28 points•monkeydust•7 days ago•61 comments•

61 comments

igor477 days ago
I listened to this podcast and it was maddening. A few of his frames :

AI is just software, nothing new to see here.

AI safety is primarily a sandboxing problem.

There is no collective action problem, and every company should just slow down if they think they need to slow down.

There is no need for regulation because the existing incentives in the market keep companies from acting badly, which is why no company has ever done anything bad.

If something bad does happen, then we can regulate after the fact.

We will end up creating more jobs than we destroy, so don't worry about it.

Our kids might forget a whole bunch of stuff or never learn it in the first place. But don't worry, they'll come up with new things to learn instead.

The only way to get safety is to move faster because then we will more quickly arrive at safety.

Recursive self-improvement is just what we've always done.

The real danger is alarmism that might scare the public and the young people.

Nothing bad can happen, it can only good happen.

lolakutty7 days ago
>We will end up creating more jobs than we destroy, so don't worry about it.

The destroyed jobs and the persons doing them will be different from the new ones created..

>If something bad does happen, then we can regulate after the fact.

How does regulating after the fact undo the harms caused?

> they'll come up with new things to learn instead.

Like they forgot how to communicate face to face, but have learned to communicate via social media?

cush4 days ago
You’re underselling how insane he seemed. Jenson’s behavior on that podcast was completely unacceptable. So much hubris and interrupted constantly. He presented so many complete unknowns about the future as obvious and matter of fact to him. The man has completely lost his mind.
WokeUp4207 days ago
A whole bunch of fluff without any evidence to back it up.
cman14447 days ago
I unironically agree with most of these points.
greggoB7 days ago
The implication being that you only ironically agree with the rest?
xelxebar7 days ago
Happy path coding is certainly the most fun.
mkl7 days ago
I think this is overly optimistic; it assumes universities reacted instantly and pivoted to teaching coding with AI as soon as it was feasible. In actuality, university curriculums cannot change quickly, and AI capabilities are changing much faster. In my experience, some students are using AI to write code, but then have no idea what's going on. The "skill" of typing "Write a function to do [basic thing]" will not make them AI-native or help them in the workplace.
cyanydeez7 days ago
It also is naive to think, if AI is shrinking head count, that companies will seek anything other than seniors.

2008 triggered a glut of cheap experienced workers that slowly reengaged juniors but this time that the entire ladder is going to be more valuable than any grad.

zero-sharp7 days ago
I'm not sure if AI use even aligns with the purpose of the university program, which is usually understanding.
flopsamjetsam7 days ago
For CS students I agree. For non-CS students, who need programming as a way to use computers as a tool, I think they do need a solid understanding of what a computer does and what it's limitations are (and what it's capable of), but for their day jobs (once they graduate), they will most likely be getting AI to do everything for them. As long as they can reason about what's happening, to understand the results and to improve them, this seems likely to be the path in the future.
flopsamjetsam7 days ago
Some unis have: https://programsandcourses.anu.edu.au/2027/course/COMP1730

This is an introductory programming course, designed for non-CS students e.g. engineers and scientists.

> Learning outcomes

> 2. Explain key concepts in AI-assisted programming, including Large Language Models (LLMs), prompting, problem decomposition, and top-down design.

> 3. Apply the workflow of AI-assisted programming and prompt-engineering techniques to guide and improve code generated by AI assistants.

This course used to be non-AI (last year), and they rewrote recently to incorporate AI tools, as they realised the writing's on the wall for non-programmers.

It must be quite challenging to write curriculum when the underlying technology (AI) is changing so quickly.

CamperBob27 days ago
In my experience, some students are using AI to write code, but then have no idea what's going on. The "skill" of typing "Write a function to do [basic thing]" will not make them AI-native or help them in the workplace.

How many of them can read x64 or ARM assembly emitted by their compilers?

How many of them will ever need to?

There's your answer.

softfalcon7 days ago
I learned how to code assembly. Knowing it makes me a better developer.

It’s how I deeply understand what a RAM lookup vs having it already in a register means for optimization.

These are things you need to know if you want to work on high performance applications or in limited embedded systems.

So, yes, many of us need to and it’s important we keep teaching it to future students.

lolakutty7 days ago
>How many of them will ever need to?

This is a category error. LLMs are probabilistic. The ones run by an AI company over API, even more so.

Compilers are not.

archagon6 days ago
AI is not an abstraction layer. If you work entirely on the level of prompting without any knowledge or understanding of the underlying code, you are not actually an engineer, but more of a half-assed technical manager. (And your job will be first on the chopping block.)
wren69917 days ago
I don't think reading disassembly is actually that weird. I spend a lot of time doing it at work.
mikgp4 days ago
I wonder if - there are sort of broadly speaking a few different types of learners.

Jensen Huang has been CEO of NVIDIA for 33 years. That is a role with a very specific type of information environment. He is sort of this weird combination of specialist and - he necessarily has to operate within a certain level of abstraction.

I’m somewhere in the middle, I’m a high achiever but not the highest. I would say I’m above average in my usage of AI at my tech job. The way I’ve learned systems thinking is by being a bit non-specific in what I learn. British history, psychology, software engineering, queuing theory, cooking.

The idea of learning systems but not basic math - the idea of being too discerning in what I’m willing to learn. The entire idea of passing up the ability to learn something like basic math.

So many mental models of the world are developed by engaging with things like basic math. How do you learn systems without learning patterns behind numbers?

If the whole argument is something like it’s now about taste or creativity or being a builder? The way you learn those skills is engagement with all the things. It’s not abandoning all the things to read a book on systems thinking and product management.

It’s not never focus, but if your default position is “maybe I shouldn’t be curious about that”. You’re operating from a deficit.

BoggleOhYeah7 days ago
They’re all backpedaling hard on all that “AI is going to replace you” hype.
peter_d_sherman7 days ago
>"The first chip Huang worked on had 200 transistors, each of which he said he knew by name, while today’s engineers assemble systems from chips containing hundreds of trillions of them without ever working at that level. “Some of the lower-level knowledge is gone,” he acknowledged, and he later described AI as “clearly” a new abstraction level in the same progression."

Jensen gets it!

Related:

https://en.wikipedia.org/wiki/Coupling_(computer_programming...

https://en.wikipedia.org/wiki/Abstraction_layer

https://www.joelonsoftware.com/2002/11/11/the-law-of-leaky-a...

https://en.wikipedia.org/wiki/Tower_of_Babel

https://en.wikipedia.org/wiki/Prat%C4%ABtyasamutp%C4%81da

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