I can imagine that this will be similar to the "Emacs/Vim in the AI age" article - it will just be considered to matter less in the AI age. Why spend 3-5 years of your life with a sometimes frustrating experience to obtain this PhD degree if you have powerful models at your disposal that will just be able to solve everything for you? (Similar to why learn Elisp/VimScript/...) Especially considering the current trajectory, expecting where things will be in 5 or 15 years. It will just feel less and less appealing to get an in-depth education, especially a formal one.
Which is quite ironic, considering who wrote the article.
LLMs fall victim to "garbage in, garbage out." Claude can solve open problems if you know what you're doing, but it can also incorrectly convince you it's right if you don't know what you're doing.
A PhD teaches you how to think, how to learn, and how to question the world. That's a vital set of skills no matter what tool exists.
I don’t really know how to optimize for a world where AIs would be smarter than everyone and able to do everything.
If that comes to pass, I guess there won’t be any economic cost to having done my PhD because the entire economy will be AI driven and we’ll hopefully just be their happy pets.
If that doesn’t come to pass, and AIs just remain good at summarizing and remixing ideas, I guess people with experience generating research will still be useful.
Because you may have fun working in a scientific environment and doing research.
I liked my job at the university - independent of the final PhD. I enjoyed what I was doing. Most of the time I also enjoyed writing my dissertation, since I was given the opportunity to write about my stuff. And mostly I could write it in a way how I felt things are supposed to be explained.
Why spend your life doing anything at all? I'm biased on the topic since im writing up atm, but it was, if nothing else, a very itnerseting way to spend 4 years of my life.
I find it very fulfilling to do a PhD and did so myself. More people should. What I mean is that I'm expecting the general view on it to evolve as described.
Ah. I did indeed misunderstand. Also, as I said, I've got a personal stake, right at the tale end of the PhD, looking for jobs, so I guess im feeling pretty defensive. I certainly hope the general public doesn't feel this way, but I've seen plenty of people say similar things about college degrees now, so it kind of makes sense.
C dev wasn't an issue back in the 1 GB or 256 MB or 16 MB days either. You just didn't use to have a Chrome tab open that by itself is eating 345 MB just to show a simple tutorial page.
C dev wasn't a problem with MSDOS and 640K either. With CP/M and 64K it was a challenge I think. Struggling to remember the details on that and too lazy to research it right now.
Autism is a quite strong diagnosis at the end of a spectrum. Not every tech-loving introvert is autistic. That's the kind of arrogant attitude that marginalizes nerds and on a forum like HN people really ought to know better.
As somebody who identified a lot with what's in that article I can say that I haven't just made peace with having been "different" but I love it and wouldn't want it any different comparing my life today with that of the arrogant non-nerds who made fun of us back in school.
The colloquial use of the word “autism” carries with it a specific connotation and mind image. That primarily negative stereotype is being reinforced by the joke by way of it being delivered as a medical diagnosis (“the results are back”).
Your parent comment is arguing against perpetuating the wrong negative connotations and lack of understanding of autism.
Not to say the original author was doing it maliciously, I don’t think they were.
And it's time that colloquial term is put to a rest. We've left other terms behind us which used to be thrown around mindlessly but were (are) actually hurtful, we will manage with that term too.
If we take the human brain as an example, it's pretty bad at computation. Multiply two 10-digit numbers takes forever, despite the enormous size of its neural network. It's not the right tool for the job - a few deterministic logic gates could do that much more efficiently. That same circuit can't do much else, but multiplying, oh boy, it's good at that! Why do we think that artificial neural nets would be the right tool for that job? What's wrong with letting the LLM reach out to an ALU to do the calculation, just like a human would do? It's surely going to be quicker and require less energy.
The embedded programs can be connected to the other weights during training, in whatever way the training process finds useful. It doesn't just have to be arithmetic calculation. You can put any hard-coded algorithm in there, make the weights for that algorithm static, and let the training process figure out how to connect the other trillion weights to it.
If we never try, we'll never know. I wouldn't be surprised if there is something to gain from a form of deterministic computation which is still integrated with the NN architecture. After all, tool calls have their own non-trivial overhead.
Funny that they speak so negatively about "fast fashion". If anything I would expect on-demand clothes production contribute to an _increase_ in that phenomenon, rather than the opposite.
