I often wonder if machine learning - at least the kind of machine learning that blindly chases higher numbers on benchmarks - even deserves to be called science.https://twitter.com/poolio/status/1093352689205837825 …
I study brains and intelligence. Anarchist biocosmist. So far I have not found the science, but the numbers keep on circling me. http://davidpfau.com
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David Pfau Retweeted Ben Poole
I often wonder if machine learning - at least the kind of machine learning that blindly chases higher numbers on benchmarks - even deserves to be called science.https://twitter.com/poolio/status/1093352689205837825 …
David Pfau added,
100% agree! Probably a lot of the issues arise from a lack of openly-discussed targets/roadmaps. Obviously hard to generate these from first-principles; but perhaps that makes it even more important to do so... Human cognitive development milestones seem a good place to start.
100% disagree! Endlessly constructing targets and roadmaps is exactly the problem!
Yes, we have too many openly-discussed targets but I think probably zero GOOD ONES motivated by first-principles. I imagine many programs have these internally (e.g. DARPA) but they are not openly discussed Abolishing all targets is a bad solution; we just need good ones.
I think targets work to help you get from A to B. But sometimes it's not even clear what "B" is! These are the things that fall by the wayside if you are excessively focused on metrics. As in all things, there needs to be a balance.
Also in my experience, the DARPA funding model is quite terrible for good science. Too much bureaucracy, all your time is spent on reports instead of working, and the threat of pulling out funding halfway through (which is meant as an incentive!) instead leads to incrementalism.
Because if you know there's a 50% chance your grant will get cut after just one year, you won't pursue any projects that take more than a year to bear fruit.
Just another reason we need Zombie Licklider at the helm again...
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