R has long been criticized for its limitations on scalable data analytics. What's needed is an R-centric paradigm that enables data scientists to elastically harness cloud resources of manifold computing capability for large-scale data analytics. Le Zhang and Graham Williams demonstrate how to operationalize an E2E enterprise-grade pipeline for big data analyticsall within R.

Conversational interfaces are a novel way to interact with computers. Human language is becoming the new user interface, bots the new apps, and personal digital assistants the new browsers. Lili Cheng, an architect who directs the Microsoft Research Lab behind Xiaoice and Tay, will reflect on human reactions to our bot counterparts.

Peter Skomoroch, an authority on data science and practical AI, offers a deep survey of the artificial intelligence landscape, covering recent developments, popular toolkits and services, and current thinking on strategies for AI.

The power of artificial intelligence and advanced analytics emerges from the ability to analyze and compute large, disparate datasets from varied devices and locations, such as predictive medicine and automated cars, at lightning-fast speed. Martin Hall explains why collaboration and openness are the key elements driving innovation in AI.

Gary Marcus explores the gap between what machines do well and what people do well and what needs to happen before machines can match the flexibility and power of human cognition.

When Hollywood portrays artificial intelligence, it's either a demon or a savior. But the reality is that AI is far more likely to be an extension of ourselves. Strata program chair Alistair Croll looks at the sometimes surprising ways that machine learning is insinuating itself into our everyday lives.

Francisco Webber offers a critical overview of current approaches to artificial intelligence using "brute force" (aka big data machine learning) as well as a practical demonstration of semantic folding, an alternative approach based on computational principles found in the human neocortex. Semantic folding is not just a research prototypeit's a production-grade enterprise technology.

Genevieve Bell explores the meaning of intelligence within the context of machines and its cultural impact on humans and their relationships. Genevieve interrogates AI not just as a technical agenda but as a cultural category in order to understand the ways in which the story of AI is connected to the history of human culture.

Mark Hammond explains how Bonsais platform enables every developer to add intelligence to their software or hardware, regardless of AI expertise. Bonsais suite of toolsa new programming language, AI engine, and cloud serviceabstracts away the lowest-level details of programming AI, allowing developers to focus on concepts they want a system to learn and how those concepts can be taught.

Jay Wang and Jasmine Nettiksimmons explore the business model of Stitch Fix, an emerging startup that uses artificial intelligence and human experts for a personalized shopping experience, and highlight the challenges encountered implementing Stitch Fix's recommendation algorithm and interacting AI with human stylists.

Deep learning has made a major impact in the last three years. Imperfect interactions with machines, such as speech or image processing, have been made robust by deep learning that finds usable structure in large datasets. Naveen Rao outlines deep learning challenges and explores how changes to the organization of computation and communication can lead to advances in capabilities.

Babak Hodjat discusses the progress in AI, diving into how AI can offer unique solutions in verticals such as investment, medical diagnosis, and ecommerce. Babak details how using massively scaled distributed evolutionary computation, mimicking biological evolution, allows an AI to learn, adapt, and react faster to provide customers with the answers and decisions they need.

Highly connected, interactive artificial intelligence systems surround us daily, but as smart as these systems are, they lack the ability to truly empathize with us humans. Rana El Kaliouby explores why emotion AI is critical to accelerating adoption of AI systems, how emotion AI is being used today, and what the future will look like.

Each year, 15 million people suffer strokes, and at least a fifth of those are due to atrial fibrillation, the most common heart arrhythmia. Brandon Ballinger reports on a collaboration between UCSF cardiologists and ex-Google data scientists that detects atrial fibrillation with deep learning.