Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return • Hacker News Board

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#151

Post by danieldoesbio » Tue, Apr 21, 2026, 4:56 PM UTC

rvz wrote: post #134

Argonaut998 wrote: post #131

Does anyone feel that the jig is almost up? Surely the returns aren’t anywhere close to what investors expect with the sheer amount of cash at this point in time. Are Anthropic and OpenAI rushing to IPO for immediate cash so they can delay the inevitable? Surely this cycle of robbing Peter to pay Paul to pay John to pay Tim must end. We are only just now getting a taste of the “true cost” of these tokens. Then there…

> Open models are promising and cost a fraction of what they proprietary models cost which the big two are vulnerable to when companies start to feel the cost of tokens. Anthropic are scared of open weight models and need to fear-monger towards you to continue paying for their models. That's the whole point of their 'safety' marketing narrative, account bans, and Dario being the AI scarecrow scaremongering everyone a…

Genuine question here about the open-weight models finding the same vulnerabilities as mythos thing: is it just a matter of false negatives/positives? I’ve seen a few cases where people show other models (even opus) can find the same vulnerabilities given many passes. Is there some disadvantage to the extra passes that give the claimed Mythos performance extra value (assuming it finds them in less)?

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#152

Post by pohl » Tue, Apr 21, 2026, 4:57 PM UTC

electroly wrote: post #121

IMTDb wrote: post #106

Earlier quoted context omitted.

The problem is that at that scale, the alternative is building your own data centers. You'd probably want at least 2 in the US, 2 in Europe, 2 in Asia, maybe 1 in Africa and 1 in LATAM. So 8-10, and you need at least half of them ready "on time." What does "on time" mean? You'll need to negotiate with local authorities, some friendly, some not. Data centers aren't exactly popular neighbors these days. Then negotiate…

For AI inference you don't need to geographically distribute your data centers. Latency, throughput, and routes don't matter here. When it's 10 seconds for the first token and then a 1KB/sec streamed response, whatever is fine. You can serve Australia from the US and it'll barely matter. You can find a spot far outside populated areas with cheap power, available water, and friendly leadership, then put all of your da…

Sounds like you're betting that the performance users experience today will be the same as the performance they'll expect tomorrow. I wouldn't take that bet.

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#153

Post by hnav » Tue, Apr 21, 2026, 4:57 PM UTC

tahoeskibum wrote: post #145

shubhamjain wrote: post #11

If you think you need to spend $100B, does using a third-party cloud provider still make sense? It doesn’t matter what sweet deal Amazon is pitching—in that scenario, you’d want to own your stack. Especially in a hyper-competitive field like this, where margins are going to matter a lot soon. It feels like these hyperscalers are just raising as much as they can giving extremely rosy projections becauses these sooner…

That is why only SpaceX/X.ai has the true advantage...

maybe in the game of promising ludicrous things. There's no realistic plan to put compute in space.

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#154

Post by cma » Tue, Apr 21, 2026, 4:59 PM UTC

johnbarron wrote: post #71

cma wrote: post #10

Earlier quoted context omitted.

Everyone using Claude code on a personal subscription is default opted in to getting their data trained on. Private troves of data like are seen to potentially end up in a winner take all scenario. More data, better models, attracts more users, results in more exclusive data (what Altman calls the data flywheel).

>> Everyone using Claude code on a personal subscription is default opted in to getting their data trained on This is completely not true if you use AWS Bedrock, and applies to both your private that or in a business context. Its one of their core arguments for the service use. [1] - "...At Amazon, we don’t use your prompts and outputs to train or improve the underlying models in Amazon Bedrock and SageMaker JumpStar…

I'm talking about the subsidized subscription plans.

The data isn't the sole point of them, they also are about bringing in users that will encourage the product use in companies and ultimately drive more profitable API adoption within their orgs, and just general diffuse mindshare doing the same.

You can still opt out (except with Google's offering which disables lots of features if you opt out of training).

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#155

Post by IshKebab » Tue, Apr 21, 2026, 5:01 PM UTC

Argonaut998 wrote: post #131

Does anyone feel that the jig is almost up? Surely the returns aren’t anywhere close to what investors expect with the sheer amount of cash at this point in time. Are Anthropic and OpenAI rushing to IPO for immediate cash so they can delay the inevitable? Surely this cycle of robbing Peter to pay Paul to pay John to pay Tim must end. We are only just now getting a taste of the “true cost” of these tokens. Then there…

Doubtful. Look at how long Uber and Tesla have lasted despite making huge losses. Hell even Magic Leap somehow still exists (I guess because they don't have running costs beyond salaries).

I think this can keep going for at least another 5 years.

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#156

Post by empath75 » Tue, Apr 21, 2026, 5:01 PM UTC

iot_devs wrote: post #7

Someone can explain to me what's the expectations for these AI labs? I mostly see their products as commodity at this point, with strong open source contenders. Eventually it will become hard to justify the premium on these models.

> I mostly see their products as commodity at this point, with strong open source contenders.

