this post was submitted on 25 Feb 2024
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Don’t learn to code: Nvidia’s founder Jensen Huang advises a different career path::Don't learn to code advises Jensen Huang of Nvidia. Thanks to AI everybody will soon become a capable programmer simply using human language.

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[–] [email protected] 29 points 8 months ago (2 children)

I think this is bullshit regarding LLMs, but making and using generative tools more and more high-level and understandable for users is a good thing.

Like various visual programming means, where you sketch something working via connected blocks (like PureData for sounds), or in Matlab I think one can use such constructors to generate code for specific controllers involved in the scheme, or like LabView.

Or like HyperCard.

Not that anybody should stop learning anything. There's a niche for every way to do things.

I just like that class of programs.

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[–] [email protected] 7 points 8 months ago (16 children)

Nvidia is such a stupid fucking company. It's just slapping different designs onto TSMC chips. All our "chip companies" are like this. In the long run they are all going to get smoked. I won't tell you by whom. You shouldn't need a reminder.

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[–] [email protected] 11 points 8 months ago

Don't tell me what to do. Going to spend more time learning to code from now on, thanks.

[–] [email protected] 49 points 8 months ago

Lmao do the opposite of whatever this guy says, he only wants his 2 trillion dollar stockmarket bubble not to burst

[–] [email protected] 58 points 8 months ago (2 children)

As a developer building on top of LLMs, my advice is to learn programming architecture. There's a shit ton of work that needs to be done to get this unpredictable non deterministic tech to work safely and accurately. This is like saying get out of tech right before the Internet boom. The hardest part of programming isn't writing low level functions, it's architecting complex systems while keeping them robust, maintainable, and expandable. By the time an AI can do that, all office jobs are obsolete. AIs will be able to replace CEOs before they can replace system architects. Programmers won't go away, they'll just have less busywork to do and instead need to work at a higher level, but the complexity of those higher level requirements are about to explode and we will need LLMs to do the simpler tasks with our oversight to make sure it gets integrated correctly.

I also recommend still learning the fundamentals, just maybe not as deeply as you needed to. Knowing how things work under the hood still helps immensely with debugging and creating better more efficient architectures even at a high level.

I will say, I do know developers that specialized in algorithms who are feeling pretty lost right now, but they're perfectly capable of adapting their skills to the new paradigm, their issue is more of a personal issue of deciding what they want to do since they were passionate about algorithms.

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[–] [email protected] 37 points 8 months ago (2 children)

It's just as crazy as saying "We don't need math, because every problem can be described using human language".

In other words, that might be true as long as your problem is not complex enough to be able to be understood using human language.

You want to solve a real problem? It's way more complex with so many moving parts you can't just take LLM to solve it, because that takes an actual understanding of a problem.

[–] [email protected] 11 points 8 months ago (1 children)

Maybe more apt for me would be, “We don’t need to teach math, because we have calculators.” Like…yeah, maybe a lot of people won’t need the vast amount of domain knowledge that exists in programming, but all this stuff originates from human knowledge. If it breaks, what do you do then?

I think someone else in the thread said good programming is about the architecture (maintainable, scalable, robust, secure). Many LLMs are legit black boxes, and it takes humans to understand what’s coming out, why, is it valid.

Even if we have a fancy calculator doing things, there still needs to be people who do math and can check. I’ve worked more with analytics than LLMs, and more times than I can count, the data was bad. You have to validate before everything else, otherwise garbage in, garbage out.

It’s sounds like a poignant quote, but it also feels superficial. Like, something a smart person would say to a crowd to make them say, “Ahh!” but also doesn’t hold water long.

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[–] [email protected] 10 points 8 months ago (1 children)

Ha

If you ever write code for a living first thing you notice is that people can't explain what they need by using natural language ( which is what English, Mandarin etc is), even if they don't need to get into details.

[–] [email protected] 3 points 8 months ago

Also, natural language can be vague and confusing. Look at legalese and law statutes. "When it comes to the law, NOTHING is understood!" ‐- Dragline

[–] [email protected] 5 points 8 months ago

Funny enough we now have prompt engineering which is specifically for talking to ai.

[–] [email protected] 34 points 8 months ago (2 children)

I don't see how it would be possible to completely replace programmers. The reason we have programming languages instead of using natural language is that the latter has ambiguities. If you start having to describe your software's behaviour in natural language, then one of three things can happen:

  1. either this new natural programming language has to make assumptions about what you intend, and thus will only be capable of outputting a certain class of software (i.e. you can't actually create anything new),
  2. or you need to learn a new way of describing things unambiguously, and now you're back to programming but with a new language,
  3. or you spend forever going back and forth with the generator until it gives you the output you want, and this would take a lot longer to do than just having an experienced programmer write it.
[–] [email protected] 16 points 8 months ago

And if you don't know how to code, how do you even know if it gave you the output you want until it fails in production?

