Here is the fundamental issue. We use the word "intelligence" for different things. Can you follow a recipe for making sour dough bread? Pretty easy. Can you make sour dough bread? Not so easy. Does following a recipe require "intelligence"? Yes. If something can follow a recipe can it also make bread? Not necessarily.
And another question, perhaps the most important. Can you determine that a recipe is flawed? In immediate terms, if I tell you to feed your sour dough starter every day, can you determine why, how or if that might be bad advice?
My conjecture is that there are at least three types of intelligence, as outlined above. And you have to remember that AI is by definition "artificial". Not in the sense of being unnatural but in the sense of artificial sour dough bread. It is not the real thing. (at least for two out of the three definitions of intelligence).
This is not to argue that AI is not useful and extremely beneficial in some contexts. Unfortunately our whole system of education has trained us to be "follow the recipe" kind of people. Uh Oh! So if your only skill and ability is to follow recipes, you might want to focus on developing your other kinds of intelligence.
I think 'expertise' is a bit of a red herring when what is being discussed is experience.
I've always believed that coding and development is an art and something analogous is the experience of a visual arts student. There's a level of experience required when one applies to an art school. The student builds a portfolio of passion projects and demonstrates a passion and skill along with creativity and other beneficial traits. If they are accepted, they learn the deeper theory, techniques, and more that will aide them in their career. This increases their exposure and overall experience.
Experience for a young developer is going to start with passion projects and be supplemented and bolstered through education in a similar way. You can take shortcuts as an arts student or a developer but you really just end up hurting yourself.
Sorry for the off-topic comment, but what happened to the front page? At the time I’m writing this, 11/30 submissions are related to AI. Maybe my comment is cliché too, but I’m honestly tired of all the AI stuff.
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
Welcome to the next wave blogspam campaign for LLMs. Plenty of popular HN blogs have gotten good notoriety by writing about LLMs even if the content is a nothingburger. Now everyone is jumping on that trend to try to continue to normalize it.
Part 1 was flood with AI content. Now Part 2 is walk back bold claims made in Part 1 (call it a fast moving landscape) and have the evangelists flood with AI content. Extra points if you can wax on something and try to redefine it as a pro for LLMs. “What is expertise? Did you have it before? Well now it’s faster with LLMs! Forget about all the efficiency claims, expertise is the real benefit you get with statistically incorrect LLMs.”
Actually - to disillusion yourself from AI, try dabbling into something you do not know. Try writing a production quality 3D engine. Trust me, a 3D engine has its own domain knowledge besides just graphics. No, seriously. And then see how helpless you feel when you yourself do not have the expertise to judge whether the direction being taken is the right or wrong.
At that time, you wish if there were some pipe through which you could reach John Carmack, Tim Sweeney, Gabe Nawell, Jonathan Blow some Casey Muratori and just ask one thing:
Sir, is this really the right direction?
These tools feel good when you yourself are a domain expert. I have written backend systems and designed REST APIs all my life in multiple languages in Java, Python, Go, Ruby for multiple verticals I'd say I am damn expert at API design including all the layers that go under it and I can confidently give a shut up call to an LLM knowing what I know.
Fuck the bean counters and the greedy parasite execs and VPs. Hug a junior today, society will need them tomorrow because I was a clueless junior once and my seniors were very kind to me that I am able to put bread for my family on the table.
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".
What’s built with all that VC money is already built though; I don’t foresee a future a few years out where we don’t have access to an open-source model roughly as good as the current flagship models for the cost of the compute itself.
Variable costs - electricity etc. Current model is very resource intensive. You know when they build all those Olympic Venues and then once the Olympics is done the ongoing cost is too expensive and then they become derelict buildings.... like that...
I think that the universities have an opportunity here to be the places where manual code is written so that juniors can gain the coding expertise necessary to become effective with AI.
Many universities are not set up to take advantage of this opportunity because they lean heavily into theory and look down on coding, but some departments will make the pivot well. I hope that ours (Montana State) is one of them.
The argument for universities to be a place to learn to think critically and not learn specific skills is an even stronger value prop in an era where useful skills likely change rapidly.
