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This is true for every other domain. When every company calls itself a AI company these days. Therefore value of AI/ML and credibility gets diluted. It becomes

This is true for every other domain. When every company calls itself a AI company these days. Therefore value of AI/ML and credibility gets diluted. It becomes very difficult to classify real orgs using hardcode stats from fake ones. When I hear "we are solving x with AI" or "AI driven", it gives me jitters.

f6v 5y ago
The elephant in the room is that AI does not exist, even in "hardcore" orgs. A transformer model is not AI.
- throwaway3699 5y ago
  The classical definition of AI in CS is so broad as it can even include expert systems. I think using that term when the general public sees it differently has done a great disservice to the fields credibility.
- debarshri 5y ago
  What I realized recently is the AI is subjective thing. AI for an Investor might be simple math for an engineer.
- martindbp 5y ago
  > A transformer model is not AI. Well, it's _something_ different. It's not "code" or "programming", so whatever you want to call it, that's what's driving the investment hype.
- qayxc 5y ago
  While I share the sentiment that the term "AI" is applied way too broadly these days, there is a point to be made that it's somewhat difficult to draw a clear line anyway. Back in the early 20th century, chess was considered to be something only an intelligent agent can do. A few decades later programs became competent enough that it took a grand master to beat them. Today, it's hopeless to try and beat a chess program as a human. The next barrier was NLP and understanding/generating text and natural speech. Speech recognition worked reasonably well 20 years ago and is close to human level today. Speech generation - given enough processing power - is now perfectly natural. Text understanding and generation is very close as well. The development of AI bears an interesting resemblance to evolution in that sceptics are busy pointing to "missing links" and as soon as that link is discovered, they chase to the next one. Intelligence itself is defined poorly enough as it is, and watering the term down by slapping the "AI"-label on everything doesn't help that. On the other hand, intelligence is a spectrum and on some aspects of that spectrum, machines have already surpassed humans decades ago (think of calculators, chess, memory, searching and indexing, etc.). IMO, the most important distinction to be made is the difference between AGI and AI. A transformer model is AI in every useful definition of the term "intelligence", but it sure isn't "general intelligence" if only for the fact that it cannot actively query its environment for additional information and has no continuous stream of "consciousness". Before we can dismiss a system as not being AI, we need a sharp enough definition of what we would define as AI first. A "I know it when I see it"-type of definition isn't helpful and always keeps the door open for the ultimate rejection: "but it still hasn't got a SOUL!"
  - lordgrenville 5y ago
    "As soon as it works, no one calls it AI anymore" - John McCarthy
beforeolives 5y ago
I have geniunely considered switching away from data science altogether for this reason.
- axelroze 5y ago
  Why? The only other branch of IT that pays as good as Data Science/Engineering is Blockchain Developer. The field of AI applications will only grow and thus career opportunities as well. Are people in serious finance bothered that there are a bazzilion of scams every day, including aforementioned blockchains? No. Why should competent AI practitioners care as well?
  - lou1306 5y ago
    > Why should competent AI practitioners care as well? AI took decades to recover from its first boom-bust cycle. No matter how competent you were back then, getting hired or funded to run your AI business/academic project/whatever was hard because the first wave of AI failed to deliver. Sure, now AI/ML/Data Science is very commercially/acadamically viable, but the hype has also grown spectacularly. If the general public fails to manage expectations, another AI winter cannot be ruled out.
delfinom 5y ago
Most of the "AI" I see is just linear regressions run on meager datasets which lets them stick on that AI label but could have been written by a person with a little effort.

f6v 5y ago

The elephant in the room is that AI does not exist, even in "hardcore" orgs. A transformer model is not AI.

throwaway3699 5y ago
The classical definition of AI in CS is so broad as it can even include expert systems. I think using that term when the general public sees it differently has done a great disservice to the fields credibility.
debarshri 5y ago
What I realized recently is the AI is subjective thing. AI for an Investor might be simple math for an engineer.
martindbp 5y ago
> A transformer model is not AI. Well, it's _something_ different. It's not "code" or "programming", so whatever you want to call it, that's what's driving the investment hype.
qayxc 5y ago
While I share the sentiment that the term "AI" is applied way too broadly these days, there is a point to be made that it's somewhat difficult to draw a clear line anyway. Back in the early 20th century, chess was considered to be something only an intelligent agent can do. A few decades later programs became competent enough that it took a grand master to beat them. Today, it's hopeless to try and beat a chess program as a human. The next barrier was NLP and understanding/generating text and natural speech. Speech recognition worked reasonably well 20 years ago and is close to human level today. Speech generation - given enough processing power - is now perfectly natural. Text understanding and generation is very close as well. The development of AI bears an interesting resemblance to evolution in that sceptics are busy pointing to "missing links" and as soon as that link is discovered, they chase to the next one. Intelligence itself is defined poorly enough as it is, and watering the term down by slapping the "AI"-label on everything doesn't help that. On the other hand, intelligence is a spectrum and on some aspects of that spectrum, machines have already surpassed humans decades ago (think of calculators, chess, memory, searching and indexing, etc.). IMO, the most important distinction to be made is the difference between AGI and AI. A transformer model is AI in every useful definition of the term "intelligence", but it sure isn't "general intelligence" if only for the fact that it cannot actively query its environment for additional information and has no continuous stream of "consciousness". Before we can dismiss a system as not being AI, we need a sharp enough definition of what we would define as AI first. A "I know it when I see it"-type of definition isn't helpful and always keeps the door open for the ultimate rejection: "but it still hasn't got a SOUL!"
- lordgrenville 5y ago
  "As soon as it works, no one calls it AI anymore" - John McCarthy

beforeolives 5y ago

I have geniunely considered switching away from data science altogether for this reason.

axelroze 5y ago
Why? The only other branch of IT that pays as good as Data Science/Engineering is Blockchain Developer. The field of AI applications will only grow and thus career opportunities as well. Are people in serious finance bothered that there are a bazzilion of scams every day, including aforementioned blockchains? No. Why should competent AI practitioners care as well?
- lou1306 5y ago
  > Why should competent AI practitioners care as well? AI took decades to recover from its first boom-bust cycle. No matter how competent you were back then, getting hired or funded to run your AI business/academic project/whatever was hard because the first wave of AI failed to deliver. Sure, now AI/ML/Data Science is very commercially/acadamically viable, but the hype has also grown spectacularly. If the general public fails to manage expectations, another AI winter cannot be ruled out.

delfinom 5y ago

Most of the "AI" I see is just linear regressions run on meager datasets which lets them stick on that AI label but could have been written by a person with a little effort.