Not at these prices :-) $150 - $200 for a sweater is not cheap. I think of fast fashion in terms of "how many times do I have to wear it to get my money's worth?" If the answer is less than the number of times I'd wear it in a year, it's fast fashion. Of course, if you're a thrift shop shopper, most fashion is fast fashion.
> But I often find that with jobs I want to give to other people, so maybe I over specify?
The difference is that with other people, you are training somebody else in your team who will eventually internalize what you taught them and then be able to carry the philosophy forward. Even if it took exactly the same amount of time for you to explain (+ code review etc), it's a clear net benefit in the long run. Not so with an LLM. There it's just lost time.
Imagine somebody writes a blog post "why I bike to work". They detail that they love it, the fresh air, nature experience biking through a forest, yes sometimes it's raining but that's just part of the experience, and they get fit along the way. You respond with "well I take the car, it's just easier". Well, good for you, but not engaging with what they wrote.
The difference is that everyone knows that it’s faster and to take the car but you get to exercise your muscles. But imagine it was 1920 when cars were still up for debate and the post was “why I ride my horse to work”. It’s still a common argument whether you’ll get better results coding manually or using AI.
> It’s still a common argument whether you’ll get better results coding manually or using AI.
Except the post has nothing to do with “better results” of the generated output, it concerns itself with the effect it has on the user’s learning. That’s the theme which is relevant to the discussion.
And we already know LLMs impact your learning. How could it not? If you don’t use your brain for a task, it gets worse at that task. We’ve know that, with studies, since before LLMs.
Did you read the post yourself? It doesn’t sound like it. It is composed of the title and three mystical-sounding quotes. How is one supposed to engage with this? Doing literary critique? A counter point to the statement “I don’t use LLMs” would probably count as valid engagement in any circumstance but especially in this one.
I did. The three quotes clearly express a shared sentiment for enjoyment of building and learning while doing so. That's certainly something one can engage with by providing a counterpoint. But just saying "that's not what I do" isn't one.
The original poster “expresses a shared sentiment” by posting three quotes, but the poster you replied to, who offers a fairly detailed account of the value LLMs bring to their daily work life, and how they feel about it, does not. OK.
The original post is a blog post that somebody put into their blog. Its purpose isn't (necesaarily) to engage into a discussion or even interact with anybody. It's the root of a discussion tree, if you will, a place to make a bold statement or just express a random thought.
In contrast, the post I replied to is a response, which by definition (and purpose of this forum) is meant to contribute to a discussion. It's an inner node of a discussion tree and thereby needs to engage with the presented argument.
So, this is an apples-vs-oranges situation, not a double-standards situation.
The irony of starting to claim that someone doesn’t engage with an “argument” (put forth by three quotes, and nothing else), and then ending up with this absolute word salad and an irrelevant metaphysical quip on the categories.
All these approaches are fundamentally flawed. If there is a possibility for a jailbreak/escape, it will be found and used. Are we really back to the virus scanner days with the continuous arms race between guard tools and rogue code? Have we not learned anything?
I understand the appeal of this tech to techies. It's so cool to automate knitting!
Though it totally misses the point of actually knitting something, with your own hands. The time it takes, the details you need to think about, the skills you work on perfecting, the quiet evening on the sofa or in a cafe with friends, chatting and knitting away, all that goes into a piece of clothing that you've knitted. Letting a machine do that is completely missing out.
I feel similarly about AI generated music. Taking the musician out of the loop misses the point of the whole thing.
This is knitting as a method of mass-production. It's not cannibalizing hobby knitters making hats and gloves for their loved ones at Christmas. The comparison to AI music doesn't work because that is trying to occupy the same space as musical artists.
Depends whether you see it as a production method or an art/recreational activity. There can be both, and don't worry, hand-made products will always have a special value. Even if everybody can order custom made knitted sweater from a machine.
Knitting by hand is for fun, with a by product of getting clothes. No one does it to make all their clothes, it’s highly impractical in this day and age.
What makes it "impractical in this day and age". My wife and her mother knitted sweaters, cardigans, scarves, hats. My wife also sewed skirts, blouses, and full length winter coats. I don't have any hand knitted skirts but I do have several that were commercially machine knitted. I'm quite sure that had my wife wanted to she could have knitted and sewn many complete suits of clothes.
Which is quite ironic, considering who wrote the article.
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