There needs to be a realization of how important communication skills are to develop and possess. The act of disagreement has skill levels that do not trigger emotional responses, and cause cross understanding to occur. Learning how to convey understanding and gain understanding from others becomes more and more important in a landscape of rapid change. Which we are collectively terrible at, with most companies being miscommunication circuses, with all the stress that generates, needlessly.
The problem is that professors say "learn to think critically", then actually just want the students to learn to sound like them, and agree with them. Actual critical thought has been on the decline for some time.
This is especially true in the humanities and the social sciences. Where truth is hard to ascertain, and therefore it is easier to substitute political correctness for critical thought.
Some will probably dismiss your comment as partisan but it is very hard to (honestly) argue that this isn’t the case. “Think critically…” but only about the cliché punching bags of academia: capitalism, Western culture, American foreign policy, The Patriarchy, etc. I didn’t witness any college classes that encouraged us to think critically about socialism, or think critically about Islam, or think critically about non-Western countries’ foreign policy aims, or think critically about third-wave feminism’s impact on society. Instead, even questioning any of those sacred cows usually brands you as “far right” and professors sometimes even get fired for making others “feel unsafe” if they even try.
Note: you can still be an avowed and serious leftist and have my respect if you allow your ideas to be questioned, hold yourself to a standard of proof, and tolerate dissent. What I’m criticizing is the way especially in universities, people jump right to “You’re a Nazi/fascist and the only acceptable response is to shut you down and eject you from the community” if someone doesn’t embrace all the same political dogma as you.
so universities become trade schools? one concern is where does one get theoretical knowledge required for e.g. going to graduate school and then doing research to push the state of the art. that's one of the reasons universities emphasize theory: it's seen as the first step on the academic ladder, not as a trade school
I hear you, there certainly is a huge value in understanding the theory, including in computer science. I don’t mean to put words in someone else’s mouth, but I think perhaps in the future, writing code yourself, unaided by any AI, may be thought of as more of an exercise in theory than a practical skill in its own right. Kind of like doing math “by hand” is absolutely key for someone in college to study math, whereas after graduation in a job outside of academia, the same person would have every reason to avail themselves of software that automates the same thing.
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.
The majority of undergrads are at university because a degree is the qualification they need to get a job. They are not there as the first step on a path to grad school and a Ph.D. and a lifetime of deep expertise, teaching, and learning in a field that they are passionate about.
So, yes. Universities are trade schools for the white collar world. Have been for quite a while. Never mind that most companies could spend 2-4 years running high school grads through an apprenticeship type of program and probably come out with better results.
At some point we will have to stop treating universities as tests to pass, and actually what they claim to be: places to learn. Ultimately it needs to be on the student to want to learn.
Obviously this would be easier if our entire school system before university wasn't seemingly designed too destroy every last ounce of a child's curiosity.
I don't understand why so many people think that true expertise would become less valuable in the age of AI. How would a non-technical person, who doesn't know the difference between HTTP and HTTPS, have what it takes to build anything serious? I mean, how would you even know to ask the AI for everything that your system needs to be doing, without understanding the concepts?
> And yet, OpenAI, Anthropic, and many top companies continue to compete fiercely for junior talent.
Are they? I would imagine they have the luxury to pick the brightest candidates, and set them to work on jobs for which their models don't have training data for, such as developing new models. Not writing React code.
Here is the fundamental issue. We use the word "intelligence" for different things. Can you follow a recipe for making sour dough bread? Pretty easy. Can you make sour dough bread? Not so easy. Does following a recipe require "intelligence"? Yes. If something can follow a recipe can it also make bread? Not necessarily.
And another question, perhaps the most important. Can you determine that a recipe is flawed? In immediate terms, if I tell you to feed your sour dough starter every day, can you determine why, how or if that might be bad advice?
My conjecture is that there are at least three types of intelligence, as outlined above. And you have to remember that AI is by definition "artificial". Not in the sense of being unnatural but in the sense of artificial sour dough bread. It is not the real thing. (at least for two out of the three definitions of intelligence).
