Latest AI Articles:

1 - Carnegie Mellon Receives $10 Million From K&L Gates To Study Ethical Issues Posed By Artificial Intelligence

Episode Summary: CEO Chris Nicholson speaks on Skymind machine learning applications, which integrate with Hadoop and Spark. In this episode, Nicholson sheds light on current machine learning trends that he sees across industries and best practices for implementing AI solutions in order to gain consistent return on investment. For our readers who enjoyed out consensus on future trends in artificial intelligence consumer applications, it may be interesting to hear some of Chris's specific use cases in industry.

Busy and multitasking are understatements for today's executives and entrepreneurs. Machine learning has the potential to help make businesses more efficient, competitive, and profitable, but learning how it works and finding the resources to implement this technology takes time. Where to apply machine learning when first getting started is dependent on a number of factors - industry, structure, current problems - but having an idea of which solutions have proved most efficient for others and derived maximum return on investment is a helpful jumping off point.

Episode Summary: We've interviewed a number of guests on Emerj, but very few who have had a serious part of their career in selling automobiles. But Michael Perry did just that for 5 years before founding Kit, his third startup - an AI-powered Virtual Employee that works in marketing for small businesses and was acquired by Shopify in April 2016. In this episode, Perry speaks about how Kit and Shopify leverage AI on a daily basis, and how a “non-tech” person with no formal background in AI or data science can build a team for an AI project.

1 - Machine Learning Veterans Launch 'ElementAI' - A Montreal Based Artificial Intelligence Startup Factory

Episode Summary: Martin Ford started off as a software entrepreneur in Silicon Valley, but became better known for his speaking and writing on robotics' and automation's influence on the job market after writing his best-selling book, Rise of the Robots: Technology and the Threat of a Jobless Future. In this episode, Martin talks about why he believes 'white collar' jobs (as opposed to blue) are at a higher risk for automation, and gives his predictions on how automation and robotics will impact the job market over the next 5 to 10 years.

Episode Summary: As Senior Director and World Wide Head of the Cognitive Innovation Group at Nuance Communications, Mark Hanson works on bringing Nuance lab innovations to business applications, with the guiding goals of  improving customer experience and business efficiency. In this episode, Hanson speaks about natural language processing (NLP) and virtual assistant services, where he believes this technology is headed in the future and where it's driving value now, and how companies are applying NLP in Silicon Valley and elsewhere.

Expertise: Data science and economics

Brief Recognition: Elena Grewal leads a team of data scientists responsible for the user’s online and offline travel experience at Airbnb. Her team partners with the product team to understand and optimize all parts of the product, using experimentation and machine learning in a wide variety of contexts. Prior to Airbnb, Elena was a doctoral candidate in the Economics of Education program at the Stanford University School of Education. She received a B.A. in Ethics, Politics, and Economics, with distinction, from Yale University, and a Masters degree in Economics at Stanford University. She was also the recipient of the Stanford Interdisciplinary Graduate Fellowship.

Predictive analytics for marketing would have been adopted years ago - if only the compute power were more ubiquitous, the data were more accessible, and the software were easier to use. Now "predictive analytics" itself is almost a buzzword, after nearly 30 years of backward-looking marketing tracking.
Today, well over 30 years after the founding of Lotus Software, even medium-sized businesses are often still operating their marketing "scoreboards" in Google Sheets or One Drive... "throw it in a spreadsheet" still works.
But businesses with an eye on the future want to know more than just what happened in the past. "Scoreboards" (most analytics tools and tracking) don't tell you what the score will be. Some of our recent "AI for marketing" articles have gained readership because more and more executives are searching for ways to look forward with their numbers, not just back. SAS defines the term well:

Episode Summary: How do you know if you’ve made the right decision for a hire? Often, employers go off gut instinct and make a decision retrospectively, but it turns out AI might be able to help out in human resource management through shedding light on best hiring decisions. In this episode, Pasha Roberts, chief scientist at Talent Analytics, tells us about how his company is working on helping companies make better decisions before they hire by applying machine learning and artificial intelligence to various data points on a given applicant, including information from aptitude tests that may help predict not only performance but retention.