My theory is that people run into the inevitable difficulty of math and rather than look inwards and come to the conclusion they aren't as smart, or special as they once thought, they blame "the system". It can't be that they haven't tried hard enough or aren't smart enough, it's the gated community who hides behind esoteric jargon that stops them from being successful in their mathematical studies.
They believe this despite the fact that there are a million different textbooks, all explaining the same concepts in different ways, or different branches that specify the same structures with unique methods. It's really strange when I read threads like this. I'm not the greatest at math either, but that's because it's a hard thing to be good at.
To learn math is an exercise in humility. You must struggle hard, do hundreds of problems, spend years refining your understanding, redoing proofs, finding counter examples, just to be at a good undergraduate level. Much harder than pretty much all CS classes, except maybe Theory of Computation, which is pretty much math.
Yes, that could be the case. I'm not a mathematician but I gave my fair share of struggle towards trying to understand the mathematics behind physics that I was studying. You don't need to know what a smooth manifold is to solve problems in classical mechanics, just as you don't need to know what a tensor product of vector spaces is to learn what tensors are in the context of neural networks. The former is always harder because the standard of rigor is higher, and that's because of different goals. So it could be that a person tries to look up what a tensor is, finds the mathematician's definition first, thinks "what the hell is this", then finds a simpler explanation in applied contexts and goes away with the idea that mathematicians unnecessarily complicate things, because the reason why the mathematical definition has to be so complicated escapes them.
I've never met someone who believed this who was actually able to solve simple math or physics questions given to them. Attitudes like this always feel like cope to me.
Read your original comment and disagreed, but you have changed my mind. Trump is tackling climate change response more than any other president, he's just doing it in the most psychotic way possible. Threatening sovereign nations, antagonizing Asia, etc.
I agree that Canada and the EU should've been more responsible for their own defense. Hope going forward they are and cut out the USA as much as possible.
> "work, study and live where they want on either side of the Atlantic"
Will the Canadian job market improve or suffer here? Does anyone know of any research that will determine if this would be beneficial for Canadians? Naively, I think it'll be harder to compete with Europeans for jobs.
Canada has needed more workers but is suffering from a lack of affordable($675000 average when the average family makes <$110000) housing like many places with other costs rising too. The number of housing starts has never recovered from the huge downturn around 2010.
I dont mean minimum wage. I mean skilled trades and highly educated. Who is going to build the homes we are build 1/2 to 2/4 what we did prior to 2010. Who is going to work the R&D roles when the Canadians are all working
Wage suppression can be dealt with by making the wages for visa workers higher than some formula that takes local and national averages into account
There's no labor shortage there either. Go look at the Canada trades/jobs subreddits. Go look at the experiences of new grads who can't find an entry level job that pays a decent wage. Go look at how many kids want to enter the trades but can't get anyone to take them on as an apprentice. Software developers, engineers, etc. Even people with experience are out of work for months. Skilled laborers are sitting around with nothing to do because nobody is building houses.
Why do you think any Canadian grad who is able moves to the States? If we truly had such a dire labor shortage, surely they'd be able to work here and be paid well for it?
Depends on the person, I never really had fun telling someone else what I wanted built or drawn. I've always enjoyed the process more than just the results, and having the results without the intellectual activity is boring.
For software, the increase usage of AI code makes my team move much faster, but our software isn't robust anymore and I fear that our longterm mission is being compromised by the endless slop. Favoring quick implementations that AI can make versus good implementations, and lazily relying on AI makes my teammates not develop a deep understanding of the work, which ultimately limits the solutions they can develop. YMMV.
Also, I don't understand what's funny about your image? Is it that it's bad?
It's that I asked for an SVG of a circle and it created a beautiful gradient filled animated technical diagram. I wanted something closer to <svg><circle cx="50" cy="50" r="40"/></svg>
Qwen 3.8 27B on xhigh is a delightfully weird over-achiever.
Here's another fun one: "Generate an SVG of a pelican eating caviar and drinking expensive wine in a tony SF restaurant" - it thought about that for almost an hour! SVG and thinking trace here: https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
Aside from fun with over-engineered SVGs, I'm finding the challenge of getting AI-generated code to be robust, maintainable and better quality than if I'd typed it out myself to be deeply intellectually stimulating.
> I'm finding the challenge of getting AI-generated code to be robust, maintainable and better quality than if I'd typed it out myself to be deeply intellectually stimulating.
Yea that's why I started my comment with "it depends on the person", in response to you asking what's not fun about having AIs do what you tell them. For many, coercing a tool to do something you can likely do yourself better isn't ideal, and at least for me, is just inefficient use of time (in the long run) and a headache. It also zaps the fun out of any task since now you move from searching for a good solution using your priors, to now validating that the LLM has a solution that works, even if it's not optimal. The searching for a good solution is for some, the fun part, which is eliminated by agentic coding, since that search inherently relies on you writing code and seeing what works IMO. The coding is an essential part of the thinking here. An analogy would be doing a math problem by hand versus reading the solution in a textbook. I can give concrete examples if you'd like.
For your SVG examples, I have used AI for a similar use case, the construction of 3D scenes for robotics via a text prompt and an asset catalog. I wish I could get the same richness as your SVG examples, the LLMs fail too hard on all 3D tasks given, even after spending a high amount of engineering effort on a suitable harness + tools. Also like your SVG example, it often doesn't give a realistic, or even nice output, and coercing it to do so, likely takes longer than just creating the image/3D scene yourself.
Isn't that just for data collection though? I imagine the fully trained model they're expecting to have will be able to map thoughts -> text. The data collection will naturally need to have the 2 sets in order to do self-supervised training.
Remember that a lot of people have no internal monologue, and even for those that do, it's silent most of the time. They might hope to get that, but the typical case is for there to be no text or voice to extract.
Right but if someone was given a task, internal monologue or not, there will be some brainwave pattern to map thoughts to typing, right? Otherwise, how is the person typing? For a sufficiently complex task, I don't think you can rely on reflexes alone. If I understand the data collection method they're using, they will sit someone in front of a keyboard, give them some task, and collect both what they type out and the associated collected brainwaves.
Sure, but remember the use case being discussed is interrogation. You have a tool that can collect what someone is trying to type, but they aren't trying to type.
And, my point was, there may be zero words to collect at all, because they'll tend not to be actively thinking about any words.
> But non-invasive methods are getting much better. The hardware is improving and getting cheaper, though I apologize for being vague about the particularities of our hardware.
The statement implies that the company has some secret hardware that can, or at least, is close to doing that. That would blow my mind, but the author seems to believe it.
They believe this despite the fact that there are a million different textbooks, all explaining the same concepts in different ways, or different branches that specify the same structures with unique methods. It's really strange when I read threads like this. I'm not the greatest at math either, but that's because it's a hard thing to be good at.
To learn math is an exercise in humility. You must struggle hard, do hundreds of problems, spend years refining your understanding, redoing proofs, finding counter examples, just to be at a good undergraduate level. Much harder than pretty much all CS classes, except maybe Theory of Computation, which is pretty much math.
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