Employing machine learning and computer vision for detection and classification of various “safety events,” the shoebox-sized device doesn’t see all, but it sees plenty. Like which way the driver is looking as he operates the vehicle, how fast he’s driving, where he’s driving, locations of the people around him and how other forklift operators are maneuvering their vehicles. IFM’s software automatically detects safety violations (for example, cell phone use) and notifies warehouse managers so they can take immediate action. The main goals are to prevent accidents and increase efficiency. The mere knowledge that one of IFM’s devices is watching, Gyongyosi claims, has had “a huge effect.”“If you think about a camera, it really is the richest sensor available to us today at a very interesting price point,” he says. “Because of smartphones, camera and image sensors have become incredibly inexpensive, yet we capture a lot of information. From an image, we might be able to infer 25 signals today, but six months from now we’ll be able to infer 100 or 150 signals from that same image. The only difference is the software that’s looking at the image. And that’s why this is so compelling, because we can offer a very important core feature set today, but then over time all our systems are learning from each other. Every customer is able to benefit from every other customer that we bring on board because our systems start to see and learn more processes and detect more things that are important and relevant.”
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The Evolution of AIIFM is just one of countless AI innovators in a field that’s hotter than ever and getting more so all the time. Here’s a good indicator: Of the 9,100 patents received by IBM inventors in 2018, 1,600 (or nearly 18 percent) were AI-related. Here’s another: Tesla founder and tech titan Elon Musk recently donated $10 million to fund ongoing research at the non-profit research company OpenAI — a mere drop in the proverbial bucket if his $1 billion co-pledge in 2015 is any indication. And in 2017, Russian president Vladimir Putin told school children that “Whoever becomes the leader in this sphere [AI] will become the ruler of the world.” He then tossed his head back and laughed maniacally.
OK, that last thing is false. This, however, is not: After more than seven decades marked by hoopla and sporadic dormancy during a multi-wave evolutionary period that began with so-called “knowledge engineering,” progressed to model- and algorithm-based machine learning and is increasingly focused on perception, reasoning and generalization, AI has re-taken center stage as never before. And it won’t cede the spotlight anytime soon.THE FUTURE IS NOW: AI'S IMPACT IS EVERYWHEREThere’s virtually no major industry modern AI — more specifically, “narrow AI,” which performs objective functions using data-trained models and often falls into the categories of deep learning or machine learning — hasn’t already affected. That’s especially true in the past few years, as data collection and analysis has ramped up considerably thanks to robust IoT connectivity, the proliferation of connected devices and ever-speedier computer processing.
Some sectors are at the start of their AI journey, others are veteran travelers. Both have a long way to go. Regardless, the impact artificial intelligence is having on our present day lives is hard to ignore:But those advances (and numerous others, including this crop of new ones) are only the beginning; there’s much more to come — more than anyone, even the most prescient prognosticators, can fathom.
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“I think anybody making assumptions about the capabilities of intelligent software capping out at some point are mistaken,” says David Vandegrift, CTO and co-founder of the customer relationship management firm 4Degrees.With companies spending nearly $20 billion collective dollars on AI products and services annually, tech giants like Google, Apple, Microsoft and Amazon spending billions to create those products and services, universities making AI a more prominent part of their respective curricula (MIT alone is dropping $1 billion on a new college devoted solely to computing, with an AI focus), and the U.S. Department of Defense upping its AI game, big things are bound to happen. Some of those developments are well on their way to being fully realized; some are merely theoretical and might remain so. All are disruptive, for better and potentially worse, and there’s no downturn in sight.
“Lots of industries go through this pattern of winter, winter, and then an eternal spring,” former Google Brain leader and Baidu chief scientist Andrew Ng told ZDNet late last year. “We may be in the eternal spring of AI.”some of the most intriguing AI research and experimentation that will have near-future ramifications is happening in two areas: “reinforcement” learning, which deals in rewards and punishment rather than labeled data; and generative adversarial networks (GAN for short) that allow computer algorithms to create rather than merely assess by pitting two nets against each other. The former is exemplified by the Go-playing prowess of Google DeepMind’s Alpha Go Zero, the latter by original image or audio generation that’s based on learning about a certain subject like celebrities or a particular type of music.
On a far grander scale, AI is poised to have a major effect on sustainability, climate change and environmental issues. Ideally and partly through the use of sophisticated sensors, cities will become less congested, less polluted and generally more livable. Inroads are already being made.
“Once you predict something, you can prescribe certain policies and rules,” Nahrstedt says. Such as sensors on cars that send data about traffic conditions could predict potential problems and optimize the flow of cars. “This is not yet perfected by any means,” she says. “It’s just in its infancy. But years down the road, it will play a really big role.”AI AND THE FUTURE OF PRIVACY & HUMAN RIGHTSOf course, much has been made of the fact that AI’s reliance on big data is already impacting privacy in a major way. Look no further than Cambridge Analytica’s Facebook shenanigans or Amazon’s Alexa eavesdropping, two among many examples of tech gone wild. Without proper regulations and self-imposed limitations, critics argue, the situation will get even worse. In 2015, Apple CEO Tim Cook derided competitors Google and Facebook (surprise!) for greed-driven data mining.
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“They’re gobbling up everything they can learn about you and trying to monetize it,” he said in a 2015 speech. “We think that’s wrong.”
Last fall, during a talk in Brussels, Belgium, Cook expounded on his concern.
“Advancing AI by collecting huge personal profiles is laziness, not efficiency," he said. “For artificial intelligence to be truly smart, it must respect human values, including privacy. If we get this wrong, the dangers are profound."
