At this point, we should have had flying cars. And robot butlers. And with some bad luck, sentient robots that decide to rise up against us before we can cause the apocalypse. While we don’t have that, it is clear that artificial intelligence (AI) technology has made its way into our world. Every time you ask Alexa to do something, machine learning technology is figuring out what you said and trying to make the best determination on what you wanted it to do. Every time Netflix or Amazon recommend that “next movie” or “next purchase” to you, it is based on sophisticated machine learning algorithms that give you compelling recommendations that are far more enticing than sales promotions of the past. And while we might not all have self-driving cars, we’re all keenly aware of the developments in that space and the potential that autonomous navigation can offer.
AI technology carries a great promise – the idea that machines can make decisions based on the world around them, processing information like a human might (or in a manner superior to what a human would do). But if you think about the examples above, the AI promise here is only being fulfilled by “big machines”—things that don’t have power, size, or cost constraints, or to put it another way—they can get hot, have line power, are big, and are expensive. Alexa and Netflix rely on big, power hungry servers in the cloud to figure out your intent. While self-driving cars are likely to rely on batteries, their energy capacity is enormous, considering those batteries must turn the wheels and steer, which are big energy expenses compared to even the most expensive AI decisions.
While the promise of AI is great, “little machines” are being left behind. Devices that are powered by smaller batteries or have cost and size constraints are unable to participate in the idea that machines can see and hear. Today, these little machines can only make use of simple AI technology: perhaps listening for a single keyword or analyzing low-dimensional signals like photoplethysmography (PPG) from a heart rate.
What if little machines could see and hear?
But is there value in small machines being able to see and hear? It is hard to think about things like a doorbell camera taking advantage of technologies like autonomous driving or natural language processing, but there is an opportunity for less complex, less processing intensive AI computations such as vocabulary recognition, voice recognition, and image analysis.