This article was originally published on 10/12/2018.
For the second quarterly panel and pitches event, New York Life Ventures and the Center for Data Science and Analytics partnered in gathering experts to demystify artificial intelligence and discuss real applications of this ever-advancing technology. In addition to New York Life’s own Glenn Hofmann, VP of CDSA, the fireside chat also included Jason Black of RRE Ventures and Sarah Catanzaro of Amplify Partners, and was moderated by Sean Madgett, Director of Business Development in New York Life Ventures.
AI has come a long way and has been around longer than most would expect. The field was formally founded in 1956, when the term “artificial intelligence” was coined, after two Carnegie Tech professors developed an AI with the ability to solve geometry problems. Later, subsets of AI developed, termed "machine learning" and "deep learning." Machine learning is a subset of AI, using statistical techniques that enable machines to improve on tasks with experience. A step further, deep learning is a subset of machine learning, which utilizes algorithms that allow the software to train itself on tasks, like speech and image recognition, through multilayered networks and a large amount of data.
While artificial intelligence has come a long way in the last 60+ years, there are still roadblocks. In the words of Glen Hofmann, "Deep Learning will not advance until we are more confident in the reasoning under uncertainty and interoperability."
AI is already a part of our day to day lives, with Apple’s Siri and Amazon’s Alexa helping answer questions and perform increasingly complex, but sometimes mundane, tasks. Yet the ever-growing presence of AI seems to drum up a lot of fear, likely from uncertainty and lack of clarity on real applications. Many point to examples from dystopian, science fiction films. In these more extreme instances, AI presents as a threat to humanity. However, these frightening portrayals are far from realistic at this point. Sarah Catanzaro put it simply, “The AI hype, it's real. And that's not to say we won't have amazing advances... but this is still really, really hard. I worry more about a bad model than The Terminator.”
For others, AI represents a perceived threat to their job security; however, this isn’t quite accurate either. In fact, the further development of AI will create a demand for a new skillset, and in most instances, be used as a tool, rather than a replacement. In the words of Sarah Catanzaro, "very often you hear this narrative of AI taking over jobs... and I don't think you're going to see that in the near future." She and others believe there is much more opportunity for real, useful applications in the marriage of human and AI use cases.
In short, AI is highly complicated, with many vital, interweaving pieces, and experts are still looking to perfect the foundations of what is needed for successful AI. Jason Black clarified, "there's a whole lot of low-hanging fruit in just data ingestion... just the value of cleaning data cannot be underestimated.” In other words, before we see the largest explosion of benefits from AI, there are still advancements and innovations needed at the front end of the data usage spectrum.
As they do expertly on the day-to-day, the Business Development team within Ventures identified some standout AI-focused startups to present for the second half of the event, furthering the dive into real world applications. AI startups Prattle, Pymetrics and Determined AI each had representatives at the event to present and discuss their technologies, resulting in the discovery of a few possible applications within New York Life’s own businesses.
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