The all-in cost of litigation is, on the average over a 10-year time frame, about $350,000 per case. We show the data for this conclusion and describe the other key values of “less litigation”: avoiding losses to productivity and brand, and protecting leadership when regulatory investigations go south. We describe a workflow that preserves confidentiality and which is powered by a deep learning engine, which Intraspexion trains using text from a large number of previous lawsuits of the same case type. Our Proof of Concept pertained to employment discrimination. After we trained our deep learning engine, we found four high-scoring risks in a portion of Ken Lay’s Enron emails. Out of 7,665 emails, one of them was a legitimate risk. Now we offer an enterprise grade system (patent pending). The system indexes and extracts emails and attachments, passes the text to our pre-trained deep learning engine, outputs the scored emails in rank order to a select list of in-house attorneys, and lets them take it from there.
Learn how and why Google, Facebook, and Netflix pioneered the user of machine learning to personalize user experiences. Why did they realize that their future lay in machine learning and what were the pros/cons of turning over user engagement and decisions to machines.
Chris Monberg, President/CTO, Boomtrain
Chris is hyper-focused on building the team that is building the most advanced predictive personalization technology in the market. Previously, Chris was the VP of Interactive at Hornall Anderson, a global design firm. In addition to leading a team of designers, engineers, and strategists, Chris launched a R&D lab focused on redefining the relationships between brands, consumers, and technology.
Cirrus Shakeri, Ph.D., Chief AI Architect, AIBrain Inc.
Every person has an episodic memory that stores day-to-day experiences such as meeting people, visiting different locations, conversations with other people, and basically a trace of all his or her activities. Similarly, what a person knows in terms of knowledge about the world including the meaning of a conversation is stored in the person’s semantic memory. AIBrain has built a human-like AI memory system, called Memory Graph, that integrates episodic and semantic memories for an intelligent agent. In this session we will provide an overview of the Memory Graph capabilities, its applications, and its comparison with other well-known graph-based systems such as knowledge graphs, social graphs, and memory networks. We will also share our product roadmap for Memory Graph including a highly scalable version built on top of the Big Data framework, Apache Spark. Please see the following link for more information: http://aibrain.com/solutions/memory-graph/
Mounir Shita, Founder & CEO, Kimera Systems
Artificial General Intelligence (AGI) is human-like intelligence that can be applied to any purpose. A staple of science fiction, most AI experts believe AGI will be the most disruptive technology yet created, but one that won’t be possible for decades – maybe as long as 50 to 100 years. Except Kimera launched it in August. In this session, Kimera’s CEO explains how his company’s physics-based approach to intelligence made it possible to create the first commercially-deployable, single-algorithm AGI technology, that right now is learning common sense by observing sensor data. This session also touches upon the disruptive nature of AGI and its immediate business applications.
Rakesh Soni, Director of Products, Databricks
As enterprise data continues to explode in volume and complexity, deploying AI at enterprise scale requires a big data approach. Apache Spark – a fast and general engine for big data – is poised to power the next generation AI at enterprise-scale. Learn how Databricks is enabling organizations to build and deploy state-of-the-art AI applications with Spark.
Adam Devine, VP & Head of Marketing, WorkFusion
Winning game shows may grab more headlines, but automating the complex, manual business processes that burden operations teams within global banks, insurance companies, commerce and healthcare organizations delivers far more practical value. This session will zero in on high-ROI applications of AI within enterprise operations, define key capabilities required for end-to-end process digitization, and provide several real-life case studies of successful AI-powered automation deployments.
Dalia Asterbadi, CEO & Chief Data Scientist, verve.ai
There was a time when the value of a customer was dictated by the company. The definition of value was based on recency and frequency of transactions, and revenue attributed to that customer. This was what we deemed customer centricity. Never was value attributed based on the customer point of view. It didn’t need to. Today, with the pace of technology and abundance of content from publishers and users, it makes it increasingly difficult to garner the coveted attention of prospects, let alone our own customers. NOW, we can. Having the right actionable data can help us understand our customers: what they care about, and most important, their micro-moments that are time-relevant and business relevant that allows the business to interact at the right possible moment. It’s time to embrace true customer centricity and keep pace with the Customer’s Speed of Life.
Bruce Wilcox, Director of Natural Language Strategy, Kore Inc
Break through the bots, AI, machine learning, NLP, fundamental learning noise to quickly discover what all of this really means for the enterprise. See real-world use cases of how bots are bringing digital, mobile, and enterprise systems to life across every industry – from transportation to healthcare and everything in between. Simply put, we’ll reveal how bots can understand, perform, learn, and adapt to turn frustrating customer experiences into rich engaging interactions – for you to retain and capture more business. And see the ways your workforce can rid the mundane, everyday bottlenecks forcing them to choose between admin tasks and growing the business. Find out why now couldn’t be better timing to move past keep-up mode, outpace competitors vying for your customers, and put intelligent bots to work for you, your customers, and your workforce.