Conventional coding practice is prototype first, optimization second.
Thus, optimizing for power consumption is only really useful if you consider Watson to be a useful prototype that we’d benefit from marketing as a product. Otherwise, we’re better off waiting until we have something that actually usefully benefits from optimizations. And we’ll get there faster by being wasteful.
See two othercomments. I am well aware of this idea in rapid prototyping. I’m not quibbling over being a bit wasteful because of legitimate engineering concerns. I do rapid prototyping in Python for computer vision algorithms all day, and if I handed my boss the equivalent of Watson but for object tracking, I’d get laughed out of the room. I’m not even talking about stringent power optimization; I’m only asking for the intentionality of the problem solvers to even be aimed at the same problem, in the same ball park. There’s a big difference between saying, “how large do we have to make this in order for a stupid, bad qualitative solution to be computationally tractable” vs. “what is a qualitatively insightful way to solve this problem, and then we can up the resources if the full-blown solution would just be a mere matter of optimization.” Watson is not something for which power optimization could even in principle reduce it to efficiency on the scale of a primate brain. You have to actually represent the whole problem of natural language processing differently than they have.
I already agree that Watson is a brilliant device for generating public interest, which was its original intent. It may even be good in its new role helping to assist in medical queries. But none of these has anything to do with why I brought up the hardware constraints in the first place.
I also strongly dispute the claim that power optmization is only useful if we see Watson as a product. First of all, some people do and second, solving natural language and cognition problems has a lot of potential benefits for society regardless of whether or not there are specific products stemming from it in the short term. You might benefit from this book when it comes out in Feb. 2012.
Conventional coding practice is prototype first, optimization second.
Thus, optimizing for power consumption is only really useful if you consider Watson to be a useful prototype that we’d benefit from marketing as a product. Otherwise, we’re better off waiting until we have something that actually usefully benefits from optimizations. And we’ll get there faster by being wasteful.
See two other comments. I am well aware of this idea in rapid prototyping. I’m not quibbling over being a bit wasteful because of legitimate engineering concerns. I do rapid prototyping in Python for computer vision algorithms all day, and if I handed my boss the equivalent of Watson but for object tracking, I’d get laughed out of the room. I’m not even talking about stringent power optimization; I’m only asking for the intentionality of the problem solvers to even be aimed at the same problem, in the same ball park. There’s a big difference between saying, “how large do we have to make this in order for a stupid, bad qualitative solution to be computationally tractable” vs. “what is a qualitatively insightful way to solve this problem, and then we can up the resources if the full-blown solution would just be a mere matter of optimization.” Watson is not something for which power optimization could even in principle reduce it to efficiency on the scale of a primate brain. You have to actually represent the whole problem of natural language processing differently than they have.
I already agree that Watson is a brilliant device for generating public interest, which was its original intent. It may even be good in its new role helping to assist in medical queries. But none of these has anything to do with why I brought up the hardware constraints in the first place.
I also strongly dispute the claim that power optmization is only useful if we see Watson as a product. First of all, some people do and second, solving natural language and cognition problems has a lot of potential benefits for society regardless of whether or not there are specific products stemming from it in the short term. You might benefit from this book when it comes out in Feb. 2012.