and self-driving cars in its native China, but technologically, it lags Google in both.

We've seen companies looking into high-speed trains transportation that will take people from New York City to Washington, D.C., faster, but France is taking it up a step: driverless high-speed trains. France's railway system, SNCF, said it's working on a TGVs (high-speed trains) that are autonomous, according to FranceInfo. The TGVs can also transport people to other countries, like Belgium, Spain and Italy. SNCF is reportedly working on a "drone train" project, which will be equipped with autonomous technology. The system will include external sensors that will anticipate obstacles on the track and automatically brake, if necessary.

Source: IDC Global Digital Data (in Exabyte) Enabling forces behind Artificial Applications 5. Artificial Intelligence, May 2016 5 Scope of report This report covers companies that provide the infrastructure for creating Artificial Intelligence. These Infrastructure companies include those working on Machine Learning, Deep Learning based platforms, libraries. Some of theses companies also provide platforms for Natural Language Processing and Visual Recognition. In the Applications section, the report covers companies leveraging AI techniques to build applications tailored for end use in Enterprise, Industry & Consumer sectors. Over $1B has been invested in AI-Infrastructure startups since 2010 with $340M being invested in 2015.

It is ironic, but perhaps not unexpected, that many organizations who want the benefits of using an Agile approach to deliver software use a waterfall approach to adopting Agile practices: they form plans, they set milestones, and they measure progress by how many teams they have engaged. Old habits die hard, but like most waterfall software projects, most waterfall-style Agile adoption efforts fail to produce the results desired. The problem is that to get the results they want, they have to change their culture and cultures are very hard to change. To paraphrase Peter Drucker, "culture eats Agile for breakfast." Successful approaches are opportunistic and leverage the power of self-organization to achieve lasting change.

These days, you hear a lot about machine learning (or ML) and artificial intelligence (or AI) – both good or bad depending on your source. Many of us immediately conjure up images of HAL from 2001: A Space Odyssey, the Terminator cyborgs, C-3PO, or Samantha from Her when the subject turns to AI. And many may not even be familiar with machine learning as a separate subject. The phrases are often tossed around interchangeably, but they're not exactly the same thing. In the most general sense, machine learning has evolved from AI. In the Google Trends graph above, you can see that AI was the more popular search term until machine learning passed it for good around September 2015.

The rise of artificial intelligence (AI) is perhaps the single biggest challenge facing today's brands. This may sound like hyperbole, but anyone familiar with the development of AI over the past few years will know how disastrous it can be for brands to get it wrong. Microsoft's chatbot Tay is the obvious example. Microsoft quickly shut down the project, but not before receiving a barrage of criticism. Even some AIs that have been considered successes have stirred up branding controversies.

With Yahoo now part of the Verizon empire, Jefferson Graham takes a good look at the homepage, and finds it....rather dated. This week Yahoo, one of the oldest Internet brands, became part of the Verizon empire, one of the companies (along with HuffPost, AOL and TechCrunch) that live within the newly created Oath unit, which hopes to compete against Google and Facebook as a bulked-up alternative for online advertisers. This Sept. 23, 2016 file photo shows the Yahoo logo pictured on a computer monitor in Taipei, Taiwan. Verizon on Tuesday, June 13, closed its $4.48 billion acquisition of Yahoo. And let's take a quick minute and look at the jewel of Oath, the beleaguered and ignored Yahoo.com.