Even before LLMs I used to joke with my traditional SE coworkers that "philosophy is very practical." On nearly every project we'd have to talk to stakeholders and ask questions like, "But when you say X, what do you mean?" Establishing definitions, relationships between concepts, etc etc turns out to be really important when you're encoding ideas into a block of silicon. (Yes I know other fields do versions of the same thing too.)
One thing I've never seen discussed on this topic (possible I just missed it, I only read popular accounts) is whether speaking multiple languages is a proxy for higher sociability / stronger social ties. That's a known dimension that improves health and aging and I wonder if just being able or interested in speaking with a broader swath of people is what helps more than the cognitive demands of switching.
You're ignoring the core analogy. The author's point is that someone (or something) can be verbose and articulate about a topic without having any real knowledge or experience of it. I can talk at length about war because I've seen Saving Private Ryan and read a hundred books on the topic, but do I really understand what it's like to be shot at, or to watch my friend die? No, I don't. My cousin's husband does, though, because he experienced both of those things.
The author is saying that that difference matters, that it isn't just a philosophical point but is actually a fundamental aspect of this new technology. I can spit out a bunch of words about war, and so can an LLM, but our understanding of war is limited to textual representations of it. Thomas Hobbes made this exact point centuries ago when he said, "Words are the wise man's counters but the money of fools."
As a complete aside, I don't agree that "Good Will Hunting" is a power fantasy. The whole point of the movie is that that power was illusory, and that it has nothing to do with what really matters in life.
It's a really fun philosophical exercise to ask what it means for them to be "wrong." My perspective is that they are fantastic at association and generalization (of language and symbols in particular), but whether they're identifying the associations you care about or generalizing to the level of abstraction you're aiming for is a complete crapshoot. If you aren't checking and correcting them, and discarding the misfires, you will end up with a very pretty Tower of Babel.
I think I've done a good job straddling the delivery/maintainability line thus far. In the near future I'm likely going to have to downshift into smaller, higher quality changes and refactors, but I've been careful to keep an eye on the output and make sure the functions are reasonably scoped, documented, and understandable. I don't anticipate any issues maintaining what I've produced so far, but it could easily get out of hand as more concepts get mixed in.
I hesitate to say this because I think the AI hype is generally overdone, but I was contemplating the other day how much I would recommend my employer spend on AI tooling for me based on my salary and it's got to be in the tens of thousands of dollars per year if I'm being honest. I'm a contractor. On my most recent client, I was able to learn a completely new domain and business, design a solution and build a full stack POC (a complicated one with technologies I had never used before) nearly singlehandedly in less than 2 months. That includes all of the onboarding time, getting access to the right people, repositories, databases etc. What made it possible was 1) the AI helped me understand technologies I had never used before, from a 30 year old Java stack to graph databases, 2) it could analyze DDLs and make correct inferences about what tables and columns meant in both business and technical terms, 3) it generated mostly-correct code in multiple languages to achieve what I needed it to do, and 4) it referenced libraries I didn't know existed to accomplish tasks I needed done. I could cycle between these activities and iterate FAR more rapidly than I ever have before. To me this is the thing the AI companies should really
be emphasizing. I'm not convinced autonomous agents are really working out, but I'm 1000% sold on their ability to empower developers. And I say this as a pretty skeptical late adopter who only knows the most basic AI tooling.
I mean in the Big 5 personality model sense. Someone who is neurotic is sensitive, more prone to negative emotions including fear. Someone who is low in neuroticism is less fearful and sensitive on average. So for example you could put two people in the situation of being about to jump out of a plane and one would feel terrified for their life while the other would feel only mild apprehension.
EDIT: People are a complex blends of emotions and motivations, so you're certainly right that can be another explanation for the same observable behavior. I really liked the comment about adrenaline junkies too. My point was only that on average it's low-sensitivity people who engage in those sorts of activities. Scaredy cats like myself stay home and read a good book.
I agree it's counterintuitive, but it makes sense when I think about how, for example, it's the least neurotic people who do high-risk activities like base jumping or mountain climbing. Fear drives you away from threatening things, lack of fear allows you to move toward them more comfortably.
This is one of those classic "sounds dumb / doesn't play well on TV but is actually smarter than most of the other people babbling about it" things. Nassim Taleb has written for example about how maddening it is to watch world-class economists who are also just sort of awkward and a little nerdy go on TV and "lose" to blowhards who don't actually know what the hell they're talking about but appear confident and look good on camera. Thankfully in Rumsfeld's case I think as time has gone on it's become a pretty respected statement about risk even if people still occasionally find the phrasing a bit amusing.
I grew up solidly middle class, even went to a good private school. A couple of my friends got ripped off by an addict that ran in our social circle who had the same background. They couldn't find the person, but they were so angry that they looked up the parents' address and went to confront them, assuming they'd be like bad people or something or had failed to raise their kid right. Instead both parents were incredibly mild and apologetic, and basically said, "We don't know what happened to our child and where it all went wrong." My friends felt very ashamed, apologized and left them in peace. It's a really tragic thing, and it's not just a cliche that it can happen to anyone.
I found it very useful running a TDD workflow the other day. It created a test plan, generated tests, documented them, implemented and modified existing code, and added structured logging. It also identified really good refactor candidates and explained them to me after I noted a core design issue in the code we were modifying. This wasn't autonomous: I spent some time correcting it and sending it in new directions. Still, it was a pretty nice feeling to not have to go manually configure Logback (it one shotted a nice basic config), not have to write a bunch of repetitive test setup code, etc. It even pulled in a newer JUnit feature that I didn't know about that was perfect for what I was doing. Definitely not the silver bullet a lot of people are trying to sell, but still a very powerful tool.
Bought a Kobo and decided I'm just going to stick to Ebooks.com DRM-free section from now on. Tired of not owning what I buy.
I did the same with music, using an Innioasis iPod knockoff + buy MP3s from Amazon Music, cheaper than Spotify and I never have to worry about my music becoming unavailable. I also prefer the experience of single-use devices.
I'm not buying into this vision at all, but, hypothetically, they could use money to optimize whatever reward function they're trained on. They could perceive it like any other resource to achieve those ends. You can also imagine a universe where it "reasons" something like, "I do work, people who do work should get paid, I should get paid" irrespective of its goals.
Just yesterday one of my junior devs got an 800-line code review from an AI agent. It wasn't all bad, but is this kid literally going to have to read an essay every time he submits code?
I had some of my own struggles but I really started noticing this more broadly in the last 2-3 years. I'm not sure if Covid did it, the end of ZIRP did it, or what, but there was a shift where suddenly almost every SE I would talk to seemed to be burned out. I can think of a lot of potential reasons but honestly the thing that jumped out at me the most is how almost in perfect sync it seemed to happen across the profession. It's a real bummer, I remember when SE was a pretty fun profession and people seemed generally pretty happy coming to work. (Maybe this was some kind of illusion though or I was just lucky where I worked at the time. I've heard plenty of death march horror stories from the old timers too.)
I've been looking into Ada recently and it has cool safety mechanisms to encourage this same kind of thing. It even allows you to dynamically allocate on the stack for many cases.