You can download and modify the code from this tutorial on GitHub here. According to Yann LeCun, "adversarial training is the coolest thing since sliced bread." Sliced bread certainly never created this much excitement within the deep learning community. Generative adversarial networks--or GANs, for short--have dramatically sharpened the possibility of AI-generated content, and have drawn active research efforts since they were first described by Ian Goodfellow et al. in 2014. GANs are neural networks that learn to create synthetic data similar to some known input data.

The dichotomy between machines and living things is narrowing. Today, artificial intelligence (AI) is embedded in all kinds of technology, from robots to social networks. This affects the youngest among us as we see the emergence of an "Internet of Toys." The trend is what prompted us to explore the impact of those "smart," interconnected playthings on children. We'll present our paper, "Hey Google, is it OK if I eat you?: Initial Explorations in Child-Agent Interaction," at the Interaction Design and Children conference at Stanford University on June 27.

This notebook was written by Dr. Randal S. Olson from GitHub. In this notebook, Randal is going to go over a basic Python data analysis pipeline from start to finish to show you what a typical data science workflow looks like. In addition to providing code examples, he also hopes to imbue in you a sense of good practices so you can be a more effective -- and more collaborative -- data scientist. Randal will be following along with the data analysis checklist from The Elements of Data Analytic Style, which he strongly recommends reading as a free and quick guidebook to performing outstanding data analysis. In the time it took you to read this sentence, terabytes of data have been collectively generated across the world -- more data than any of us could ever hope to process, much less make sense of, on the machines we're using to read this notebook.In response to this massive influx of data, the field of Data Science has come to the forefront in the past decade. Cobbled together by people from a diverse array of fields -- statistics, physics, computer science, design, and many more -- the field of Data Science represents our collective desire to understand and harness the abundance of data around us to build a better world.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

SYS-CON Events announced today that IBM has been named "Diamond Sponsor" of SYS-CON's 21st Cloud Expo, which will take place on October 31 through November 2nd 2017 at the Santa Clara Convention Center in Santa Clara, California. In an era of historic innovation fueled by unprecedented access to data and technology, the low cost and risk of entering new markets has leveled the playing field for business. Today, any ambitious innovator can easily introduce a new application or product that can reinvent business models and transform the client experience. In their Day 2 Keynote at 19th Cloud Expo, Mercer Rowe, IBM Vice President of Strategic Alliances, and Raejeanne Skillern, Intel Vice President of Data Center Group and GM, discussed how clients in this new era of innovation can apply data, technology, plus human ingenuity to springboard to advance new business value and opportunities. Speaker Bios Mercer Rowe is Vice President, Strategic Partners for IBM's Cloud Business Unit.

Key Topics Covered: 1 Introduction 1.1 Background 1.2 Scope of the Research 1.3 Target Audience 1.4 Company Coverage 2 Executive Summary 2.1 Global Connected Manufacturing Market 2.2 Top Line Growth 2.3 Success Factors 2.3.1 Partnerships for Value Added Services 2.3.2

Brain scans, analyzed using a type of artificial intelligence, can reveal whether 6-month-old babies are likely to develop autism, a new study shows. The study examined 59 infants who were at high risk of developing autism; that is, each had an older sibling with autism. The artificial intelligence predicted with 100 percent accuracy that 48 infants would not develop autism. In addition, of the 11 infants who did develop the disorder by the time they were 2 years old, the system correctly predicted nine of the cases. "It was extremely accurate," Robert Emerson, the lead author on the study and a former cognitive neuroscience postdoctoral fellow at the University of North Carolina (UNC), told Live Science.

At the first "AI for Good Global Summit" in Geneva, the Chairman of the Board of Management of AUDI AG said in front of UN experts: "We need a discourse in society that looks at the enormous potential of piloted and autonomous driving in relation to the ethical and legal questions." Artificial intelligence (AI) is regarded by experts from science and industry as a key technology for piloted and autonomous driving. It assists the car in perceiving and interpreting its environment, and deriving decisions from this. But who is liable in the case of accidents, and how should the car driving autonomously behave in a situation of unavoidable danger? Prof. Stadler: "We take the concerns of the public seriously and are facing up to the challenges associated with this."

Artificial intelligence start-up Wyzerr announced today the launch of an online platform to create feedback surveys that feel like games. The surveys, which the company calls "Smart Forms," can capture up to 25 questions in under 60 seconds. Wyzerr's Smart Forms were developed based on playful design principals and rules of engagement. Wyzerr spent the past 2 years piloting their gammified surveys with large enterprises like Walmart, Unilever, and Volkswagen. The key learnings from those pilots served as the inspiration for the company's new online Smart Form builder, which guides customers in creating effective feedback campaigns.

Did you have a good, relaxing break over the summer? Are you refreshed and re-energised, looking forward to a new start, a new you and brushing up on your data analysis skills? If so, I've thrown together a collection of a few excellent (and free!) statistics eBooks for your Kindle to sharpen up your stats while you're on the long commute to work. Just try not to read them while driving! These books require different levels of existing knowledge, and while some are for early-stage data scientists others are for more hard-core physicists and mathematicians.