This is not to argue that AI is not useful and extremely beneficial in some contexts. Unfortunately our whole system of education has trained us to be "follow the recipe" kind of people. Uh Oh! So if your only skill and ability is to follow recipes, you might want to focus on developing your other kinds of intelligence.
I think 'expertise' is a bit of a red herring when what is being discussed is experience.
I've always believed that coding and development is an art and something analogous is the experience of a visual arts student. There's a level of experience required when one applies to an art school. The student builds a portfolio of passion projects and demonstrates a passion and skill along with creativity and other beneficial traits. If they are accepted, they learn the deeper theory, techniques, and more that will aide them in their career. This increases their exposure and overall experience.
Experience for a young developer is going to start with passion projects and be supplemented and bolstered through education in a similar way. You can take shortcuts as an arts student or a developer but you really just end up hurting yourself.
Sorry for the off-topic comment, but what happened to the front page? At the time I’m writing this, 11/30 submissions are related to AI. Maybe my comment is cliché too, but I’m honestly tired of all the AI stuff.
Even worse it that it's the same few talking points repeated over, and over, and over again - re-spun with AI
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
I don't think you can ignore it. It's the biggest change to tech in 30 years I'd say.
"I'm tired of all this internet talk" in 1990s?
5 years ago it was web3. 5 years before that it was Haskell and monads. It’s how things work
because this is a billboard for YC companies and YC cultural psyops, this isn't an organic forum
Been away for a while? It's been like this for at least a year.
Welcome to the next wave blogspam campaign for LLMs. Plenty of popular HN blogs have gotten good notoriety by writing about LLMs even if the content is a nothingburger. Now everyone is jumping on that trend to try to continue to normalize it.
Part 1 was flood with AI content. Now Part 2 is walk back bold claims made in Part 1 (call it a fast moving landscape) and have the evangelists flood with AI content. Extra points if you can wax on something and try to redefine it as a pro for LLMs. “What is expertise? Did you have it before? Well now it’s faster with LLMs! Forget about all the efficiency claims, expertise is the real benefit you get with statistically incorrect LLMs.”
Personalization would solve that.
Ironically, AI can solve it too.
It's polluting the world, gobbling up hardware, and making us dumber. And HN and LinkedIn just can't get enough.
People say AI is the new internet. I say AI is the new tobacco.
Honestly, at this point it's an accurate reflection of the reality of tech.
Actually - to disillusion yourself from AI, try dabbling into something you do not know. Try writing a production quality 3D engine. Trust me, a 3D engine has its own domain knowledge besides just graphics. No, seriously. And then see how helpless you feel when you yourself do not have the expertise to judge whether the direction being taken is the right or wrong.
At that time, you wish if there were some pipe through which you could reach John Carmack, Tim Sweeney, Gabe Nawell, Jonathan Blow some Casey Muratori and just ask one thing:
Sir, is this really the right direction?
These tools feel good when you yourself are a domain expert. I have written backend systems and designed REST APIs all my life in multiple languages in Java, Python, Go, Ruby for multiple verticals I'd say I am damn expert at API design including all the layers that go under it and I can confidently give a shut up call to an LLM knowing what I know.
Fuck the bean counters and the greedy parasite execs and VPs. Hug a junior today, society will need them tomorrow because I was a clueless junior once and my seniors were very kind to me that I am able to put bread for my family on the table.
> Try writing a production quality 3D engine.
Actually I tried that and you are correct about this.
With Claude it took me hundreds of iterations and I'm still not happy.
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".
AI is cheap right now. Let's re-ask this question when it's priced to recover profit and ROI.
What’s built with all that VC money is already built though; I don’t foresee a future a few years out where we don’t have access to an open-source model roughly as good as the current flagship models for the cost of the compute itself.
Variable costs - electricity etc. Current model is very resource intensive. You know when they build all those Olympic Venues and then once the Olympics is done the ongoing cost is too expensive and then they become derelict buildings.... like that...
AI compresses the time to acquire expertise.
