Can AI Startups Compete with Tech Giants?
If you happen to be a world-famous futurist, inventor, and entrepreneur, what would compel you to take a corporate job? That was one of the questions that I discussed with Ray Kurzweil recently at Synergy Global Forum in New York. Kurzweil was among a large group of luminaries who shared their ideas on innovation and the future with an audience of 5,000 at the conference’s North American debut at Madison Square Garden. I had the pleasure of moderating a Q&A session with the audience following Kurzweil’s presentation. We’ve talked about a great many things, from his views on strong AI to extreme life extension, but this particular point on his résumé—accepting a position at Google in 2012—piqued my curiosity.
It seemed that Kurzweil wasn’t keen on the offer at first, having come to the Google founders with a proposal for funding one of his latest inventions. But after they explained all of the resources and assets they had around data sets and computing capabilities, Kurzweil found the argument compelling enough to take the first job he’s ever had at a company that he didn’t start. So, why does it matter that Kurzweil—a recipient of the National Medal of Technology and Innovation (the highest honor in technology given in the U.S.) and the Lemelson-MIT Prize (the largest cash prize for invention in the U.S.)—took a job at Google? Kurzweil’s decision offers a glimpse into the sources of innovation in a field that is changing many aspects of our lives already and is poised to bring even more significant changes in the near future.
Go big or go home?
If we take a look at how innovation happens in other hot industries today, we see vibrant ecosystems of players large and small inventing and testing things out in the marketplace and collaborating in all sorts of interesting ways. Startups thrive independently and in symbiosis with large companies, sometimes literally next door. Close to home in Kendall Square, the life-sciences capital of the world, established pharmaceutical companies are seeking new ways to work effectively with startups to externalize their R&D for faster and more efficient development of life-saving medicines and therapies. (Admittedly, these paths to innovation pose their own challenges.)
Is innovation in AI different? We keep hearing that for AI to be effective, machines need vast amounts of data on which they can train to become better at whatever task they are intended to perform. This parameter is hard to get around if your company doesn’t have control over massive datasets (like Google or Facebook, for example) or doesn’t have the resources to purchase datasets from companies that amass those for sale. It would seem that the companies with the most data assets and resources at their disposal would have a significant advantage over the smaller market entrants.
At the Synergy Global Forum conference, a lively discussion ensued about the viability of startups in the AI space. Is it possible to compete with the likes of Google, or do you have to be a Google or a Microsoft or an IBM, with the kind of resources they have available, to do this? Kurzweil’s answer was, to some extent, “yes.”
Tech giants bank on massive scale
In 2017, Google declared itself an “AI-first” company. “We are now witnessing a new shift in computing: the move from a mobile-first to an AI-first world,” CEO Sundar Pichai wrote on the company blog. “And as before, it is forcing us to reimagine our products for a world that allows a more natural, seamless way of interacting with technology.”
While Google’s latest commercial offerings may seem modest to some, its AI-focused R&D is impressive. If you were to search the United States Patents and Trademarks Office (USPTO) database of patents granted in Class 706 (Data Processing – Artificial Intelligence), Google is among the top three “patent assignees.” The other two are IBM and Microsoft, unsurprisingly. A recent study by McKinsey Global Institute reports that “Tech giants including Baidu and Google spent between $20B to $30B on AI in 2016, with 90% of this spent on R&D and deployment, and 10% on AI acquisitions.” A staggering number indeed, compared to the $6B to $9B investment by startups, according to the study.
Bigger may not necessarily be better
During our conversation, Kurzweil acknowledged that there are ways for much smaller companies to collaborate and get some of the benefits of scale that the larger companies enjoy. (He cited the Open Source Initiative as an example.)
Even on their own, startups can be quite successful. My MIT Sloan colleague Thomas Malone, professor of information technology and director of the MIT Center for Collective Intelligence, points out that there are plenty of opportunities for innovation and discovery in the field of AI that don’t require … Next Page »