631–640 of 868 posts
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Technology and productivity have reduced more death than any redistribution
Who said redistribution? This money could be invested in universal healthcare, or into AI research for medicine. But hey, I guess replacing developers and generating slop is more beneficial to our society.
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Are you paying that, or is your work paying for it? If you’re using it for personal work, why is $100 worth it?
I’ve been a copilot and ChatGPT subscriber for probably close to two years now, give or take a couple of months, and I had a trusted friend telling me for months to give Claude a try. It took about two weeks of really running it through its paces, and constantly slamming against the limit on it to convince me I had to upgrade to at least the 100/month sub, and at this point I wouldn’t blink to bump that to the 200/mo…
Doesn’t make any sense.
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> The correction will be brutal, worse than the Industrial Revolution. Has it occurred to you that there might not be a correction, and that the outcome would still be brutal, at least on par with the industrial revolution.
It won't get that far. It's physically impossible to build out the datacenters required for the "AI is actually good and we have mass layoffs" scenario. This Anthropic investment is spurred on because they've already hit a brick wall with capacity. $40B goes a long way, but not for datacenters where nearly every single component and service is now backordered. Even if you could build the DC, the power connection won'…
The next level of layoffs is probably still 25 years out.
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Don't open models and competition between frontier providers both serve as barriers here? If a frontier provider pivoted as you describe it would certainly change the landscape but they wouldn't be unassailable without developing some sort of secret sauce that gave them an extremely large advantage over everyone else. They'd need a sufficient advantage to pull out far ahead of everyone else before others had a chance…
> If a frontier provider pivoted as you describe it would certainly change the landscape but they wouldn't be unassailable without developing some sort of secret sauce that gave them an extremely large advantage over everyone else. Integration, and mindset. AI, by its general-purpose nature, subsumes software products . Most products today try to integrate AI inside, put it in a box and use to supercharge the product…
Any of Meta’s competitors could reproduce Instagram “the software” in every meaningful detail for (let’s say) $100M.
They still don’t have Instagram the product. Reducing that outlay to a few billion tokens doesn’t change that.
I guess I’ll believe this theory when Anthropic or OpenAI rolls out a search engine with an integrated ad platform that can meaningfully compete with Google. How hard can that be?
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That boat has sailed off. Not even Google has the cash to buy a company valued at almost a trillion dollars.
Valued at a trillion by basically, no one who would actually invest anywhere close to that
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True. Regardless, (a) it's ability/desire to make such investments is still driven by stock-driven optimism and (b) these transactions' "signal" can have a similar, warping effect. In this case the transaction creates demand for Google's services and also funds anthropic's growth... which represents demands for google's services. "Loop" is an approximation of an analogy. The risk is that enough of such transactions c…
>(a) it's ability/desire to make such investments is still driven by stock-driven optimism I don't think it has much to do with the stock price at all. Current platform oligopolists fear the rise of new platforms. They want a foot in the door for strategic reasons. What could happen is that frontier labs like Anthropic and OpenAI never become platforms and turn out to be providers of a largely commoditised, low margi…
So they're selling the transformation, or the model. Or the ability to make a model. And their brand and their harness.
And it seems like the model is definitely not worth 380 billion. Models depreciate incredibly fast. There are lots of models and the other models aren't that far behind.
And it seems like the harness is not worth much as there's already open source alternatives that people claim are better.
And all these companies are paying lots of money for these AI training experts.
But I suspect that any regular Hacker News reader of 10 years dev experience could become a training expert in months if allowed to play with a load of compute and a lot of data for a bit.
Just like any of us could have become a data scientist, this stuff is not particularly hard. Random horny dudes on the internet are putting out loras and quantized models in days against the open source image models.
So what's worth 380 billion exactly? The brand?
These valuations just look really off. Not by one order of magnitude, but more like by 4 orders of magnitude. Like 380 million might be a reasonable valuation, but not billion.
What I also don't get is that it's pretty obvious to me that the Europeans should all be spinning up their own, not necessarily massive, data centers and throwing a few billion at some guys in Cambridge or Stockholm or London or Berlin to make their own AI models.
Only the French have done it.
But instead the rest seem to be trying to court Anthropic or OpenAI to build data centers. Which is just stupid politics given what's happening in the world right now.
My opinion about this is that Google see it as a way to weaken OpenAI, and few other side benefits, including the option to acquire Anthropic. And it may very well be bad news for OpenAI.
It'd be funny if Google offered 750m in stock + cash just to see what happened... :D The drama on HN alone would last for days. Twitter would implode in on itself.
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Such as?
I'll throw this out as something where it has saved literally weeks of work: debugging pathological behaviour in third-party code. Prompt example: "Today, when I did U, V, and W. I ended up with X happening. I fixed it by doing Y. The second time I tried, Z happened instead (which was the expected behaviour). Can you work out a plausible explanation for why X happened the first time and why Y fixed it? Please keep tr…
> The explanation it came back with was pretty wild. It essentially boiled down to a module not being adequately initialized before it was used the first time and then it maintained its state from then on out.
Even without knowing any of the variable values, that explanation doesn't sound wild at all to me. It sounds in fact entirely plausible, and very much like what I'd expect the right answer to sound like.
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>(a) it's ability/desire to make such investments is still driven by stock-driven optimism I don't think it has much to do with the stock price at all. Current platform oligopolists fear the rise of new platforms. They want a foot in the door for strategic reasons. What could happen is that frontier labs like Anthropic and OpenAI never become platforms and turn out to be providers of a largely commoditised, low margi…
But OpenAI/Anthropic are not selling the compute as they're buying that from Google/Amazon/etc. So they're selling the transformation, or the model. Or the ability to make a model. And their brand and their harness. And it seems like the model is definitely not worth 380 billion. Models depreciate incredibly fast. There are lots of models and the other models aren't that far behind. And it seems like the harness is n…
Whatever it is that leads to a $30bn run rate, growing >200%. Right now it's having the better model and being able to show how to use it in specific verticals.
But I suspect in the long run only platforms have high margins (and they will need margins not just revenues to justify their valuation). Are they becoming platforms? Google seems to think (or fear) that they might.