AI and AAI Fin Analytics

AI and AAI

The paradigm shift towards conversational / bot interfaces in response to consumer app fatigue has been accompanied by a lot of buzz about “AI.”

All of this buzz (somewhat disappointingly) is just a conflation of the chat interface with “AI” due to the central role that conversation plays in the Turing test for machine intelligence — it’s not the result of any breakthroughs in general intelligence / deep learning that would enable new consumer applications. The exciting “AI” action is still in the realm of research labs like Vicarious or Google’s Inceptionism (perhaps an early version of “computer thought”?).

If we already had AI in the strong sense, Siri (and similar products) would be good. Today, however, Siri et al can really only perform narrow tasks like setting reminders, checking the weather, and dialing phone numbers (and they only get it right about half of the time).

The result is a tantalizing glimpse of the AI powered interface from all the sci-fi (Samantha from Her, HAL from 2001: A Space Odyssey, Jarvis from Ironman), that makes us yearn for this awesome style of interaction even more.

At Fin, we’re tired of waiting for “AI” / software to deliver on the future, so we’re trying to build it with “AAI” — artificial artificial intelligence. We will combine the best of both software and human intelligence to get the results we want — namely, a system that functions like the AI powered ones from sci-fi.

We’re less concerned with modeling pure software algorithms after individual brains, and we look instead to biological models at the species or ecosystem level, where we observe diverse sets of creatures participating symbiotically in a system that exhibits probabilistic tendencies.

With this in mind, we try to design all of the hybrid systems powering Fin to have feedback loops that ensure subsequent interactions tend to be better and better over time (just as we observe systems like evolution of species and survival of the fittest within species trend towards this in nature). This means that when we talk about “AI” at Fin, we don’t mean “artificial intelligence,” but “always improving.”

The practical upshot of our bastardized interpretation of “AI” is a service that delivers human level intelligence and understanding to our users today and over time is constantly learning more about them and getting faster and cheaper as our software systems grow more sophisticated.

If you’re interested in this framework for designing intelligent systems, drop us a line.