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Every year, companies spend 1.3 trillion dollars on 265 billion customer service calls. On average, the cost to find and hire a call center agent costs $4000 (not including salary), with an additional $4,800 for training -- and with frustrated agents tending to drop like flies in the face of an often brutally stressful job, these costs mount up. AI, or what IBM calls cognitive computing, is changing that. Autodesk began piloting the IBM Watson Conversation Service in June 2016 as a virtual agent called OTTO, later enhancing it and renaming it AVA (Autodesk Virtual Agent) in February 2017. The return on investment has been tremendous, says Rob High, IBM vice president and Watson chief technology officer and one of the featured speakers at VB Summit coming up on October 23 and 25 in Berkeley, CA.

Hollywood is beginning to recast artificial intelligence from being the lead character in movies to becoming the leading technology driving the industry. Producers and directors alike are discovering the power of a new kind of AI assistant: IBM Watson, the cognitive computing system that is enhancing the work of the human imagination and giving artists, filmmakers, and other creative minds the tools to uncover new ways of thinking and problem-solving. Imagine the ultimate "super-assistant" on the set to help make hundreds of decisions and take care of mundane tasks that free you up to concentrate on making the picture a box office success. IBM Watson can do this by pushing the boundaries of what producers and directors can create on the silver screen. It can analyze volumes of data -- think photos, online content, scripts, video -- and then recognize, inform and project from the patterns it identifies.

As if active portfolio managers didn't have enough challenges from computer-driven passive investing strategies, now machines are directly horning in on their territory. San Francisco-based EquBot LLC is launching the first ever exchange-traded fund to use artificial intelligence, according to a company statement on Tuesday. Employing International Business Machines Corp.'s Watson platform, the AI Powered Equity ETF, ticker AIEQ, will attempt to mimic an army of equity research analysts working around the clock, according to Art Amador, co-founder of EquBot. "There has been an explosion of information," Amador said by phone. "AI provides a more informed way of investing."

Machine learning has already made its mark in healthcare as well as fraud detection, with PayPal leveraging it to fight against money laundering. And both new and emerging machine learning technologies are set to make waves in the realms of B2C and B2B marketing. A supercomputer that combines AI with superior analytical software, IBM Watson is a fully-optimized question answering system - and it processes at a rate of 80 teraflops (trillion floating-point operations per second). Enticed by its incredible cognitive abilities, brands including Staples and Autodesk are successfully using IBM Watson's technology. For Autodesk, their goal was to reduce the turnaround time and overall costs of their customer support initiatives.

For this project, we will be using the bAbI data set created by Facebook. This data set, like all QA data sets, contains questions. Questions in bAbI are very straightforward, although some are trickier than others. All of the questions in this data set have an associated context, which is a sequence of sentences guaranteed to have the details necessary to answer the question. In addition, the data set provides the correct answer to each question.

The typical goal of an experience manager in an interactive narrative is to create a sense of shared authorship that lends the player freedom to personalize the experience while still meeting the author's constraints on structure. This can be difficult when the player and author only communicate with one another through their actions. Each new action causes new questions to arise, assumptions to be made, and old questions to be answered. In this paper, I propose a technique called Mutual Implicit Question Answering, or MIQA, designed to allow an experience manager to both perceive and influence the momentum of an interactive story. It combines a generative model of narrative planning with analytical models of question answering and salience. I also present the results of a small, qualitative study of how people construct interactive narratives that lends insight for the eventual evaluation of a MIQA experience manager.

A recent interview with a former IBM employee who worked in the company's life sciences group shows that the hype of artificial intelligence's impact on healthcare was felt internally too. Severak reported accounts in recent months, including the well-researched piece in Stat News, have documented how IBM Watson's foray in healthcare has been far less noteworthy than advertised. In fact, other companies in the AI space have not hesitated to call out the company for overstating its capabilities. At MedCity News' own cancer innovation conference – CONVERGE – earlier this summer in Philadelphia, Zach Weinberg, co-founder at Flatiron Health, who was a panelist along with an IBM Watson Health representative, took IBM to task as recorded by this tweet. "@IBMWatson not intellectually honest about what it is actually doing; instead using buzz wrds" @zachweinberg @flatironhealth #mcConverge Similarly, this former employee, who declined to speak on the record for fear of angering his powerful former employer, said that large marketing budgets have yielded a lot of advertising but no tangible off-the-shelf product.

A successful platform has several essential elements, according to Ruchir Puri, chief architect at IBM Watson. Puri, an IBM fellow, spoke with SearchCIO at this year's Platform Strategy Summit hosted by the MIT Initiative on the Digital Economy. In this video, he discusses the essential components of the IBM Watson platform, how he sees the platform evolving and what factors are contributing to its growth. Below are excerpts from the interview; click on the player to hear the interview in its entirety. How do you define platform and how do you see platforms changing in the next five years?

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