[–] [email protected] 3 points 8 months ago* (last edited 8 months ago) (1 children)

But that’s not what the article is getting at.

Here’s an honest take. Let me preface this with some credential: I’m an AI Engineer with many years in field. I’m directly working on right now multiple projects that augment and automate code generation, documentation, completion and even system design/understanding. We’re not there yet. But the pace of progress in how fast we are improving our code-AI is astounding. Exponential growth in capability and accuracy and utility.

As an anecdotal example; a few years ago I decided I would try to learn Rust (programming language), because it seemed interesting and we had a practical use case for a performant, memory-efficient compiled language. It didn’t really work out for me, tbh. I just didn’t have the time to get very fluent with it enough to be effective.

Now I’m on a project which also uses Rust. But with ChatGPT and some other models I’ve deployed (Mixtral is really good!) I was basically writing correct, effective Rust code within a week—accepted and merged to main.

I’m actively using AI code models to write code to train, fine-tune, and deploy AI code models. See where this is going? That’s exponential growth.

I honestly don’t know if I’d recommend to my young kids programming as a career now even if it has been very lucrative for me and will take me to my retirement just fine. It excites me and scares me at the same time.

[–] [email protected] 11 points 8 months ago* (last edited 8 months ago) (1 children)

There is more to a program then writing logic. Good engineers are people who understand how to interpret problems and translate the inherent lack of logic in natural language into something that machines are able to understand (or vice versa).

The models out there right now can truly accelerate the speed of that translation - but translation will still be needed.

An anecdote for an anecdote. Part of my job is maintaining a set of EKS clusters where downtime is... undesirable (five nines...). I actively use chatgpt and copilot when adjusting the code that describes the clusters - however these tools are not able to understand and explain impacts of things like upgrading the control plane. For that you need a human who can interpret the needs/hopes/desires/etc of the stakeholders.

[–] [email protected] 4 points 8 months ago (1 children)

Yeah I get it 100%. But that’s what I’m saying. I’m already working on and with models that have entire codebase level fine-tuning and understanding. The company I work at is not the first pioneer in this space. Problem understanding and interpretation— all of what you said is true— there are causal models being developed (I am aware of one team in my company doing exactly that) to address that side of software engineering.

So. I don’t think we are really disagreeing here. Yes, clearly AI models aren’t eliminating humans from software today; but I also really don’t think that day is all that far away. And there will always be need for humans to build systems that serve humans; but the way we do it is going to change so fundamentally that “learn C, learn Rust, learn Python” will all be obsolete sentiments of a bygone era.

[–] [email protected] 7 points 8 months ago

Let's be clear - current AI models are being used by poor leadership to remove bad developers (good ones don't tend to stick around). This however does place some pressure on the greater tech job market (but I'd argue no different then any other downturn we have all lived through).

That said, until the issues with being confidently incorrect are resolved (and I bet people a lot smarter then me are tackling the problem) it's nothing better then a suped up IDE. Now if you have a public resources you can point me to that can look at a meta repo full of dozens of tools and help me convert the python scripts that are wrappers of wrappers( and so on) into something sane I'm all ears.

I highly doubt we will ever get to the point where you don't need to understand how an algorithm works - and for that you need to understand core concepts like recursion and loops. As humans brains are designed for pattern recognition - that means writing a program to solve a sodoku puzzle.

[–] [email protected] 12 points 8 months ago (1 children)

It's not really about the coding, it's about the process of solving the problem. And ai is very far away from being able to do that. The language you learn to code in is probably not the one you will use much of you life. It will just get replaced by which ai you will use to code.

[–] [email protected] 13 points 8 months ago

Yep. The best guy on my team isn't the best coder. He's the best at visualizing the complete solution and seeing pinch points in his head.

[–] [email protected] 24 points 8 months ago

I can kind of see his point, but the things he is suggesting instead (biology, chemistry, finance) don't make sense for several reasons.

Besides the obvious "why couldn't AI just replace those people too" (even though it may take an extra few years), there is also a question of how many people can actually have a deep enough expertise to make meaningful contributions there - if we're talking about a massive increase of the amount of people going into those fields.

[–] [email protected] 14 points 8 months ago (1 children)

There’s good money to be made in selling leather jackets.

[–] [email protected] 53 points 8 months ago* (last edited 8 months ago) (2 children)

This overglorified snake oil salesman is scared.

