This just goes to show just how tragically far away we are from even beginning to build the rudiments of a strong general purpose AI. For all the fantastic achievements of systems like Watson and Alphago, and they are amazing achievements, they are radically optimised special purpose systems fine tuned to solving one extremely specific and narrow problem, and that problem only.
Watson is a case study in this, but I know Google has big plans for applying the tech behind Alphago in medicine. I wish them every success, but I'm concerned they will hit similar specialisation issues.
Medicine - the biggest prize, the biggest trap. Every complication, huge, mind blowing rewards. Maybe, if Google were to go 100% they could break the beast... but it's a 100bn bet.
Untill you actually have a viable, testable plan to implement it almost allege money you throw at it is pretty much certain to be wasted.
The Manhattan project is often given as an example, but that project was based on solid theoretical models and repeatable experiments. They knew exactly what they were doing and how they were going to do it.
The problem in AI at the moment is mainly developing talent and expertise, not capital funding. I'm all for advanced research into technologies. However we need to advance that research on as many different fronts as possible in a flexible way simply because we don't know how we are going to solve the problem of general AI. Guessing on an approach and spending billions on it would be a complete waste. We're simply not at a point where that would do any good.
Agree, they should have focused on much more tractable domains before Medicine.
I think that there's an business case issue here; MBA's see this as the mega win, the research staff can't say "it won't work" (because you are immediately flagged as an obstacle to progress and the execs either cease to listen because they don't want to hear, or you get bullied with an avalanche of attacks on your team or sacked).
Watson is a case study in this, but I know Google has big plans for applying the tech behind Alphago in medicine. I wish them every success, but I'm concerned they will hit similar specialisation issues.