Neon, the artificial human prototype conceptualized by computer scientist and inventor Pranav Mistry, created waves recently. The President and CEO of Samsung's STAR Labs told ET in an exclusive interview that he created Neon because human beings are unable to connect with artificial intelligence (AI) assistants such as Apple's Siri. The Palanpur (Gujarat)-born Mistry, considered one of the best innovative minds in the world right now, said Neon will be a companion to the elderly and to those who are lonely and could even work as fashion models or news anchors. The 38-year-old also spoke about the dangers posed by AI,echoing Google parent Alphabet Inc's chief Sundar Pichai who recently called upon governments to regulate AI. Edited Excerpts: When you started thinking about Neon, what was the problem you were trying to solve?
In 2017, the predictive ability of artificial intelligence (AI) powered many new tools and platforms. So what does 2018 have in store for AI? I asked some marketers to find out. Gregg Johnson, CEO of Invoca, a call tracking and analytics service, says that 2018 will be "the year the voice trend becomes undeniable." "As people increasingly trade typing for talking, we'll see more companies invest in developing for voice interfaces," Johnson said.
In this Q&A on Explainable AI, Andrea Brennen speaks with In-Q-Tel's Peter Bronez about descriptive vs. prescriptive models, "white box" vs. "black box" explanation techniques, and why some models are easier to explain than others. Peter also discusses the reproducibility crisis in Psychology and why good experiment design is so important. Peter is a VP on the technical staff at IQT. Could you tell me about your experience with machine learning and AI? PETER: As an undergraduate, I studied econometrics and operations research, so my exposure to machine learning was in the context of designing models of the world that you could test mathematically -- basically, doing hypothesis testing using statistics. Afterwards, I worked at the Department of Defense and used a lot of the same techniques. From there, I went to the private sector and [worked on] social media and data mining in marketing applications, trying to create mathematical models to categorize people, activities, and messages in order to understand them better.
It's a somewhat ironic tail: in the midst of digital transformation, artificial intelligence (AI) is in position to take over many functions of people services--the business of human resources. After all, many companies have been automating their job application processes for quite a while. But as the sophistication of AI continues to ramp up, AI will be playing an even more significant role in recruitment and talent acquisition. This is the future of AI and HR. If you're anything like most people, you have your doubts at how well a machine could select a human for a certain position.
Every year the Loebner Prize for artificial intelligence is awarded to the chatbot software able to converse most like a human. It is a version of the Turing test, proposed in 1950 by Alan Turing. A program passes when a human judge cannot tell that they are talking to a machine. No machine has yet passed. But the winner of the Loebner Prize at the weekend – Elbot, brainchild of Fred Roberts at Artificial Solutions in Germany – came close, according to the contest's rather generous rules.