“What is AI?”
On one level, this simple question is reasonably addressed by the intersection of the answers to “What is a person?” and “What is a computer?” Yet when I ask people to define AI—something I regularly do at conferences, parties and the odd Silicon Valley dinner (which might be redundant)—I usually learn more about the person than the technology. That’s because our understanding of AI is complicated by misconceptions and expectations, fear and intrigue.
For better or worse, artificial intelligence has the potential to transform humanity like no technology before. With so much at stake, it is essential for us to speak a common language so that we can better communicate and evaluate the benefits and risks. Personally, I’m an AI optimist—if we’re thoughtful about how we develop and deploy the technology. And in subsequent columns I will explore how AI advances are likely to positively impact society, but first I want to do my part in developing that common language around AI, and share a bit about the AI world in which, as CEO and founder of Node, I live and breathe.
AI is far from a new concept—machines have matched or surpassed humans in many disciplines for decades, sometimes in ways (e.g., chess) that seem intelligent. But early AI technology wasn’t intelligent in any real sense. That is, the systems and mechanisms couldn’t operate without being explicitly programmed to perform a specific task. With recent advances in AI, however, this is starting to change.
Consider “deep learning,” which is the most promising AI technology available today because it doesn’t require explicit programming to function as intended. If you design the algorithms correctly and feed them relevant data, deep learning systems will automatically arrive at the correct conclusions without any human input. (Again, this differs from prior AI technologies that were really just sets of coded instructions or statistical inferences, albeit complicated ones.)
We hear a great deal about consumer applications for AI, which are more ubiquitous than ever: self-driving cars are beginning to prowl the streets, language translators outperform humans in real-time and image recognition software helps drive platforms like Facebook and Instagram.
Increasingly, though, businesses are integrating AI into their core strategies, not as a nice-to-have features but rather as an essential guiding principle for growth. But for enterprises to leverage AI most effectively, they must apply the technology in a manner that drives the specific outcomes they care about. Just as importantly, they need the accurate and comprehensive data that enables AI to make the particular intelligent predictions that will deliver those desired outcomes.
Companies that innovate, grow quickly; those that can’t, wither and die—we’ve witnessed this through the adoption of computers, then the internet and mobile. Similarly, I believe the most immediate consequence of the rise of AI in corporate markets will be a widening gulf between the haves and the have-nots: those that can leverage the technology will grow; those that can’t—well, you get the picture.
Unfortunately, it’s no trivial exercise for businesses adopt an AI-first mentality. Building AI-powered solutions requires expensive talent, significant data management, ongoing support, and vigilance against stagnation. I’ve recently spoken with several businesses that spent between $5 million and $10 million over several years to deploy AI-powered solutions—and mostly failed. Most organizations, especially those without millions of dollars—or years—to spare, don’t have the resources to compete in the AI market battles of the future.
That’s why I believe the best way to foster continued innovation is to democratize access to AI. This gives entrepreneurs with the talent, motivation, and tenacity a shot at being competitive in an AI-first market, regardless of their financial means. I’m incredibly excited by the work we’re doing at Node to help usher in this next wave of innovation by giving businesses the tools they need to deploy AI-powered solutions quickly, without requiring expensive hires or time-consuming builds.
And why we need to move beyond the question of what AI is. The world of AI is coming, whether we like it or not, and we must ask whether it is a world for the many or just the well-funded. I firmly believe that everyone, not just big companies with deep pockets, should be able to play a part in building the future.
