I take issue when people seem to think that AI is only AI if it resembles what we’ve been shown in movies. I actually unsubscribed from a podcast when one of the hosts said that none of what is currently being touted as AI counts because it’s essentially not AGI or super AI. #petty 😒
That being said, I think this framework laid out by Ben Evans is pretty spot on: 👌
Indeed, I think one could propose a whole list of unhelpful ways of talking about current developments in machine learning. For example:
- Data is the new oil
- Google and China (or Facebook, or Amazon, or BAT) have all the data
- AI will take all the jobs
- And, of course, saying AI itself.
More useful things to talk about, perhaps, might be:
- Enabling technology layers
- Relational databases.
Machine Learning’s current superpower is level of automation that seems almost magical. Of course this also means that products can claim to be AI/ML based but really just be a crazy automation stack. And maybe using some “new” terminology to talk about AI/ML/DL will help lead to constructive conversations and a better informed public instead of turning everything into a discussion about Terminator. 🤖
This might be my favorite part of the post: ❣️
Talking about ML does tend to be a hunt for metaphors, but I prefer the metaphor that this gives you infinite interns, or, perhaps, infinite ten year olds.
ML is amazing, but it isn’t omnipotent or truly intelligent in the way we would probably consider the meaning of that word (at least our limited, ego-driven meaning of it). Yeah, it can be like a superpower, but its superpower is that it’s the quietest assembly of unlimited 10 year olds you’ve ever (legally) put to work. ⚡