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AI eats the world (Spring 26) [pdf]

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Re: AI eats the world (Spring 26) [pdf]

#101

Post by nathan_compton »

zx0r23 wrote: post #42
dist-epoch wrote: post #14

It will literally eat the world. Just like we crowded out wild animals in a few reserved areas, so will AI data centers crowd us out. To quite Ilya Sutskever: > I think it’s pretty likely the entire surface of the earth will be covered with solar panels and data centers.

Or we could not do that... Technology is meant to serve us not drive us into a hellscape lol

In the current system technology is meant to serve the shareholders. That might end up serving us, if you believe the standard narrative. But maybe the shareholders will just carve out a few nature reserves for themselves and just wait for the rest of us to die off.

Re: AI eats the world (Spring 26) [pdf]

#103

Post by ern_ave »

dist-epoch wrote: post #14

It will literally eat the world. Just like we crowded out wild animals in a few reserved areas, so will AI data centers crowd us out. To quite Ilya Sutskever: > I think it’s pretty likely the entire surface of the earth will be covered with solar panels and data centers.

> AI data centers crowd us out.

Here's a test to know if this is/will be true: look for a situation where the "needs" of AI (e.g. land, electricity, etc) conflict with the needs of people (e.g. land to live on, grow food on, electricity to light our homes).

Find a place where the needs of AI conflict with people, and observe who wins out.

Does the entity that owns the datacenter say, "oh sorry! I guess we're using too much electricity. No worries! We'll stop doing that" ...or does it say, "lol too bad, all the electricity belongs to us!"

Does the entity wanting to build a datacenter say, "oh sorry! We thought you'd be okay with us using this land. But if you're not that's okay, we wont build here" ...or does it say, "lol too bad, we own the government and they're seizing the land under eminent domain!"

(both of these scenarios have happened, btw)

Re: AI eats the world (Spring 26) [pdf]

#104

Post by libraryofbabel »

zetsurin wrote: post #89
libraryofbabel wrote: post #84

Earlier quoted context omitted.

Thanks for the summary. I do love Benedict‘s work; I find he’s one of the few commentators who consistently strikes a balance between taking the transformative potential of AI seriously while not falling over into hype. Some things that stand out: * He’s really good with his historical analogies, especially looking at previous transformations like the early Internet and mobile; no surprise given that he has a history…

> for example, almost all of their predictions weren’t just wrong… in hindsight, given how the future played out, they were asking the wrong question Do you have an example of this? My (poor) memory remembers "it's going to change how people buy things", was the big deal at the time, and it seems like it was a great prediction.

Well, yes, but as the other commenter says, that’s a very broad general statement akin to something like “AI will change knowledge work“. That’s certainly true, but how? What are the details? What kind of companies are going to be the winners and what kind will be losers, or end up with commodity margins, like the telcos did after the mobile revolution? What is the pricing structure going to look like?

I suppose a concrete example in 1997 would be that a lot of companies thought the future of e-commerce was setting up a store on AOL, that people would use while sitting down at a desktop PC. Obviously it didn’t turn out quite that way. Furthermore, the Internet enabled new kinds of ways to buy things that weren’t even envisioned in the pre-Internet pre-smartphone world: think Airbnb and Uber.

Predictions are hard, especially about the future. Most predictions reflect the worldview and biases of the time in which they are made: think about all the vintage sci-fi from the 60s 70s and 80s that actually reads or looks kind of retro now. Similarly, our predictions of the future will look kind of retro and strange to someone living in the 2030s or 2040s. If studying history has any lesson to teach us, it’s really just this: that the past is an alien world with alien moods of thinking, and that our moment in time will look similarly alien to people in the future who choose to look back and analyze it closely.

This isn’t an argument that we should stop trying to make predictions. We need to, but it is an argument for humility, and also for questioning all your assumptions that you might be importing.

Re: AI eats the world (Spring 26) [pdf]

#105

Post by nkohari »

lorecore wrote: post #56
benedictevans wrote: post #52

Earlier quoted context omitted.

Nope. This is the exact quote. Crypto today has a lot in common with both the internet in 1993 and the internet in 1999. Huge potential with few of the use cases invented yet, combined with froth, scams and delusion. This makes it easier to dismiss (“useless AND a scam!”). But dismissing crypto as a useless scam is much like looking at Usenet, Cuecat and Boo .com and dismissing the internet. It mistakes applications…

Nope what? You just confirmed the OP’s point. Glad we’re all in agreement.

I don't think it's fair to consider writing an analysis (even a favorable one) about a topic as _shilling_ for it. It's not like he was pushing shitcoins or minting NFTs.

I have always been (and remain!) bearish on crypto but it absolutely was something that couldn't be ignored a few years ago. Even if you came to the conclusion that it was bunk, there was significant enough fervor that any technologist needed to reckon with their position on it.

For example, lots of engineers proclaimed very loudly that document databases would replace the RDBMs, or that GraphQL was the future of APIs. They were wrong, as it turned out, but only with the wisdom of hindsight.

