That really depends on how you define alive and well. There are still stocks and there are still traders, but the market valuations are obscene and it sure appears that there must be collusion or corruption driving the industry to jam massive IPOs into every index and 401k they can find as fast as possible to fasciliste and exit.
Teaching is a lot like (a certain style of) management. You learn what motivates someone, make the connection between that and the subject matter at hand, and make it accessible for them to get to the next level. The rest takes care of itself.
History bears out that cheap and satisficing soundly beats expensive and optimal every time. Until we have smarter and more prescient decision makers in leadership, the bottleneck on output will be the quality of decision making not the quality of code. Trying more things faster and cheaper will win.
If it were really groundbreaking, I imagine it wouldn't have burned out after a little missed hype. See No Man's Sky.
The other way to look at this is, thank goodness we didn't waste months or years on a failed game concept. Instead we got to market and validated (or invalidated) the concept fast.
Marketing, networking, and sales are the job. Or a large part of it. If you don't have connections, knowing how to make connections is part of it.
Accept that there are other skills besides engineering, and they can be just as challenging to learn, and just as opaque from the outside of you don't understand it.
I've seen this expressed as a concern even from one of my colleagues. My retort was:
"English is not my native language and LLMs taught me quite a few very useful formalisms that do land well for people and they change their attitude towards you to be more respectful afterwards. It also showed me how to frame and reframe certain arguments. I agree sounding like an LLM is kind of sad but I am getting a lot of educational value -- and with time I'll sneak my own voice back in these newly learned idioms and ways to talk."
Since you seem interested in the ins and outs of English, I want to say that "retort" has a connotation of anger or sharpness. Your response reads more like a "rebuttal" to me.
This is not a correction; maybe retort is what you meant and I'm not trying to be the English police. I just like discussing the intricacies of language :)
Like most of all widely spoken languages, there's a lot of regional variation in English. There's even a bunch of quizzes online where you answer 20 questions about phrasings, and they can tell you where you're from with a disconcertingly high degree of accuracy.
In my experience a "retort" is sharp or witty, but certainly not angry, whereas the word "rebuttal" is itself essentially antagonistic. You might use it when referring to something or someone that you look down upon, whereas a more neutral term would simply be "response."
Just personally I tend to regard retort as short and reactive while rebuttal as a longer and more considered disagreement. A retort could be defensive and wrong or it could be sharp and insightful - it doesn't imply one or the other. A rebuttal is mostly an attempt to correct something while a retort doesn't need to be a correction (although it could).
Even something like "piss off!" could be a retort, but usually never a rebuttal :)
Just as I was reading your comment I remembered that Samuel Jackson used "retort" in his speech in the "Pulp Fiction" movie and was wondering whether he was openly antagonistic there (I mean, he killed a bunch of guys with a pistol shortly afterwards but still) or was it a witticism.
I admit I am lost on these nuances and I usually kind of use whatever idiom comes to mind, which yes, likely would net me some weird looks depending on where I am geographically.
So human language will improve and become more precise? I'm all for it, especially if we get more emojis in speech! Why is that sadly? Humans will learn to imitate their more intelligent betters.
There was already evidence last year[1] that pointed to ChatGPT-specific words like "meticulous," "delve," etc becoming more frequently used than they were previously. The linked study used audio of academic talks and podcasts to determine this.
Part of me wanted to object to those two examples, which I’ve used frequently since the reaching adulthood in the 80s. Another part of me has been triggered by an apparent uptick in the word “crisp”, which my gut takes as an coding-LLM tell.
Opus 4.7 loves to use the word “substrate” whenever it gets the chance, it’s a really weird tic. How do these models end up this these sorts of behaviors?
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