If it isn’t clear to everyone, this is a gesture meant to calm public populace fears about “AI”.
First of all, there is no definition of “AI”. It’s a running joke in the community that once an “AI” approach gets good enough to be commoditized it is no longer called “AI” and becomes simply “ML” (machine learning) that we teach to college students.
With that in mind, military drones have used “AI” since at least during the Obama administration. This is a nonstory.
I’ve been to summits like the one talked about that are a bunch of people in government, nonprofit, or for profit executive roles that get together to discuss things they don’t understand and make a resolution that looks good. They are all for show. Nothing useful, meaningful, or impactful comes from these things.
Yes, yes, we should be responsible with the use of AI. Everyone agrees without asking what that really means.
I am once again baffled by folks in the tech industry being totally unaware of what came before them.
You are, in a way, asking what consciousness is and how one could recognize it. This has been a philosophical topic for millennia; this is a reasonable place to start reading: https://plato.stanford.edu/entries/consciousness/
It is a very interesting and deep topic. But let’s not pretend that recent advances in AI are the thing that brought it up for the first time.
I feel like fluff articles like this are written by people who have never actually been in the situation they write about.
One of the first things one learns when working professionally is to say “I’ll look into that and get back to you” or some such instead of “I don’t know” and just standing there.
It never ceases to baffle me how people in the tech industry are completely unaware of everything that preceded them. The meandering exploration described in this article could have been short circuited by an understanding of things are standard topics in organizational psychology. There’s a wiki article on it: https://en.wikipedia.org/wiki/Leadership_style
I echo others here in the sense that “mastering programming” is not well defined. It’s interesting to try to define what that might be though. For example, I know people who would qualify as “master Java programmers” if there ever was one, but that doesn’t make them “master programmers”.
I think that in my life I have met one person that I would call a master programmer. He was intimately familiar with C, C++, Java, Erlang, Perl, APL, Ruby, Python, Prolog, Haskell, Scala, and more. You could probably find a person that is more of an expert in any one of those, sure, but that’s beside the point. The reason this fellow qualifies as a master of programming, for me, is that he seems to have complete knowledge of where every language came from, how that influenced its semantics, what the pros and cons of each language’s design are, and could code more or less idiomatically in any one of all those languages and explain why it was idiomatic.
Based on that, I’d say that if there is such a thing as a “master programmer”, it’s probably someone so well versed in computational theory and language design that picking up a new language is just a fun afternoon.
I am sure others will have different viewpoints. This is my two cents.
The fact that the data is from 1915 - 1920 does not invalidate it unless you want to suggest that human nature in 1915-1920 is different than it is now - which would seem a strange point to defend. And the sample sizes are quite decent.
I know that the HM userbase had a tendency to dismiss studies that are incorrectly conducted, but I don't think that this is one of those cases.
It sounds like you haven't actually understood that argument. "The guy in the room" has always been a minor detail. Furthermore, machine translation has existed since before convolutional neural nets, so your whole point falls under the "not even wrong" category.
>Philosophers interested in mind and cognition tend to take a great deal of interest in developments in CS and neuroscience.
And they tend to mangle it by inserting rigorous scientific results into a nonrigorous framework that often ends up being a game of word association played using misunderstandings of basic science.
Logic is taught exactly in mathematics and computer science programs as a mandatory topic. Philosophy programs place far less emphasis, often providing it only as an elective.
As a person that has interviewed for and gotten jobs at multiple Fortune 500s (whose tech departments varied from abysmal to impressive effective) and as a person that has been a part of the interviewing/hiring process several times, I appreciate the attempted formalization of interview metrics and see more than a little value in the metrics described in the article.
To me, though, there is one "metric" that trumps all the rest, and that is personality fit with existing employees. If you have two brilliant software engineers that just absolutely cannot stand each other, nothing will get done. The best interview experience I've had, personally, has been to be placed into a technical interview - "start programming application X that does Y" - with two existing employees looking over my shoulders asking me why I'm doing what I'm doing and why not something else.
The technical justification for my chosen solution to the technical interview question didn't matter much once it was clear I covered a base level of technical ability, but it was incredibly valuable that I and the employees looking over my shoulder didn't want to get into a fistfight after an hour - it meant that we could amicably disagree, support our reasonings for our arguments, and then not have sticks up our asses when the other person's proposed solution ended up being the right one, and then gracefully defer and say "thank you for the conversation and debate." That meld is immensely important.
That said, I do recognize that it becomes increasingly difficult to gauge this sort of interaction with increasingly large teams. My experience interviewing and being interviewed is limited to cases where it's been a team of 3 - 8 people. For larger teams, perhaps such a formalized approach makes sense. I do not have any experience that informs me as to whether it is or isn't.
But then I have to ask whether there should be a team of more than about 8 people without a dedicated manager. I don't have anything more than a gut answer to that question, but my gut says no.
First of all, there is no definition of “AI”. It’s a running joke in the community that once an “AI” approach gets good enough to be commoditized it is no longer called “AI” and becomes simply “ML” (machine learning) that we teach to college students.
With that in mind, military drones have used “AI” since at least during the Obama administration. This is a nonstory.
I’ve been to summits like the one talked about that are a bunch of people in government, nonprofit, or for profit executive roles that get together to discuss things they don’t understand and make a resolution that looks good. They are all for show. Nothing useful, meaningful, or impactful comes from these things.
Yes, yes, we should be responsible with the use of AI. Everyone agrees without asking what that really means.