Good Old Fashioned AI is dead, long live New-Fangled AI
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Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#2The "new-fangled" AI, as the article calls it, is often useful when the stakes are low, and you can accept mistakes in outcomes. Examples of such applications are: trying to determine which of your friends occur in a photo, which movies a subscriber may be interested in, or which action could lead to victory in a computer game. Getting a rough translation of a newspaper entry, as mentioned in the article, is also a good example.
As soon as you need reliable outcomes, such as certainty whether an erroneous state can arise in a program, whether a proof for a mathematical conjecture exists, or whether a counterexample exists, exhaustive search is often necessary.
The question then soon becomes: How can we best delegate this search to a computer, in such a way that we can focus on a clear description of the relations that hold between the concepts we are reasoning about? Which symbolic languages let us best describe the situation so that we can reliably reason about it? How can we be certain that the computed result is itself correct?
The article states: "The heart of GOFAI is searching – of trees and, more generally, graphs." I think one could with the same conviction state: "The heart of GOFAI is reasoning – about relations and, more generally, programs."
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#3[deleted]
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#4The "new-fangled" AI, as the article calls it, is often useful when the stakes are low, and you can accept mistakes in outcomes. Examples of such applications are: trying to determine which of your friends occur in a photo, which movies a subscriber may be interested in, or which action could lead to victory in a computer game. Getting a rough translation of a newspaper entry, as mentioned in the article, is also a g…
GOFAI was never more than a rules engine. If-then statements.
Agree with you about probabilistic AI being useful in low-stakes situations, at least at first.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#5Why do the eyes in the generated images always look a little off? Most facial features usually appear photorealistic to me, but the eyes always have a little smudge or something in them that gives them away.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#6The "new-fangled" AI, as the article calls it, is often useful when the stakes are low, and you can accept mistakes in outcomes. Examples of such applications are: trying to determine which of your friends occur in a photo, which movies a subscriber may be interested in, or which action could lead to victory in a computer game. Getting a rough translation of a newspaper entry, as mentioned in the article, is also a g…
> As soon as you need reliable outcomes, such as certainty whether an erroneous state can arise in a program, whether a proof for a mathematical conjecture exists, or whether a counterexample exists, exhaustive search is often necessary.
Checking proofs is easier than finding proofs.
> The question then soon becomes: How can we best delegate this search to a computer, in such a way that we can focus on a clear description of the relations that hold between the concepts we are reasoning about? Which symbolic languages let us best describe the situation so that we can reliably reason about it?
These questions are largely answered. Or, at least, the methodology for investigating these types of questions is well-developed.
I think the more interesting question is co-design. What do languages and logics look like when they are designed for incorporation into new-fangled AI systems (perhaps also with a human), instead of for purely manual use?
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#7Why do the eyes in the generated images always look a little off? Most facial features usually appear photorealistic to me, but the eyes always have a little smudge or something in them that gives them away.
Maybe because the training data have a lot of bad photos with the red dot in the eyes.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#8The "new-fangled" AI, as the article calls it, is often useful when the stakes are low, and you can accept mistakes in outcomes. Examples of such applications are: trying to determine which of your friends occur in a photo, which movies a subscriber may be interested in, or which action could lead to victory in a computer game. Getting a rough translation of a newspaper entry, as mentioned in the article, is also a g…
> As soon as you need reliable outcomes, such as certainty whether an erroneous state can arise in a program, whether a proof for a mathematical conjecture exists, or whether a counterexample exists, exhaustive search is often necessary. Checking proofs is easier than finding proofs. > The question then soon becomes: How can we best delegate this search to a computer, in such a way that we can focus on a clear descri…
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Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#9The "new-fangled" AI, as the article calls it, is often useful when the stakes are low, and you can accept mistakes in outcomes. Examples of such applications are: trying to determine which of your friends occur in a photo, which movies a subscriber may be interested in, or which action could lead to victory in a computer game. Getting a rough translation of a newspaper entry, as mentioned in the article, is also a g…
GOFAI was never more than a rules engine. If-then statements. Agree with you about probabilistic AI being useful in low-stakes situations, at least at first.
If-then questions can lead to non-deterministic outputs with some simple feedback systems
not disagreeing completely, but.. both "questions that are reasoned about", and "the code that reasons about questions".. need more careful classification in order to make use of these new data methods..
personally, I see the hype on DeepLearning to solve "find pattern in varying digital content" that is so clearly useful to the FAANG content Feudal Lords, is engaging in an investor shouting match that paves over simple use cases where DeepLearning is really not appropriate.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#10People spend an awful lot of time talking about current successes in AI without often reflecting on how much (or little actually) AI impacts their lives. Despite all of the energy put into current gen AI, as far as every day impacts the biggest things I can think of are:
- Spam filtering/email sorting
- Web search
- GPS/Wayfinding
- Voice assistants
These are the only practical applications of "AI" that I use more or less everyday (I'd be happy to reminded of others). Of these 4 I personally have found spam filtering to be getting worse recently, as well as web search. The first 3 were all more or less solved over a decade ago, and, while I find Siri convenient, I wouldn't mind much at all if voice assistants completely disappeared tomorrow.
I'm not denying we've had an amazing decade of pushing the research needle further. There have been tons of impressive AI projects out there. However the practical, day-to-day improvements we've seen with the existence of AI seem to be few and far between, and this is even more true when you start asking about any AI work done in the last decade. I was happier with the state of "AI" in my life in 2006 than I am today.
I just find it a bit fascinating how much energy has gone into both generic data science as well as more serious AI research and yet how little the reach of AI has grown in the last 10 years. All of the cool AI that I use existed before data science was declared the "sexiest job".