Dr. Andrew Ng is a globally recognized leader in artificial intelligence. He was until recently chief scientist at Baidu, where he led the company's approximately 1,300-person AI group and was responsible for driving its global AI strategy and infrastructure. He was also the founding lead of the Google Brain team. In addition, Dr. Ng is co-chairman and cofounder of Coursera, the world's leading MOOC (massive open online course) platform, and an adjunct professor of computer science at Stanford University. He has authored or coauthored over 100 research papers in machine learning, robotics, and related fields.
Artificial intelligence is an oxymoron (Technology quarterly, June 13th). Intelligence is an attribute of living things, and can best be defined as the use of information to further survival and reproduction. When a computer resists being switched off, or a robot worries about the future for its children, then, and only then, may intelligence flow. I acknowledge Richard Sutton's "bitter lesson", that attempts to build human understanding into computers rarely work, although there is nothing new here. I was aware of the folly of anthropomorphism as an AI researcher in the mid-1980s.
The abundance of knowledge and resources can be at times overwhelming specifically when you are talking about new age technologies like Natural Language Processing or what we popularly call it as NLP. When trying to educate yourself, you should always choose resources with solid base and fresh books to impart unprecedented package of learnings. Here is the list of top books that can help you expand your NLP knowledge. One of the most widely referenced and recommended NLP books, written by Stanford University professor Dan Jurafsky and University of Colorado professor James Martin, provides a deep-dive guide on the subject of language processing. It's intended to accompany undergraduate or advanced graduate courses in Natural Language Processing or Computational Linguistics. However, it's a must-read for anyone diving into the theory and application of language processing as they grow and strengthen their analytics capabilities.
In this episode of the McKinsey on AI podcast miniseries, McKinsey's David DeLallo speaks with McKinsey Global Institute partner Michael Chui and associate partner Bryce Hall about the latest trends in business adoption of artificial intelligence (AI). They discuss where the technology is being used most across industries, companies, and business functions; the keys to getting impact from AI investments; and what lies ahead. There's no shortage of predictions about how it could fundamentally change the way we live and work. Over the past few years, companies around the world have been figuring out exactly how AI technologies can improve their performance in a number of areas across their business. But is AI actually delivering significant results? Moreover, what can we expect to see as we move into a new decade of AI use and development? To answer some of these questions today, I'm joined by Michael Chui, a McKinsey partner with the McKinsey Global Institute, who is based in our San Francisco office, and associate partner Bryce Hall from our Washington, DC, office.
"I'm trying to go down a bottomless pit. I'll never make it till the end." That's what I thought when I tried to create my own video game. I was young, beautiful, and I was struggling to use for loops and arrays at the same time. There was so much to learn! Fortunately, I found the strength to continue. More and more, the concepts behind programming began to make sense. Going through a book about C and trying to create my own adventure on MS-DOS was a crazy Indiana Jone's-like discovery I'll never forget. My first video game wasn't great, but it was mine. Yet, what I remember today, with a tear in my left eye, is not the result, but the learning process itself. It was these "Aha!" moments which brought me the most joy! That's why I tried, through the years, to make my learning gradually more effective and efficient.
Researchers from North Carolina State University have discovered that teaching physics to neural networks enables those networks to better adapt to chaos within their environment. The work has implications for improved artificial intelligence (AI) applications ranging from medical diagnostics to automated drone piloting. Neural networks are an advanced type of AI loosely based on the way that our brains work. Our natural neurons exchange electrical impulses according to the strengths of their connections. Artificial neural networks mimic this behavior by adjusting numerical weights and biases during training sessions to minimize the difference between their actual and desired outputs.
Scientists have created a glove that translates sign language into speech in a matter of seconds through a smartphone app. The hi-tech glove sends electronic signals generated from different movements of the fingers to a circuit board, which are then transmitted wirelessly to the phone. The app translates letters from movements on one hand, as per the American Sign Language (ASL) standard, into phrases, which are uttered by an automated voice. The patented technology aims to reduce the language barrier between people with hearing or speech impediments and those who don't understand sign language. Components used to make the device are cheap, flexible and highly durable, according to the team of engineers in the US, who plan to commercialise the technology if they can speed up the translation time even further.
Walter Bender, the Chief Learning Architect at Sorcero and the founder of Sugar Labs and One Laptop One Child, shared with IBL News how transparent AI will revolutionize online learning following his talk at the Open edX conference last month in San Diego. The main goal, he posits, is "to leverage what makes us human to become part of the learning process." His talk, "Beyond the Black Box: How Transparent AI can Transform Learning," focused on the strides that Sorcero is making with AI and online learning. With his extensive experience in academia and accessible and open online education, he says his experiences were "a case study for transparency, for providing tools and a framework." The natural extension from this was to switch gears and talk about AI, the "tool du jour in machine learning these days."
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