Past Performance is Not Indicative of Future Results (2020) • Hacker News Board

Re: Past Performance is Not Indicative of Future Results (2020)

#21

Post by starmftronajoll » Sat, Jul 31, 2021, 4:29 PM UTC

marcinzm wrote: post #6

I find his comment about hallucinating faces in the snow amusing given that humans hallucinate faces in things all the time. And then either post it to Reddit or have a religious experience.

Yes, that is explicitly part of the point Doctorow is making. It’s why the essay mentions the fact that humans see faces in clouds, etc. Humans typically know when they are “hallucinating” a face, and ML algorithms don’t. When humans see a face in the snow, they post it to Reddit; they don’t warn their neighbor that a suspicious character is lurking outside. This is the distinction the essay draws.

Re: Past Performance is Not Indicative of Future Results (2020)

#22

Post by itisit » Sat, Jul 31, 2021, 4:30 PM UTC

marcinzm wrote: post #6

I find his comment about hallucinating faces in the snow amusing given that humans hallucinate faces in things all the time. And then either post it to Reddit or have a religious experience.

Those humans don't typically believe those hallucinated faces belong to people though nor do they call the cops.

Re: Past Performance is Not Indicative of Future Results (2020)

#23

Post by version_five » Sat, Jul 31, 2021, 4:33 PM UTC

itisit wrote: post #22

marcinzm wrote: post #6

I find his comment about hallucinating faces in the snow amusing given that humans hallucinate faces in things all the time. And then either post it to Reddit or have a religious experience.

Those humans don't typically believe those hallucinated faces belong to people though nor do they call the cops.

You don't think a person has ever called the police because they hear a noise they thought was an intruder, or saw someone or something suspicious only in their mind? People make these kind of mistakes too.

Re: Past Performance is Not Indicative of Future Results (2020)

#24

Post by mistrial9 » Sat, Jul 31, 2021, 4:34 PM UTC

version_five wrote: post #9

This article is mostly a straw man, while still containing some valid ML criticism. I am a ML s(c|k)eptic too, in that popular conceptions of what ML is currently overpromise, often don't even understand what ML actually is, and are often just some layperson's imagination about what "artificial intelligence" might do. This article is the opposite. He's treating ML as basically a simple supervised architecture that do…

I like your comment here starting with "straw man" .. and agree with some of the statements.. I have seen lengthy, detailed and authoritative reports that say some of the same things, but in a formal, long-winded way with more added..

This meta-comment of restatement in various contexts, with various amounts of story-telling and technical detail, brings up the educational burdens of communication -- to be effective you have to reach a reader where there are today .. in terms of assumptions, technical learning, and focus of topic.. since this is such a fast-moving and wide subject area, its super easy to miss the distinction between "low value, high volume audio clips recognition" and "life and death medical diagnosis for less than 100 patients". hint - that matters a lot in the tech chain AND the legal structure, and therefore combined, the "do-ability"

Re: Past Performance is Not Indicative of Future Results (2020)

#25

Post by Reimersholme » Sat, Jul 31, 2021, 4:36 PM UTC

swayvil wrote: post #20

I see no path from "observation" to "model" that does not involve an arbitrary (aesthetic? Nonrational, human-necessitating?) choice. This would suggest that "general" AI is impossible. ON THE OTHER HAND There is a variety of general AI, called an "optimizer". It starts with something better than a void. Maybe that's the path we should be looking at.

Well, human thinking relies on prior models/filters for understanding the world as well so that would invalidate us as having general intelligence too?

Re: Past Performance is Not Indicative of Future Results (2020)

#26

Post by ziggus » Sat, Jul 31, 2021, 4:36 PM UTC

version_five wrote: post #9

This article is mostly a straw man, while still containing some valid ML criticism. I am a ML s(c|k)eptic too, in that popular conceptions of what ML is currently overpromise, often don't even understand what ML actually is, and are often just some layperson's imagination about what "artificial intelligence" might do. This article is the opposite. He's treating ML as basically a simple supervised architecture that do…

Agreed. The article reminds me of the arguments that religious fundamentalists make against evolution: "there are still monkeys, so how could it be that we evolved from monkeys, wouldn't all the monkeys have evolved as well?"

Clearly, no biologist claims that humans evolved from modern primates, just like no modern AI researcher seriously thinks that current machine learning methods will lead to "True AI".

Re: Past Performance is Not Indicative of Future Results (2020)

#27

Post by itisit » Sat, Jul 31, 2021, 4:38 PM UTC

version_five wrote: post #23

itisit wrote: post #22

Earlier quoted context omitted.

Those humans don't typically believe those hallucinated faces belong to people though nor do they call the cops.

You don't think a person has ever called the police because they hear a noise they thought was an intruder, or saw someone or something suspicious only in their mind? People make these kind of mistakes too.

Of course, but the consistency of the false positive is the issue. An able-minded person can readily reconcile their confusion.

Re: Past Performance is Not Indicative of Future Results (2020)

#28

Post by m0rphy » Sat, Jul 31, 2021, 4:39 PM UTC

iamnotwhoiam wrote: post #8

Are there any approaches to artificial intelligence that do involve qualitative data or don’t rely entirely on statistical inference?

Maybe if we could invent quantum DNA computing + ML = artificial intelligence that would be perceived and understood by humans.

Re: Past Performance is Not Indicative of Future Results (2020)

#29

Post by marcinzm » Sat, Jul 31, 2021, 4:41 PM UTC

starmftronajoll wrote: post #21

marcinzm wrote: post #6

I find his comment about hallucinating faces in the snow amusing given that humans hallucinate faces in things all the time. And then either post it to Reddit or have a religious experience.

Yes, that is explicitly part of the point Doctorow is making. It’s why the essay mentions the fact that humans see faces in clouds, etc. Humans typically know when they are “hallucinating” a face, and ML algorithms don’t. When humans see a face in the snow, they post it to Reddit; they don’t warn their neighbor that a suspicious character is lurking outside. This is the distinction the essay draws.

People perceive nonexistent threats all the time and call the police. The threshold is simply higher than current AI but that’s a question of magnitude rather than inherent difference. Fine tune a reinforcement model on 5 years of 16 hours a day video and I’m sure it will also have a better threshold.

Re: Past Performance is Not Indicative of Future Results (2020)

#30

Post by shannifin » Sat, Jul 31, 2021, 4:41 PM UTC

> I don’t see any path from continuous improvements to the (admittedly impressive) ‘machine learning’ field that leads to a general AI any more than I can see a path from continuous improvements in horse-breeding that leads to an internal combustion engine.

While I also don't expect that AGI will emerge solely through optimizing statistical inference models, I also don't think "improvements to the machine learning field" consist only of such optimizations. Surely further insights, paradigm shifts, etc., will continue to play a role in advancing AI.

Perhaps it's more a matter of semantics and a bad analogy; "machine learning" seems far more broad a field than "horse-breeding." Horse-breeding is necessarily limited to horses. Machine learning is not limited to a specific algorithm or data model.

Even calling it a "statistical inference tool", while not wrong, is deceptive. What exactly does he or anyone expect or want an AGI to do that can't be understood at some level as "statistical inference"? One might say: "Well, I want it to actually understand or actually be conscious." Why? How would you ever know anyway?