> Honestly, I like it. It reminds me of the culture I'd find amongst my Chinese peers in the 2000s and 2010s when they built China.

I dont like it. It might have built china but this isnt what built modern america. I dont think this focus on personal achievement, rather than slowing down and doing societal good is conducive to creating new technologies. Its hard to monetize new technologies, so if your in it to make the number go up, then youll just copy and optimize what already exists. You need to want to help people to make new things

Fucking MBAs

Most of the leaders of big tech are (former) engineers

Wait how does it establish collaboration? Because its opensource so anyone can copy the source code? If so, thats a pretty weak, and disengenuous argument. Is the US collaborating with russia because russians can use the internet and darpa funded its initial RnD?

Euro-Office codebase will, obviously, not diverge significantly from the original product. If they planned fundamental changes, they would have started from scratch because taking over a huge project and rewriting its basis is an ever more daunting undertaking.

As such, any future patches to both codebases should be trivial to copy from one another, which essentially makes it collaboration.

This is a very interesting thought. We complain about having to fix some MBAs vibecpded slop, but it actually might be faster, easier, and alot less painful than getting them to try to explain their vision to us and implement what they have in mind.

Like they actually iterate on the UX alot when they are vibecoding things up, answer alot of questions that can onky be answered when you see an initial version of experience and realize something is off. Id rather they waste the clankers time with that than mine

Have my angry upvote. :-)

One of my faults is "When somebody tries to explain something I hear 'A' and everyone else in the room hears 'B'". And vice-versa. But if someone can iterate a very VERY rough cut of what they want and hand it off to a design / development team ... well ... damn. That might make everyone's life a lot easier.

You are right, but at the same time, if no UX designer is involved in the loop, what happens when they've prompted a prototype that looks good - and therefore eludes them to think it's designed good as well? How do we convince them that we need to involve a UX designer to fix the application flow?

That's odd: all the other AI proponents on HN recently defended their decision to produce AI written code by saying the coding was never the hard part, it was the translation of business goals to a spec.

You're saying even that bit doesn't require them.

Seemed sufficient to me. They said it was a mistake and they'll be more careful not to sponsor nazis in the future

> True but it also reflects that the EU has indeed destroyed most goodwill towards it in the last decade regarding most things digital.

Not for me, my opinion of things like GDPR and forcing usbc on phones gives me the impression that the EU is holding corporations accountable and looking out for normal people.

Its been mentioned before but i feel like while alot of negative views might be organic, alot are also the result of tech companies' smear campaigns against the EU

How many do you need?

I have to agree. It is messed up that transformers can just talk, and it been pretty normalized. We are only talking about the impact they will have and whether they can do what people say they can, but we arent talking about how crazy it is that they can talk

I come back to this every so often as well. After so many years of looking at Markov chain outputs that almost looked like they made sense or chatbot systems rewriting your sentence back at you, software which can simply talk is a heady thing.

I would say that the LLM is something completly different especiayll as its not a normal algorithm but is very close to what brains do.

Ah yes, matrix multiplication is "not a normal algorithm", surely.

The matrix multilication underneath a large language model is the hardware but the data and the forming weights is not.

A quick sort sorts a list. A LLM depends on its learning data.

You train a model and then you use the model.

The LLM is still a "normal algorithm", just one with a fairly large dataset to use. Assigning the algorithm part of LLMs magical properties hinders understanding. The work needed to pick the next output token is very much a classical algorithm.

Algorithms can be based on training and/or use data just fine, too. https://arxiv.org/abs/1712.01208

(Now, the weights used, those we kinda really don't understand the same way we understand the processing, and the approach to looking for structures in weights sometimes looks more like archeology or anthropology than computer science.)

It sounds like you're trying to express some kind of "but LLMs are so much more" thought. Yes, very much, they are. It's because of the size of the data, there's interesting emergence there. They're still a normal algorithm. (And our brains aren't quite like that; biological things are much more random/chaotic and generally non-reproducible. And the data and algorithm aren't separate.)

Anthropic has a blog article on how they analyse their LLM to understand better how the LLM is doing math and estimates.

For this they needed extra tools to do so.

This 'algorithm' of how the lLM does that, was unknown before their research.

Our brains are not that chaotic though. They have even more complexity to size for sure and the issue that its hard to look into a humans brain.

LLMs have really changed the world. I didn’t think something like then would be possible in my lifetime

It came out of nowhere. It’s all emergent. I’m convinced this is possible with just about anything given enough data. We will be seeing a near magical physical outputs LLM in the near future. It’s going to take in video and sounds and spit out physical movements that will be just as mind blowing as when 3.5 came out and it will come out of nowhere.

I can't agree enough, and I am increasingly struggling to understand why people are not grasping this. It's just a matter of sensors in the right places and compute.

sufficient telemetry + sufficient compute = AI solution to any problem

From the Universal Approximation Theorem for neural nets, we know that if we have the right training method and net architecture we can get approximate any function with a NN. Of course, that doesn't imply that we actually have a sufficient training method and net architecture for the problem at hand, but we have been able to demonstrably solve at least two engineering domains: physical world navigation (Waymo) and language (GPT). It turns out a robust enough language model is sufficient for reasoning.

Given these results, I am personally stumped to come up with a problem humans can solve now that we can't solve with a computer given the correct telemetry and sufficient compute.

if youve ever seen a pile of wrinkly mush and wondered.. pretty damn crazy too

https://web.mit.edu/people/dpolicar/writing/prose/text/think...

But whats the problem woth using DNS internally? Given the system is already present, and moving away fron it would be effort. Seems like a nitpick

Its not teaching. These people cant pass a the class. They never went through the friction needed to learn

It depends how you use it. You can either get it to explain a concept, or do your homework for you. Its a bit like the decision students have to make as to whether to review their material before exams or go out partying.

Overall it just seems like a huge waste of money to piss away the huge tuition cost your parents probably paid.

You can use an llm to get out of doing homework but you can also use it to ask every question you would ever wanted in a 1-1 tutoring session. The problem is kids will use it to cheat on their homework. If we can’t deal with that problem then a ban is necessary. But these things can be phenomenal teachers if you use them properly.

As an educator, this is exactly what I struggle with. I'm pulling out all the stops to give students every chance to do the hard work and not lean on AI. But there's a good chunk of the class who don't listen to reason. I haven't figured it out yet. They know, logically, they can't pass an interview, but that's apparently a "tomorrow" problem.

The smart ones either use it not at all, or use it to positive effect, like you're saying.

> But there's a good chunk of the class who don't listen to reason. I haven't figured it out yet. They know, logically, they can't pass an interview, but that's apparently a "tomorrow" problem.

These people should be doing manual work, not intellectual work. There is no shortage of manual work available.