51–60 of 154 posts
Of course we know it. It’s been obvious since at least 2023. Everyone in AI oversells, except a few companies that built an actual business with revenue, like Midjourney. There is no AGI coming anytime soon no matter how much hype is being thrown around. We are not in the singularity. However, peak bullshit is NEAR.
I would argue we still have not even really gotten started. What do we have in the decade ahead? Robotics in every household, models 10x+ faster and more intelligent than today. Really no significant impact in life sciences, R&D, and 'offline' world / robotics today as of yet, which is where most of the value will live.
Robotics in the household has been the realm of science fiction for decades and it still hasn't happened. We get dedicated, compact machines like dishwashers and washing machine/dryers, that's it. Most recent innovation has been the automatic vacuum. If you want someone else to do household chores, hire someone. You can pay someone to do your house chores for years for the cost that these things will have initially.
Wasnt AI science fiction (research) for decades but just took couple of years after Chatgpt to become mainstream. Why do you that wont happen to robotics?
Outside a relatively small world of circular investment and FOMO feeding FOMO the general consensus seems to be “let it burn.” It appears very unlikely we will ever see an IPO of OpenAI. Anthropic appears less doomed, but still iffy at best. Tons of other large, but little discussed, AI startups are just dead-companies-walking at this point. The likes of AWS are showing good headline numbers but are taking out massiv…
> infrastructure that looks increasingly unneeded This is the crux that needs to be substantiated. Without substantiation none of your other arguments hold up.
Frankly it’s the opposite scenario (that’s there’s all this demand) which is struggling for any hard evidence.
> I caution anyone looking at API prices: they dropped the price, but is it actually less expensive? > Yeah, they dropped the price, but count the number of tokens you're tossing into it and see if it's actually cheaper. It's good for marketing, but the rub is how much you're actually using. The level of discourse is so horrible now, I don't have words. Are these the ones making predictions on AI bubble?
Of course, the price of tokens going down makes it cheaper. You can now afford to throw millions of tokens at solving a problem that would have been impossible for AI to solve at all a year ago for any price. People completely lack imagination about this stuff. The main problem right now with AI isn't even AI successfully producing code at a reasonable cost, it's human coordination and review that is the bottleneck.
Cost isn't just token price though - it's (number-of-tokens-used x price-per-token), and there are large differences in token efficiency between different models and harnesses. Increasingly we're seeing benchmark sites focusing on "cost per completed task" as a cost metric, and it's not always the cheapest tokens that win.
I agree that ultimately AI/coding cost is just part of the picture - at the end of the day it's about software development cost, which for time being involves humans.
I would argue we still have not even really gotten started. What do we have in the decade ahead? Robotics in every household, models 10x+ faster and more intelligent than today. Really no significant impact in life sciences, R&D, and 'offline' world / robotics today as of yet, which is where most of the value will live.
We see a similar paradigm with lots of revolutionary technology. The initial promise is high, people get very excited, lots of money pours in, and.... 15-30 years go by before we start seeing real impact across the economy at large.
It's just a real slog to actually implement and roll out new tech.
So take robots: I can promise you that you won't see robotics in every household in the next decade (especially so if we exclude the current market of robot vacuums). Even if a company makes an incredibly capable robot "today" (and to be clear - they are not) it won't have time to scale out production, reduce costs, generate a used market that's accessible to less wealthy consumers, deal with regulatory hurdles and quality problems that only pop up in real-world usage, etc...
It's just slower than you're implying.
The change very well will happen (I'm inclined to agree that things are going to shift). That doesn't mean that the current investment is sane and will pay off.
So many historical examples of this, just two here real quick:
- Ford built his first automobile in 1896, founded a company in 1901, went out of business, got sued by ALAM, didn't build more than 10k Model T's until 1910, then only finally hit real scale (of low hundred of thousands of units) in 1913: More than a decade to "basic scale". Household ownership didn't hit 60% until 1929... 30+ years later.
- The initial web enthusiasm, followed by the dot-com crash in early 2000s...
Earlier quoted context omitted.
Robotics in the household has been the realm of science fiction for decades and it still hasn't happened. We get dedicated, compact machines like dishwashers and washing machine/dryers, that's it. Most recent innovation has been the automatic vacuum. If you want someone else to do household chores, hire someone. You can pay someone to do your house chores for years for the cost that these things will have initially.
The cost of a timeshare robot will come down first, so you'll be hiring a robot before you own one. But that might not take so long to occur as you imagine.
Earlier quoted context omitted.
I expect Nvidia to survive the crash on its own, and everyone else except Softbank to be bailed out with US taxpayer money.
Nvidia has hordes of raucous gamers on the prowl waiting to tear their chips out of their hands the moment hyperscaler demand falters; plus, China has made sure there will always be plenty of open models to run for hobbyists and neoclouds, even if training compute were to drop off a cliff. They'll be just fine.
I saw it put quite well in a comment on reddit:
> In 2020, the gaming segment was 47% of revenue at around 8 billion. Today it's doubled to 16 billion, or 7% of revenue. That's right, data center went from 6 billion 2020 to around 198 billion today.
Even if gaming revenue doubles again when the AI bubble pops, their total revenue will still drop by something like 80%. I'm neither smart nor dumb enough to be confident about whether that's something Nvidia can survive.
There is something I have been pondering recently. If we compare the cost of AI subscriptions (let's say Claude's 100/month) to a median developer salary (let's say 100k/year to 200k/year), the difference is orders of magnitude. This fills like a gap that needs to close. I suspect llms are too cheap right now but will raise their prices to a point where only big companies will be able to afford subscriptions to use t…
> 100k/year to 200k/year Is this range just Silicon Valley or what is this? Even including just Europe, you're looking at a lower bracket of 10k. If you expand to the rest of the world... Or do you think rich cities in the USA, where developers make 100k+ per year, can alone sustain this industry?
€57-114k p.a. is well within the order of magnitude of yearly gross developer salaries in Western Europe (e.g. Germany).
Earlier quoted context omitted.
> infrastructure that looks increasingly unneeded This is the crux that needs to be substantiated. Without substantiation none of your other arguments hold up.
Are you saying people haven’t been throwing unneeded GPU capacity on the market? That is happening. Frankly it’s the opposite scenario (that’s there’s all this demand) which is struggling for any hard evidence.
I would argue we still have not even really gotten started. What do we have in the decade ahead? Robotics in every household, models 10x+ faster and more intelligent than today. Really no significant impact in life sciences, R&D, and 'offline' world / robotics today as of yet, which is where most of the value will live.