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) …
Medical devices that monitor and respond to changes in our health. Robotic assistants that know what we want before we do. Kitchens that help us with our shopping and plan our meals. Every day, we hear about how artificial intelligence is going to change the world. Amid all this focus on the future, it's easy to ignore an unavoidable truth: AI is already changing the world in significant ways.
Nvidia deep learning consultant Michelle Gill never imagined herself working in California's robot-crazed tech industry. When she left Nebraska and got a PhD in biochemistry and biophysics at Yale University, she saw herself as more of a scientist who studied life than a technologist prepared to build new creations. It wasn't until she started working at the National Cancer Institute that she first became interested in machine learning. Analyzing medical images with data science opened the door to a whole new world. "A lot of the concepts I had learned in science applied in some way to machine learning," Gill told Newsweek at the Artificial Intelligence & Data Science conference in New York City.
Publications like The Wall Street Journal, Forbes and Fortune have all called 2017 "The Year of AI." AI outperformed professional gamers and poker players in new realms. Access to deep learning education expanded through various online programs. The speech recognition accuracy record was broken multiple times, most recently by Microsoft. And research universities and organizations like Oxford, Massachusetts General Hospital and GE's Avitas Systems invested in deep learning supercomputers. These are a few of many milestones in 2017.
Artificial intelligence (AI) is a "tsunami" that's coming to healthcare. That's what Naveen Jain, CEO of Viome, a small company focused on applying AI to healthcare, told CNBC on Thursday. The waves have already started picking up force. Three major milestones were reached related to the use of AI in healthcare in the last four weeks. There's a good chance you haven't heard about any of them.
The demand for data science talent in the capital markets space has seen portfolio managers and discretionary traders attending night classes in a bid to safeguard their jobs amid a rising tide of automation. The whole asset management industry is moving in the direction of being more systematic, being more quantitative and using new unique data. A lot of firms are struggling in many ways to get their heads around that. While there may be many vanilla data science training courses out there, finding a solid introduction for quantitative finance training with the nuanced level of applicability is not so easy. Leigh Drogen, the founder of crowdsourced financial analysis platform Estimize, designed and created the L2Q (Learn to Quant) programme as a rudimentary introduction for discretionary managers.
It is finally resonating with me that incorporating Deep Learning at the Edge has the potential to create a paradigm shift in the way robots are deployed in manufacturing operations. FANUC's aggressive move to integrated Deep Learning technologies could revolutionize the way robotic systems are deployed. When you consider how robots are deployed in manufacturing operations today, the application programs employ traditional procedural and function programming methods. But as robots increasingly rely upon vision systems to identify and locate geometric patterns on a work piece, the logic and decision making no longer has to be all pre-programmed in order to process the workpiece. Today, every robotic application program applies the experiential knowledge of a human expert to account for every possible situation that may arise in the manufacturing operation.
Graphcore won't release images of its AI-focused chip, called an IPU, until its first shipments to customers in early 2018. Instead, it's offered images of the'computational graph' that runs on the chip, like the one above. I've just clicked on a tutorial video on YouTube about puppy-training, but there's nary an ad about dogs or even pet care. Instead, YouTube cues up a video ad for dishwashing tablets, before popping up a banner ad for a mobile game I'll probably never play. Google has struggled to make its video ads on YouTube relevant to what people are watching.
There's a frequently cited PwC report that says that 38% of U.S. jobs are at risk of being overtaken by artificially intelligent automation by 2030. Similarly, a Scientific American article warned earlier this year that 40% of the top 500 companies will vanish within a decade as they fall victim to artificial intelligence (AI). Let's be honest here, those predictions are pretty easy to dismiss right now. The average person can take a look around and ask, "Where is all of this scary AI?" But AI is already starting to take over in very subtle ways, and there's plenty of evidence that as AI becomes a bigger part of what these companies do it'll eventually become a bigger part of how our world functions.
Good morning, or afternoon, wherever you are. Here's a roundup of recent AI developments on top of everything else we've reported over the past week or so. Researchers at Nvidia have developed and described a new way to train generative adversarial networks (GANs) in a more stable manner to generate a series of, what appears at first glance, seemingly realistic convincing photos. In other words, this is a neural network that can produce, at a decent resolution, fairly plausible photos of things – from couches to buildings – on demand from scratch. The computer can invent or fabricate scenes for you or anyone else, from a description: pretty much on-demand fake news.
New England-based horror writer Stephen King has been scaring us all for decades. Now -- just in time for Halloween -- a team at the Massachusetts Institute of Technology is at the center of what might be the only tale that could scare the modern world's most frightening writer. They've created an artificial intelligence that can turn one of the internet's most infamous online communities into an AI that turns snippets of text into spine-tingling stories. "We're interested in how AI induces emotions, fear in this particular case," said Manuel Cebrian, a research scientist in the MIT Media Lab. "So Halloween is always a great time to roll out a mass-scale AI agent that tests our emotion-inducing capability."