Anyone who understands how these models works can see plain as day we have reached peak LLM. Its enshitifying on itself and we are seeing its decline in real time with quality of generated content. Dont believe me? Go follow some senior engineers.

[–] [email protected] 12 points 8 months ago (1 children)

Why do you think we've reached peak LLM? There are so many areas with room for improvement

[–] [email protected] 0 points 8 months ago* (last edited 8 months ago)

You asked the question already answered. Pick your platform and you will find a lot of public research on the topic. Specifically for programming even more so

[–] [email protected] 20 points 8 months ago (2 children)

Any recommendations whom to follow? On Mastodon?

[–] [email protected] 0 points 8 months ago* (last edited 8 months ago)

Fediverse is sadly not as popular as we would like sorry cant help here. That said i follow some researchers blogs and a quick search should land you with some good sources depending on your field of interest

[–] [email protected] 16 points 8 months ago (1 children)

There is a reason they didn't offer specific examples. LLM can still scale by size, logical optimization, training optimization, and more importantly integration. The current implementation is reaching it's limits but pace of growth is also happening very quickly. AI reduces workload, but it is likely going to require designers and validators for a long time.

[–] [email protected] 3 points 8 months ago* (last edited 8 months ago) (4 children)

For sure evidence is mounting that model size benefit is not returning the quality expected. Its also had the larger net impact of enshitifying itself with negative feedback loops between training data, humans and back to training. This one being quantified as a large declining trend in quality. It can only get worse as privacy, IP laws and other regulations start coming into place. The growth this hype master is selling is pure fiction.

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[–] [email protected] 11 points 8 months ago* (last edited 8 months ago) (1 children)

So TIL 'prompt engineer' is now a thing. We're doomed, aren't we?

[–] [email protected] 6 points 8 months ago

Yay! Another job that's impossible to fail at for those who are already well-off.

[–] [email protected] 27 points 8 months ago (1 children)

Jensen fucking Huang is a piece of shit and choke full of it too

Actually, AI can replace this dick at a fraction of the cost instead of replacing developers. Bring out the guillotine mfs

[–] [email protected] 19 points 8 months ago (1 children)

Your vulgarity and call to violence are quite convincing, sir. Mayhaps you moonlight as a bard?

[–] [email protected] 37 points 8 months ago

This seems as wise as Bill Gates claiming 4MB of ram is all you'll ever need back on 98 🙄

[–] [email protected] 48 points 8 months ago (1 children)

Well. That's stupid.

Large language models are amazingly useful coding tools. They help developers write code more quickly.

They are nowhere near being able to actually replace developers. They can't know when their code doesn't make sense (which is frequently). They can't know where to integrate new code into an existing application. They can't debug themselves.

Try to replace developers with an MBA using a large language model AI, and once the MBA fails, you'll be hiring developers again - if your business still exists.

Every few years, something comes along that makes bean counters who are desperate to cut costs, and scammers who are desperate for a few bucks, declare that programming is over. Code will self-write! No-code editors will replace developers! LLMs can do it all!

No. No, they can't. They're just another tool in the developer toolbox.

[–] [email protected] 12 points 8 months ago (2 children)

I've been a developer for over 20 years and when I see Autogen generate code, decide to execute that code and then fix errors by making a decision to install dependencies, I can tell you I'm concerned. LLMs are a tool, but a tool that might evolve to replace us. I expect a lot of software roles in ten years to look more like an MBA that has the ability to orchestrate AI agents to complete a task. Coding skills will still matter, but not as much as soft skills will.

[–] [email protected] 1 points 8 months ago (1 children)

Well, I sometimes see a few tools at my job, which are supposed to be kinda usable by people like that. In reality they can't 90% of time.

That'd be because many people think that engineers deal in intermediate technical details, and the general idea is clear for this MBA. In fact it's not.

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[–] [email protected] 10 points 8 months ago* (last edited 8 months ago) (5 children)

I really don't see it.

Think about a modern application. Think about the file structure, how the individual sources interrelate, how non-code assets are stored, how applications are deployed, and all the other bits and pieces that go into an application. An AI can't know any of that without being trained - by a human - on the specifics of that application's needs.

I use Copilot for my job. It's very nice, and makes my job easier. And if my boss fired me and the rest of the team and tried to do it himself, the application would be down in a day, then irrevocably destroyed in a week. Then he'd be fired, we'd be rehired, and we - unlike my now-former boss - would know things like how to revert the changes he made when he broke everything while trying to make Copilot create a whole new feature for the application.

AI code generation is pretty cool, but without the capacity to know what code actually should be generated, it's useless.

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