How do you see impact of using LLM on the teaching content? (genuine curiosity)
In the industry, almost everyone here is doing the exact same thing, outsourcing more and more of their thinking to LLM: so even if students learned how to manually write code, they will probably loose it later on (happening to us already, mostly can be seen when people are working on new solutions/frameworks... they now have the same issue than students).
LLM are quite a good learning opportunity, mostly in classes where learning is sequential/needs building blocks, like mathematics, where if you miss a trimester, it's finished. Here it's like a free and immediately accessible private tutor. It would be great for computer sciences classes indeed.
I would have killed for access to an LLM during school. Not to do my homework (though that too, homework is an antipattern imo) but to fill my gaps at my own pace and level of patience. Just endlessly pestering the AI "ok, but why?" until I grokked it.
It's like the rail industry analogy: we got a big bubble, but the rails are still there. Now with llm, we can just distill expensive one to create cheap open-source ones indeed
I have the theory (not tested, subjective) that current economy prefers buying capital (broadly here defined as machine/tools) than having to pay workers salaries, even if both have the same level of competitivity
Capital expenditures are easy to calculate, and it's easy to help raising money. As the current economical system is based on debts, it works quite well: if a company knows that productivity output will raise by 15% over the next year if they spend X dollars, it's easy to get investments (investments firms themselves are relying heavily on private credits, which more and more is coming from bank too). With a system based on debts, they care less about the amount spent, than the yield generated.
With investing in people, it's harder to predict.
Industry does it by buying machines, now knowledge-based companies might do it with GPUs or tokens.
Good question! Maybe a scheme like in France: we generally separate engineering schools, which teach a mix of theory and knowledge, for getting a white collar hob; and the masters, which teach mostly pure theoretical learning, which leads to an academical career.
Both are at the same levels at +5 years after high-school, but they leads to different career paths.
Everyone is quite worried of their job. Many of us have made coding/IT our personality, what we were proud of, what the society made us feel valued. It's a big change in life... and there is no solution yet.
So everyone feels the needs to talk about it, to either get rid of this anxiety by ranting or trying to prove that it would be an opportunity, or a non-event depending on the point of view, etc
Going off this thought tangent a bit, I think many engineers could be gatekeepers because it's a pretty hard industry to get into and it's just not everybody's cup of tea. Now that AI is assisting people who wouldn't necessarily make it in the old world, it turns out business just cares about results and the gatekeepers don't matter as much anymore. It's creating quite a big split between the old guard and people who just get stuff done even if it creates 10 times the bloat.
I've always been on the get it done side to the chagrin of my peers but I've also never impressed anyone with what I've came up with so who knows.
My personal opinion is that if you don't get with the program, you're probably going to get left in the dust or going to have to split off and do your own thing where you can control what's going on but I think in general in a capitalistic society, the business just wants to get to the next thing to make more money and subpar or middling quality is good enough.
I should caveat my comment that this doesn't apply to pacemaker software and higher end software engineering
Welcome to the club, but remember: you break it, you own it. You will be expected to take part in incident response and explain why it broke and how to remediate it in the post-mortem.
Believe me, I know. I am completely an entirely responsible for a service that receives around 500 requests a second. AI assisted coding has really helped me get through a backlog of things I've wanted to do but never had the time because I was one man.
The tempo of AI development is overwhelming. Within one generation, coding/IT has gone from the most promising career for the young to profound insecurity about the future.
That's true! Even faster, for exemple for young people who started university in September 2022 thinking computer sciences is one of the most promising for job opportunities: they started before ChatGPT was released, and now they haven't yet finished their masters degrees.
I get the analogy of the calculator. The thing however, is that in college, we had dedicated time to learn how to not use it: classes without it, exams without it, etc.
In current job market and pressure, we doesn't have time anymore. You need to be constantly delivering the new jira ticket, and the time expected to perform a task now decreased, as it's expected of the workers that now they are "more productive with AI".
In the industry, almost everyone here is doing the exact same thing, outsourcing more and more of their thinking to LLM: so even if students learned how to manually write code, they will probably loose it later on (happening to us already, mostly can be seen when people are working on new solutions/frameworks... they now have the same issue than students).
reply