Re: AI eats the world (Spring 26) [pdf]

#106

Post by aurareturn »

In slide 22, it compares LLM labs (OpenAI/Anthropic) to mobile data telecoms (AT&T, Verizon, TMobile) in 2010s. The difference is that mobile telecoms follow a standard (3G, 4G LTE, 5G) and there is little to no differentiation. It's virtually the same no matter which company you choose or which country you travel to.

A better comparison is actually AWS/Azure/Google Cloud/NeoClouds to AT&T and Verizon. The data centers follow a standard (CUDA/PyTorch/etc.) while OpenAI and Anthropic are becoming more like iOS and Android. Both the clouds and telecoms had to spend a ton of capex to build out infrastructure first.

Because of what I think is a poor comparison, the the next few slides make the wrong conclusions. For example, it thinks that models will be a commodity like 5G data. I disagree. I think frontier models are a classic duopoly/monopoly scenario. The smarter the model, the more it gets used, the more revenue it generates, the more compute the company can buy, the smarter the next model and so on. It's a flywheel effect. This is similar to advanced chip nodes like TSMC where your current node has to make enough money to pay for the next node. TSMC owns something like 95%+ of all of the most advanced node market. Back in the 80s and 90s, you had dozens of chip fab companies. Today, there are only 3. There should only be 1 but national security saved Intel and Samsung fabs.

There is evidence that the Chinese models are falling further behind, not gaining. Consolidation will likely happen soon because many unprofitable open source labs will have to merge and focus on revenue generation.

Re: AI eats the world (Spring 26) [pdf]

#107

Post by zx0r23 »

nathan_compton wrote: post #101
zx0r23 wrote: post #42

Earlier quoted context omitted.

Or we could not do that... Technology is meant to serve us not drive us into a hellscape lol

In the current system technology is meant to serve the shareholders. That might end up serving us, if you believe the standard narrative. But maybe the shareholders will just carve out a few nature reserves for themselves and just wait for the rest of us to die off.

Time for a new system then!

Re: AI eats the world (Spring 26) [pdf]

#108

Post by benedictevans »

aurareturn wrote: post #106

In slide 22, it compares LLM labs (OpenAI/Anthropic) to mobile data telecoms (AT&T, Verizon, TMobile) in 2010s. The difference is that mobile telecoms follow a standard (3G, 4G LTE, 5G) and there is little to no differentiation. It's virtually the same no matter which company you choose or which country you travel to. A better comparison is actually AWS/Azure/Google Cloud/NeoClouds to AT&T and Verizon. The data cente…

I've made the semi comparison myself, but the amount of capital required to build a SOTA model today is clearly nowhere near enough to lead to a monopoly.

I'm aware that telecoms networks are standardised (I was once a telecoms analyst), but that isn't a precondition for a commodity.

Re: AI eats the world (Spring 26) [pdf]

#109

Post by aurareturn »

benedictevans wrote: post #108
aurareturn wrote: post #106

In slide 22, it compares LLM labs (OpenAI/Anthropic) to mobile data telecoms (AT&T, Verizon, TMobile) in 2010s. The difference is that mobile telecoms follow a standard (3G, 4G LTE, 5G) and there is little to no differentiation. It's virtually the same no matter which company you choose or which country you travel to. A better comparison is actually AWS/Azure/Google Cloud/NeoClouds to AT&T and Verizon. The data cente…

I've made the semi comparison myself, but the amount of capital required to build a SOTA model today is clearly nowhere near enough to lead to a monopoly. I'm aware that telecoms networks are standardised (I was once a telecoms analyst), but that isn't a precondition for a commodity.

Just like how starting a chip fab was relatively easy back in the 80s and 90s. There were dozens of chip fab companies in the 80s.

It turns out that fabs follow Rock's Law which is that the capital cost to build a new fab doubles every 4 years. This means it will quickly get rid of the less competitive players. This is not dissimilar to the LLM scaling laws where you need a magnitude more compute to get unlock a new tier of intelligence.

Today, Anthropic and OpenAI are clearly in the lead for models and then there is everyone else. Google is a close 3rd. No one else is challenging them anymore in SOTA models. Some models might beat them in one or two benchmarks but none can compete overall. I expect this gap to grow bigger as models cost more and more to train.

Re: AI eats the world (Spring 26) [pdf]

#110

Post by lorecore »

nkohari wrote: post #105
lorecore wrote: post #56

Earlier quoted context omitted.

Nope what? You just confirmed the OP’s point. Glad we’re all in agreement.

I don't think it's fair to consider writing an analysis (even a favorable one) about a topic as _shilling_ for it. It's not like he was pushing shitcoins or minting NFTs. I have always been (and remain!) bearish on crypto but it absolutely was something that couldn't be ignored a few years ago. Even if you came to the conclusion that it was bunk, there was significant enough fervor that any technologist needed to rec…

He actually was pushing NFTs but has since deleted his tweet: https://news.ycombinator.com/item?id=26434769
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