The New York Times ran an article
this week looking at the extraordinary salaries earned by researchers in artificial intelligence. It mentions the $1.9m paid to the top researcher at OpenAI and the $345,000 average
cost per employee at DeepMind.
People are expensive in AI - and the costs don’t end there. There are now 19+ companies designing their own chips for deep learning acceleration, according to James Wang
. Barrons has a piece
looking at some of the contenders in this space. It’s clear it’s a race that is going to consume enormous sums of capital in the next few years.
So why might it be worth it? Even if you dismiss the likelihood of general intelligence
, what’s already happening is extraordinary - not least in software engineering itself. This tweet
mentions that Google used machine learning to reduce the lines of code in Google Translate from 500,000 to 500
- i.e. the software “learned” how to write more efficient code. This is just one instance, but it will happen everywhere. Jeff Dean (who leads Google’s AI work) gave an amazing presentation
on this topic late last year at NIPS (one of the top AI conferences). Software that can write software will change everything; it’s worth spending a lot to invent it.