I have seen this argument made a lot, but llm serving being a commodity makes it _better_ for them not worse.

If it's a commodity, then you are entirely competing on price, and the players that will win on price will be the largest ones, because they can find efficiencies that smaller competitors won't have.

It's actually the small LLM companies that are in trouble if LLM serving commoditizes. They will need to distinguish themselves on features, because they can't compete on price. And even there the big labs will have an advantage.

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#157

Post by infecto » Tue, Apr 21, 2026, 5:03 PM UTC

Argonaut998 wrote: post #131

Does anyone feel that the jig is almost up? Surely the returns aren’t anywhere close to what investors expect with the sheer amount of cash at this point in time. Are Anthropic and OpenAI rushing to IPO for immediate cash so they can delay the inevitable? Surely this cycle of robbing Peter to pay Paul to pay John to pay Tim must end. We are only just now getting a taste of the “true cost” of these tokens. Then there…

I am not sure how grounded this is in reality. Fortune 500s that were not already testing the waters with companies like Anthropic are rushing to figure out governance and how to use these tools across their orgs.

Has there been a ton of hype? Absolutely but the value proposition is getting more and more tangible.

Did some of the AI companies over commit in spending? I am sure and they will probably hurt in the long term. I thought Anthropic had been scaling towards profitability at a quick timeline though.

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#158

Post by electroly » Tue, Apr 21, 2026, 5:05 PM UTC

CuriouslyC wrote: post #147

TSiege wrote: post #124

Earlier quoted context omitted.

latency absolutely matters? this is such a weird thing to say. for training sure, but customers absolutely want low latency

The only AI use case that cares about latency is interactive voice agents, where you ideally want <200ms response time, and 100ms of network latency kills that. For coding and batch job agents anything under 1s isn't going to matter to the user.

tbh, that's a good point about the voice agents that I hadn't considered. I guess there are some latency-sensitive inference workloads. Thanks for pointing that out.

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#159

Post by empath75 » Tue, Apr 21, 2026, 5:06 PM UTC

loveparade wrote: post #29

iot_devs wrote: post #7

Someone can explain to me what's the expectations for these AI labs? I mostly see their products as commodity at this point, with strong open source contenders. Eventually it will become hard to justify the premium on these models.

I give it one to two more years before open source models have fully caught up. Products are commodities and models are commodities too. GPUs cores are still hard to get for inference at scale right now. They need a platform with lock in but unsure what that would look like and why it wouldn't be based on open source models.

What is the transition state where people start using open source models that you imagine actually happening?

Play out a scenario. An open source model is released that is capable as Mythos. Presumably it requires hardware big enough that running it at home is unfeasible. You are imagining that individuals can run it in the cloud themselves for cheaper than api tokens would cost? Or even small companies? And that Anthropic and OpenAI won't be able to cut costs deeper than their competitors while staying profitable?

If it is fundamentally a commodity, that means "running it yourself" also isn't really interesting as a proposition. Many of the world's biggest companies sell commodities. It's a great business to be in if you can sell them cheaper than anyone else.

The value add here isn't the model, it is "having a bunch of compute and using it more efficiently than anyone else".

Re: Anthropic takes $5B from Amazon and pledges $100B in cloud spending in return

#160

Post by electroly » Tue, Apr 21, 2026, 5:06 PM UTC

pohl wrote: post #152

electroly wrote: post #121

Earlier quoted context omitted.

For AI inference you don't need to geographically distribute your data centers. Latency, throughput, and routes don't matter here. When it's 10 seconds for the first token and then a 1KB/sec streamed response, whatever is fine. You can serve Australia from the US and it'll barely matter. You can find a spot far outside populated areas with cheap power, available water, and friendly leadership, then put all of your da…

Sounds like you're betting that the performance users experience today will be the same as the performance they'll expect tomorrow. I wouldn't take that bet.

You mean that if you were Anthropic, you'd build the data centers on every continent? Can you explain your reasoning?

We're talking about billions of dollars of extra capex if you take the "let's build them everywhere" side of the bet instead of "let's build them in the cheapest possible place" side. It seems to me that you'd have to be really sure that you need the data center to be somewhere uneconomical. I think if you did build them in the cheap place, it's a safe bet that you'll always have at least enough latency-insensitive workloads to fill it up. I doubt that we would transition entirely to latency-sensitive workloads in the future, and that's what would have to happen for my side of the bet to go wrong. The other side goes wrong if we don't see a dramatic uptick in latency-sensitive inference workloads. As another comment pointed out, voice agents are the one genuinely latency-sensitive cloud inference workload we have right now; they do need low latency for it. Such workloads exist, but it's a slim percentage so far.

I believe I'm taking the safe bet that lets Anthropic make hay while the sun shines without risking a major misstep. Nothing stops them from using their own data centers for cheap slow "base load" while still using cloud partners for less common specialized needs. I just can't see why they would build the international data centers to reduce cloud partner costs on latency-sensitive workloads before those workloads actually show up in significant numbers.