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) …
AI isn't science fiction or a future technology we're waiting to adopt. It is, right now, affecting every aspect of our daily lives, and that includes how we develop applications, products, and services. Every few years, there's a new buzzword technology that drives mass hype as it promises to disrupt the status quo: software, mobile, IoT, 3D printing, virtual reality, blockchain. In 2016, every company desperately wanted to latch on to artificial intelligence (AI). So while the earliest innovators (think Alan Turing) were studying how computers could mimic humans in the 1950s, we just recently witnessed a hype cycle triggered by the potential for AI to cause the next generational shift in computing.
There is a lot of AI action in Aotearoa this year. Yes, Artificial Intelligence is a red-hot topic. Many-a-talk at Tech Week last week featured the topic of AI somewhere in the mix. Layered on top of all this is a decent dollop of AI-related media hype. Fair enough; there are some intriguing stories based on comments by thought leaders such as Stephen Hawkings and Elon Musk.
I've been needling the artificial intelligence (AI) hype bubble since 2015 when, after managing a CalTech research grant, I saw a massive discrepancy between the attitudes of buzzword merchants and data scientists. Later, in 2017, I was the lone dissenting source in a FoxNews piece overhyping the use of AI to solve fake news. While I hate the hype, I love what's coming with AI. Get the latest from CSO by signing up for our newsletters. Early stage investor Rick Grinnell articulates a pragmatic assessment of the hype around AI and how it's really being used now.
Machine learning, machine intelligence, thinking machine, electronic brain – whatever you want to call it, artificial intelligence is here to stay. Although, machines haven't completely taken over, they have slowly but surely crept into our lives affecting the way we live, communicate and ultimately work. From voice-driven assistance on a mobile phone, suggestive searches to autonomous driverless cars, we will continue to see fast-evolving technologies in the coming years. At ACCA we have a deep interest in how technology impacts the accountancy profession and how it will continue to do so in the future. This year will see the 30th anniversary of the worldwide web – meaning we are firmly part of the digital revolution; technology is something accountants cannot shy away from or avoid.
More than ever, medicine now aims to tailor, adjust, and personalize healthcare to individuals' and populations' specific characteristics and needs--predictively, preventively, participatorily, and dynamically--while continuously improving and learning from data both "big" and "small." Today, these data are increasingly captured from data sources both old (such as electronic medical records, EMR) and new (including smartphones, sensors, and smart devices). Combining artificial intelligence (AI) with augmented human intelligence, these new analytical approaches enable "deep learning health systems" that reach far beyond the clinic to forge research, education, and even care into the built environment and peoples' homes. The volume of biomedical research is increasing rapidly. Some is being driven by the availability and analysis of big data--the focus of this collection.
By Ariel Procaccia Last March, McDonald's Corp. acquired the startup Dynamic Yield for $300 million, in the hope of employing machine learning to personalize customer experience. In the age of artificial intelligence, this was a no-brainer for McDonald's, since Dynamic Yield is widely recognized for its AI-powered technology and recently even landed a spot in a prestigious list of top AI startups. Neural McNetworks are upon us. Trouble is, Dynamic Yield's platform has nothing to do with AI, according to an article posted on Medium last month by the company's former head of content, Mike Mallazzo. It was a heartfelt takedown of phony AI, which was itself taken down by the author but remains engraved in the collective memory of the internet.
Dr Mark Woods is one of our panellists in the afternoon. Mark leads the Autonomy and Robotics group at SCISYS UK. We invited him to tell us more about himself ahead of the conference. Mark, thank you so much for accepting our invitation to be a panellist. And you've developed autonomous/AI/ML based systems for Mars Exploration including the European Space Agency's first robotic mission to Mars!
Moore's Law, advocated by Gordon Moore of Intel fame, says that the computational capabilities will double every 18 to 24 months. And we've seen that really unfolding over the last 30 years (see chart). It's really stoked people's imagination, so much so that many believe that the promise of artificial intelligence (AI) could become reality, and computers could actually learn to think like humans. I believe it's still a number of years away, but it is fueling a lot of hype regarding AI. What it's truly capable of, where it can be effective, and what it takes to implement it, all of which have become somewhat inflated in the market today.
Despite all the hype about artificial intelligence, most executives expect that it will take years before the cutting-edge technology gives their businesses a financial lift. Their long-term view was laid out by consulting firm KPMG in a recent survey of 400 executives, all of whom had artificial intelligence projects in progress within their companies. The executives generally said that it would take some time before artificial intelligence pays dividends, signaling a growing realization that the technology won't have the quick impact that many had initially hoped for. Just over half of the executives surveyed, 51%, said it will take three-to-five years before their A.I. projects create a "significant return on investment." That's in sharp contrast to last year's survey, in which only 28% said it would take that long--highlighting how much executives have reconsidered their initial rosy expectations.