A high schooler can become an expert very quickly with AI, that used to require years and years of education and experience.
but the real expertise still will be to translate real world problems to technical solutions and iterate on design.
not really sure how you're imagining AI sidesteps education and experience
I think that the universities have an opportunity here to be the places where manual code is written so that juniors can gain the coding expertise necessary to become effective with AI.
Many universities are not set up to take advantage of this opportunity because they lean heavily into theory and look down on coding, but some departments will make the pivot well. I hope that ours (Montana State) is one of them.
The argument for universities to be a place to learn to think critically and not learn specific skills is an even stronger value prop in an era where useful skills likely change rapidly.
There needs to be a realization of how important communication skills are to develop and possess. The act of disagreement has skill levels that do not trigger emotional responses, and cause cross understanding to occur. Learning how to convey understanding and gain understanding from others becomes more and more important in a landscape of rapid change. Which we are collectively terrible at, with most companies being miscommunication circuses, with all the stress that generates, needlessly.
The problem is that professors say "learn to think critically", then actually just want the students to learn to sound like them, and agree with them. Actual critical thought has been on the decline for some time.
This is especially true in the humanities and the social sciences. Where truth is hard to ascertain, and therefore it is easier to substitute political correctness for critical thought.
Some will probably dismiss your comment as partisan but it is very hard to (honestly) argue that this isn’t the case. “Think critically…” but only about the cliché punching bags of academia: capitalism, Western culture, American foreign policy, The Patriarchy, etc. I didn’t witness any college classes that encouraged us to think critically about socialism, or think critically about Islam, or think critically about non-Western countries’ foreign policy aims, or think critically about third-wave feminism’s impact on society. Instead, even questioning any of those sacred cows usually brands you as “far right” and professors sometimes even get fired for making others “feel unsafe” if they even try.
Note: you can still be an avowed and serious leftist and have my respect if you allow your ideas to be questioned, hold yourself to a standard of proof, and tolerate dissent. What I’m criticizing is the way especially in universities, people jump right to “You’re a Nazi/fascist and the only acceptable response is to shut you down and eject you from the community” if someone doesn’t embrace all the same political dogma as you.
so universities become trade schools? one concern is where does one get theoretical knowledge required for e.g. going to graduate school and then doing research to push the state of the art. that's one of the reasons universities emphasize theory: it's seen as the first step on the academic ladder, not as a trade school
I hear you, there certainly is a huge value in understanding the theory, including in computer science. I don’t mean to put words in someone else’s mouth, but I think perhaps in the future, writing code yourself, unaided by any AI, may be thought of as more of an exercise in theory than a practical skill in its own right. Kind of like doing math “by hand” is absolutely key for someone in college to study math, whereas after graduation in a job outside of academia, the same person would have every reason to avail themselves of software that automates the same thing.
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.
The majority of undergrads are at university because a degree is the qualification they need to get a job. They are not there as the first step on a path to grad school and a Ph.D. and a lifetime of deep expertise, teaching, and learning in a field that they are passionate about.
So, yes. Universities are trade schools for the white collar world. Have been for quite a while. Never mind that most companies could spend 2-4 years running high school grads through an apprenticeship type of program and probably come out with better results.
Universities became trade schools as soon as the first company listed "college degree" as a job requirement.
They don't know it yet but universities have a role to curate training data, so we can have trustable models.
Agreed, but I can immediately see how painful it will be to monitor whether the work is actually done by the student.
At some point we will have to stop treating universities as tests to pass, and actually what they claim to be: places to learn. Ultimately it needs to be on the student to want to learn.
Obviously this would be easier if our entire school system before university wasn't seemingly designed too destroy every last ounce of a child's curiosity.
hiring top junior talent is more competitive than it's ever been!
I don't understand why so many people think that true expertise would become less valuable in the age of AI. How would a non-technical person, who doesn't know the difference between HTTP and HTTPS, have what it takes to build anything serious? I mean, how would you even know to ask the AI for everything that your system needs to be doing, without understanding the concepts?
> And yet, OpenAI, Anthropic, and many top companies continue to compete fiercely for junior talent.
Are they? I would imagine they have the luxury to pick the brightest candidates, and set them to work on jobs for which their models don't have training data for, such as developing new models. Not writing React code.