Cognitive technologies such as Artificial Intelligence (AI) offers businesses an incredible opportunity to rethink traditional processes. By automating rote tasks and accelerating standard workflows, companies can free employees to pursue innovation in other capacities. But are AI and intelligent automation different than other enterprise technologies? Does AI's potential pose far more dramatic threats than previous technological innovations? Why are technologists and business leaders so excited and simultaneously apprehensive about a technology that, despite its creation in the 1950s, is still in its relative infancy?In this video, we speak with Fred Laluyaux, CEO and President of Aera Technology and David Bray, Executive Director of the People-Centered Internet, about these critical topics. During our conversation, we define some of the industry buzzwords and scientific terms that may still mystify the business world. We discuss the ways in which humans and machines should work in collaboration, both now and in a future that may give rise to machines that become responsible for many of the tasks humans handle today. We also examine how AI will revitalize current business technology including supply chain solutions, e-commerce platforms, and the still-nascent Internet of Things. To learn more about how, when, and why your business should jump into the world of AI and automation, be sure to watch this video. In it, you'll also find valuable advice from David and Fred on how to handle the ethical implications of AI adoption, and how you should treat your employees as AI becomes ubiquitous. The transcript below has been lightly edited for clarity and length. I'm delighted to speak with two gentlemen who will explain these concepts and what they mean for business. Fred, tell us briefly about Aera Technology. Fred Laluyaux: We build the technology that enables self-driving enterprise. I'll speak more about what it is, but it's fundamentally a cognitive operating system.
Why are so many AI researchers so worried about lethal autonomous weapons? What makes autonomous weapons so much worse than any other weapons we have today? And why is it so hard for countries to come to a consensus about autonomous weapons? Not surprisingly, the short answer is: it's complicated. In this month's podcast, Ariel spoke with experts from a variety of perspectives on the current status of LAWS, where we are headed, and the feasibility of banning these weapons. Guests include ex-Pentagon advisor Paul Scharre (3:40), artificial intelligence professor Toby Walsh (40:51), Article 36 founder Richard Moyes (53:30), Campaign to Stop Killer Robots founders Mary Wareham and Bonnie Docherty (1:03:38), and ethicist and co-founder of the International Committee for Robot Arms Control, Peter Asaro (1:32:39). You can listen to the podcast above, and read the full transcript below. You can check out previous podcasts on SoundCloud, iTunes, GooglePlay, and Stitcher. If you work with ...
Artificial intelligence might sound like a futuristic concept, and it may be true that we're years or decades away from a generalized form of AI that can match or exceed the capabilities of the human brain across a wide range of topics. But the implications of machine learning, facial recognition and other early forms of the technology are already playing out for companies, governmental agencies and people around the world. This is raising questions about everything from privacy to jobs to law enforcement to the future of humanity. On this episode of the GeekWire Podcast, we hear several different takes from people grappling right now with AI and its implications for business, technology and society, recorded across different sessions at the recent GeekWire Summit in Seattle. Listen to the episode above, or subscribe in your favorite podcast app, and continue reading for edited excerpts. Smith: I think it's fair to say that artificial intelligence will reshape the global economy over the next three decades probably more than any other single technological force, probably as much as the combustion engine reshaped the global economy in the first half of the 20th century. One of our chapters is about AI in the workforce, and we actually start it by talking about the role of horses, the last run of the fire of horses in Brooklyn in 1922. And we trace how the transition from the horse to the automobile changed every aspect of the economy. I think the same thing will be true of AI, so we should get that right.
Both the progress and the hype around cutting-edge machine learning techniques were on vivid display at the December 2018 NeurIPS Conference in Montreal, Quebec, says Will Knight, MIT Technology Review's senior editor for artificial intelligence. One big question hanging over the meeting, he says, was how to detect and reverse the sexism, racism, and other forms of bias that seep into machine-learning algorithms that train themselves using real-world data. Participants also previewed the coming generation of chips designed specifically to support deep learning--a field where US manufacturers face growing competition from China. Separately, Will looks to the most exciting AI trends for 2019, including the generative adversarial networks (GANs) being used to generate authentic-looking photos and videos. This episode is sponsored by PwC, a global consulting firm in 158 countries with more than 250,000 people. PwC transforms business outcomes and results, helping companies use digital and emerging tech to reimagine their business, from strategy and operations to tax and finance. In the second half of the show, Scott Likens, PwC's New Services and Emerging Tech Leader, shares details from a new PwC study on the main trends in artificial intelligence that business leaders need to know about in 2019. Business Lab is hosted by Elizabeth Bramson-Boudreau, the CEO and publisher of MIT Technology Review. The show is produced by Wade Roush, with editorial help from Mindy Blodgett. Will Knight: "China has never had a real chip industry. Making AI chips could change that." PwC 2019 AI Predictions: Six AI priorities you can't afford to ignore Elizabeth Bramson-Boudreau: From MIT Technology Review, I'm Elizabeth Bramson-Boudreau, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.
Most of us followed the exciting introduction of the new iPhone X, and there you also saw in the press conference, it's all about machine learning now for face recognition, applied also, machine learning in face recognition to unlock your phone. So, I think we all experience it already with our smartphones, and going forward, we'll see much more of it. Michael Chui: What we're starting to see is these AI technologies underpinning a lot of the things, all the online and mobile services that we're now increasingly taking advantage of. So, for instance, in e-commerce or media, when systems are providing you with suggestions for things you might be interested in, things you might be interested in reading or things you might be interested in buying--the next-product-to-buy use case, as we describe it--increasingly, those types of systems are powered not only by statistical methods, but by some of these AI technologies as well, hopefully bringing consumers closer to the things that they'd be most interested in. Simon London: I'm going to throw one more into the pot there. I'm lucky enough to live in the city of Mountain View in Silicon Valley. There are a surprising number of self-driving cars out on the road.