Over the past few years, artificial intelligence has begun to dominate news cycles, and it has captured the attention—and the imagination—of entrepreneurs, investors, and consumers alike. What’s not fascinating about self-driving, on-demand transportation, and robotic assistants in the home?
As much as we talk about AI, many still wrongly compare artificial intelligence to human intelligence, suggesting that human intellect is the AI end goal. But it’s not. In fact, if 10 is the upper limit of intelligence, human intelligence is much closer to one than it is to 10.
Human Intelligence Is a Bar, Not “the” Bar
To many, the goal of AI is to create technology that can think like humans—but it’s oversimplifying to suggest that any human or AI intelligence can be rated on such a simple scale as “better” or “worse.” Some people excel at memorization, logic or emotional IQ, yet others thrive at the visual or auditory. Similarly, a form of AI may have strengths and weaknesses. Furthermore, why have a goal of just matching humans when outdoing them is within reach?
Many of the most promising applications of AI aren’t the ones that seem most like us, but rather, the ones that can do things we never even contemplated.
Think about all the dimensions where AI seems to have already surpassed human intellect. Can anyone you know translate a passage into any one of 300 languages within a fraction of a second, or instantly determine the optimal driving route to avoid all traffic? On many tasks, machines have already learned to outperform us.
What Should We Expect From Artificial Intelligence?
Different types of AI are worth understanding. For instance, artificial general intelligence (AGI) requires no training data beyond direct “human” experience and mimics a human’s ability to observe and interact with the world just as a child would. It is fun to imagine coexisting with machines that are relatively indistinguishable from humans, but it is not a useful benchmark for understanding the trajectory of AI, and how it will impact most products and industries.
Next-level impact during the coming decade will include domain-specific use cases that need reams of data and speedy algorithms. Domain-focused AI will disrupt entire industries and is already transforming advertising. For instance, each time an ad is served and not clicked, it is an extra data point to train the AI for future campaigns—a small opportunity for the system to learn, and more importantly, make new conclusions.
The Symbiotic Relationship Between Data and AI
Nearly every industry—from brick-and-mortar shopping and TV ads to mobile marketing and payments—is moving toward a digital reinvention that requires a massive amount of data, and so on. That’s exactly why I founded Factual—to power digital innovation with the highest-quality location data. And to build an engine for producing such data, we built our own AI, which is in turn fed by even more data from our partners—a terrific feedback loop.
The effectiveness of our proprietary AI can’t be easily compared to a human scale because the capabilities derive meaning from processing trillions of data points. Many of the most promising applications of AI aren’t the ones that seem most like us, but rather, the ones that can do things we never even contemplated.