If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The presentation will introduce contemporary brain-computer interface (BCI) techniques. Dr Rutkowski will explain auditory, visual, and tactile reactive BCI examples with applications for communication and passive solutions for cognitive-load/dementia biomarker elucidation. He will also discuss future research directions of the so-called neurotechnology applications for healthcare and especially cognitive monitoring solutions. Tomasz Rutkowski received his M.Sc. in Electronics and Ph.D. in Telecommunications and Acoustics from Wroclaw University of Technology, Poland, in 1994 and 2002, respectively. He received postdoctoral training at the Multimedia Laboratory, Kyoto University, and in 2005-2011 he worked as a research scientist at RIKEN Brain Science Institute, Japan.
Every weekday, this feed brings you our latest talks in audio format. Hear thought-provoking ideas on every subject imaginable -- from Artificial Intelligence to Zoology, and everything in between -- given by the world's leading thinkers and doers. This collection of talks, given at TED and TEDx conferences around the globe, is also available in video format.
From visual search to computer vision, natural language processing to predictive modelling, machine learning underpins all kinds of innovations that are levelling the playing field by giving retailers of all sizes access to the same tools as behemoths like Amazon – and allowing them to develop cutting-edge online and in-store experiences. This in-depth briefing will look closely at a number of different applications for machine learning in retail, accompanied by examples of how retail brands are putting them into practice and how they translate to improvements in sales, processes, customer engagement, and the customer journey. It will examine both ecommerce and bricks-and-mortar retail, noting the differences in how machine learning is used in digital versus offline environments, before finally considering how this usage might evolve in the future.
This article is coauthored by Joy Rimchala and Shir Meir Lador. Rapid adoption of complex machine learning (ML) models in recent years has brought with it a new challenge for today's companies: how to interpret, understand, and explain the reasoning behind these complex models' predictions. Treating complex ML systems as trustworthy black boxes without sanity checking has led to some disastrous outcomes, as evidenced by recent disclosures of gender and racial biases in GenderShades¹. As ML-assisted predictions integrate more deeply into high-stakes decision-making, such as medical diagnoses, recidivism risk prediction, loan approval processes, etc., knowing the root causes of an ML prediction becomes crucial. If we know that certain model predictions reflect bias and are not aligned with our best knowledge and societal values (such as an equal opportunity policy or outcome equity), we can detect these undesirable ML defects, prevent the deployment of such ML systems, and correct model defects.
Works with experienced team members to conduct root cause analysis of issues, review new and existing code and/or perform unit testing. Learns to create system documentation/play books and attends requirements, design and code reviews. Identifies ideas to improve system performance and impact availability. Creates system documentation/play book(s) and participates as a reviewer and contributor in requirements, design and code reviews. May serve as the subject matter expert on development techniques.
IoT is giving people the latest experience of "the future is here." How far away are we from a practical, daily IoT experience that touches the majority of Americans? What form will that take (how will we know it's here?) What are the practical, daily experiences people will encounter first, and how will their lives be improved? How will a technological mesh of AI, platforms, voice-driven software and hardware free people up to be better related and connected?
The increased adoption of artificial intelligence (AI) at work is changing the relationship between employees and managers. More than half (64%) of employees said they trust a robot more than their manager, with half turning to a robot instead of a supervisor for advice, an Oracle and Future Workplace report found.
Nowadays, consumers have a variety of options for obtaining services and getting the help they need. They can use webchat, email, the Internet, and face-to-face contact, yet telephone customer service is still the first choice for most customers when they have questions or a problem that needs to be resolved. In order to ensure your customers are happy with the customer service they receive, it's even more important for you to provide exceptional customer service, including outstanding telephone service. Consumers expect better service than ever before, and the capabilities of modern telephone communications allow you to offer them the satisfaction and resolution they demand. IVR (Interactive Voice Response) can be a great tool for your company in decreasing customer wait time and increasing customer satisfaction, but customers are sometimes not overly fond of automatic response systems -- especially when they have bad experiences.
As befits the topic, we start our list with a comprehensive introduction into AI technology: "Introduction to Artificial Intelligence." Written by Phillip C. Jackson, Jr., the book is one of the classics that's still read by experts in the field and non-specialists alike. This book provides a summary of the previous two decades of research into the science of computer reasoning, and where it could be heading. Published in 1985, some of the information might be outdated, but if nothing else, the book could serve as a valuable historical document.
Analyst Forrester defines robotic process automation (RPA) as a technology that provisions software agents – bots – that can mimic human interactions with software systems. These bots run predictable tasks, and act either in concert with humans (attended RPA) or mostly autonomously (unattended RPA). Increasingly, RPA is adding artificial intelligence (AI)-based capabilities, such as reading unstructured data. IT research firm Computer Economics says in its April 2019 Technology trends report that bots are typically taught by human example to respond to various triggers. For example, when an employee submits a change of address form to the human resources (HR) department, the bot could then be used to trigger an update to the records in payroll, benefits systems, expense reporting and accounts payable, just as a human clerical worker might do.