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And I get where you're coming from but we don't know when something is working until science. See the recent frontpage article on LK-99. If you got jets and ai

And I get where you're coming from but we don't know when something is working until science. See the recent frontpage article on LK-99. If you got jets and airliners, sure you can look up at the sky and see the thing working. But if you're at the stage where people are jumping off hills with makeshift wings tied to their arms, then you need some other way to know what works, and which way to keep digging. That other way, that is science.

YeGoblynQueenne 3y ago
@bonoboTP: This is a bit late now and you'll probably not see it, but it occurred to me that we are talking about different things, throughout. When you're talking about progress, you mean neural nets now work better than before in classifying images, recognising speech, translating text, etc. What I mean on the other hand is progress towards artificial intelligence. I don't have any difficulty accepting that image classifiers work better now than 20 years ago (although see my comments about why) and we perhaps don't necessarily need science to understand this. What we do need science to understand is whether that kind of progress is progress towards artificial intelligence. And I would very much like to say that that is irrelevant because personally I don't care much about creating artificial intelligence, but a) that's the name of the field and b) many people in machine learning seem convinced that artificial intelligence is what they are trying to build (see e.g. how "the AI" became a common way to refer to neural net systems in recent years, even appearing in scholarly articles by people who should really know better, but, unfortunately, don't seem to). In other words, is progress in classification at all connected to progress towards artificial intelligence? That one is a scientific question. The problem of course is that we have plenty of metrics to measure the performance of classifiers, but no good tests to detect the presence of anything like intelligence. I've thought of writing a paper to propose some but every time I'm like, nah, that's not what I'm working on, let someone else do it.

YeGoblynQueenne 3y ago

@bonoboTP: This is a bit late now and you'll probably not see it, but it occurred to me that we are talking about different things, throughout. When you're talking about progress, you mean neural nets now work better than before in classifying images, recognising speech, translating text, etc. What I mean on the other hand is progress towards artificial intelligence. I don't have any difficulty accepting that image classifiers work better now than 20 years ago (although see my comments about why) and we perhaps don't necessarily need science to understand this. What we do need science to understand is whether that kind of progress is progress towards artificial intelligence. And I would very much like to say that that is irrelevant because personally I don't care much about creating artificial intelligence, but a) that's the name of the field and b) many people in machine learning seem convinced that artificial intelligence is what they are trying to build (see e.g. how "the AI" became a common way to refer to neural net systems in recent years, even appearing in scholarly articles by people who should really know better, but, unfortunately, don't seem to). In other words, is progress in classification at all connected to progress towards artificial intelligence? That one is a scientific question. The problem of course is that we have plenty of metrics to measure the performance of classifiers, but no good tests to detect the presence of anything like intelligence. I've thought of writing a paper to propose some but every time I'm like, nah, that's not what I'm working on, let someone else do it.