211–220 of 370 posts
Apple failed in their efforts to build their own models, but they got lucky. China is doing all the R&D for free and the whole thing turned out to be unprofitable anyway.
LOL WHAT.
Actually the right framing is Apple hedged the risk by maintaining good relations with China. They did not need to take any of the risk.
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So I’ve heard this argument before but I’ve not even seen someone demonstrate HOW the numbers are “adversarial”. This is the crux of my argument: Zitron provides numbers and he provides a lot of them sourced from reliable and trustworthy sources. He provides counterarguments to numbers-sparse arguments by using even more actual, real numbers with a logical theory formed from them. This should make it rather easy to d…
Some of his numbers are rebutted all the time. It doesn't matter, because he will just ignore the rebuttals and just keep repeating the invalid or irrelevant numbers. For example, a few months ago he did some bad math with a broken spreadsheet to prove that Anthropic's ARR numbers had to be incorrect. That was quickly rebutted[0], but Zitron continued repeating the argument anyway. Just this article has a dozen insta…
Either way it looks like he didn't just "repeat the numbers". He updated them and provided more data to back them up.
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> It very well could crash the consumer hardware market as a result Tbh, I hope it does. Prices are outrageous, and I'm a firm believer in personal computing/having access to powerful hardware, privately and locally, is hugely important. On a more selfish note, I miss the days of being able to build an outrageously powerful desktop for myself for relatively cheap. For now I'm still holding onto my AM4 motherboard w/…
64 GB! you are lucky :) sitting there with 16GB, a GPU that already shows the signs of strain, and AM4 Ryzen 5 5600G. (MacBook Air M1 equivalent in single-threaded tasks.) apparently the CPU requirements slowly crept up across the line. and then there is looming AVX512. why "looming"? because at some point enough people will move to it that software will require AVX512.
Unfortunately, I don't think IBM Cloud will suffer enough for me to play Tux Racer on my very own Z17.
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> As an example I use Claude code heavily for every day development and Opus 4.8 was already good enough for my use cases and never used Fable. I think the flaw in this logic is thinking about how AI is currently used only. Yes, Opus is good enough for the task you are asking it to do, but that doesn't mean that is all you will ever need. As AI gets better and better, it will open up new use cases that require the be…
You don’t “need” any LLMs to do software development. Plenty of us were productively writing code for years before these models were released, and many of us continue to do so. The “AI” companies want to sell you hype. But you don’t “need” them - not if you’re a legit, professional programmer.
This is completely unrelated to the how useful AI is for programming or how much more efficient you can be with it.
I never said you would need AI to do things you can do today. When I said it will not be 'all you ever need', my point is that NEW uses will come that will need more powerful AI. By definition, you can't NEED a new technology to do something that is already being done, because the fact that it is being done already proves you can do it without the new tech. However, that doesn't mean the tech can't do something new that does need the tech.
For example, no one needed an airplane before they were invented. However, you do need an airplane if you want to get somewhere 6000 miles away in less than a day.
There hasn't been a single bit of technology that is 'needed' if you use your strict definition of the word, because obviously humans existed and survived before the technology existed. Being absolutely necessary is not what makes a technology persist or spread, that is an artificial bar to reach.
Some people have such a natural aversion to LLMs that they will make incoherent arguments as to why they should go away. There are plenty of legitimate concerns and critiques of LLMs, you don't need to articulate arguments that you would never make about any other piece of technology to argue against their usage.
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You were just attacking his character without backing it up? Do I not know what an ad hominem is? If that's the case, then that's embarrassing for me. Unless you're saying that your remark doesn't technically bash his character?
Yeah, you're off on what an ad hominem is. I would dispute that I attacked his character at all, but that doesn't matter: an ad hominem isn't an "attack on character", it's an argument that is predicated on an unrelated character attack. My argument here is just that Zitron says things that are wrong all the time. You could fairly rebut me by saying I didn't substantiate that argument. That's true! That doesn't make…
And I agree that he says things that are wrong much of the time, but not all the time. I also don't like him enough to care, but I do care enough to bring it up when I see multiple random attacks.
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Read a little more of what he's written before you praise him, so you don't end up looking as dumb as I did. Ed may be right about some of his claims, but he is 100% a crank, and he makes so many incoherent claims I'd say that if he's right, it's in the nature of a broken clock.
If you want to dismiss him for being hyperbolic or under estimating the usefulness of AI go for it. If you are making the case that he is full of shit, please provide some actual evidence of his main thesis that AI companies are not going about this in any sustainable way
The point isn't that his thesis is fucked, just that his analysis tends to be free with details in a way that shouldn't inspire confidence, e.g. mixing up EBIT and EBITDA.
Someone elsewhere in this thread referenced this guy [1]. His takes properly summarise the lack of care Zitron appears to display for getting detailed arguments right.
If you're deeply familiar with financial jargon, I think he's fine. But if you're not, it's easy to get whisked into woo-woo nonsense that's falsely precise due to mis-using (and in some cases, very clearly mis-understanding) core financial and economic concepts.
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Cell phones may be commodities, but iPhones are not.
Yeah, as an android user myself I switch brands all the time, but the iPhone users in my life all bought iPhones 15ish years ago and have kept doing it ever since.
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Tim Cook was probably mostly disinterested because it didn't seem like a real business opportunity. Wherever AVP fell on the VR/AR spectrum, VR (while having other opportunities) was mostly a niche for high-end gamers and AR, whatever the possibilities in some future idealized form with fashionable glasses that give you lots of information about what/who you're looking at is a long way from reality.
It was released to appease investors. Ultimately as a manager you are held accountable to your investors and the cost-benefit analysis is such that it was the right action to take.
That article is a bit incoherent. I think it is pretty clear at this point that Apple has gone all-in on being the ideal edge silicon for AI. This leverages their core competencies, requires only modest investment, and will likely pay out no matter how the AI market eventually shakes out. They are in one of the only parts of the obvious future AI market where there isn't really a fight for greenfield turf with other…
I generally agree. Xserve didn't work out for Apple and they dropped it pretty quickly--think I still have an A/UX coffee cup. Wasn't really in their DNA even if there was an argument before Linux took off. For better or worse, they're basically a client company and barely a software (OK and basically a software services) one--although they spend a fair bit on (roughly) user experience.
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Same, though the types of jobs I’m working on now require the speed I get from LLMs. If I had to take my current projects and switch to hand-coding I’d have to extend the timelines and practically add a zero to the price.
If you don't mind sharing, what types of jobs are you working on now? I haven't personally seen a speed boost from LLMs, but my experience with them suggests that they could be effective in some domains and inadequate in others. E.G., I have observed that LLM tools are inadequate for generating C++ code.
- An electrical component "synthesizer" which takes natural language specifications in (e.g. from an RFQ) and uses material data sheets and core physics calculations to design new components. (Python)
- A transcript processing pipeline which reads what happened on a call, identifies participants from the CRM, drafts structured call notes, and posts them to the CRM with the proper associations after a human-in-the-loop confirmation. Fairly complex server & web app. (Go)
- Interaction design prototypes for a family of smart devices, some with screens. Brought together as an interactive web app to see how each device behaves (vanilla JS). Each prototype generated with the help of an LLM, including 3D animated examples (Claude driving Blender).