r/technology • u/CarciaNerissa • 1d ago

Artificial Intelligence Anthropic logged net loss of over $80 billion in first half of 2026

https://www.reuters.com/business/anthropic-recorded-net-loss-over-80-billion-first-half-this-year-wsj-reports-2026-10-20/
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u/Ivence 21h ago

Yeah, there's no path to profitability for them. None. They have to subsidize every user in order to keep people from fleeing in sticker shock at the actual cost to run these things.

You can't loss leader your entire fucking business model.

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u/wrgrant 11h ago

Years ago a friend of mine was working at a small company - he noticed they were selling their widgets at below the cost to produce them and pointed that out to his boss/the owner - who replied "Thats okay, we will make it up in volume" :P

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u/AckBarRs 7h ago

I mean Uber very famously did this exact strat successfully, among others

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u/sobrique 11h ago

Oh I think there is. I mean, its not a strong one, but I think there is a market niche for enterprise contracts. The kind where there's compliance, auditing, assurances around data protection, maybe model leasing to run locally, etc.

IF they can break in to 'enterprise services' I reckon it'll become just part of the 'user services packages' like provision of email, and video calls and similar.

I don't know for sure they'll manage it of course, but I think the niche exists, and that's what a lot of the AI companies are trying to land-grab.

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u/AGreasyPorkSandwich 15h ago

Unless AGI, and then all bets are off

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u/hellscape_navigator 13h ago

I'm gonna start a cult business based on "what if there was a rapture but for weirdo nerds though?"

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u/AGreasyPorkSandwich 13h ago

Im not saying its for sure going to happen, but that is the play here

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u/Virtual_Ferret6261 13h ago

It can't happen with current models. LLMs will never acheive AGI, they are stochastic prediction machines. They understand nothing and only output hallucinations, it's just most of the time the hallucination aligns with reality.

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u/AGreasyPorkSandwich 12h ago

I guess we'll see. Theres a lot of brilliant people, smarter than you and I, that are betting it can happen.

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u/atxgossiphound 11h ago

I actually have a PhD in this stuff. It can't happen with LLMs. Sure, something closer to human-style intelligence might be possible with different models, but we already know the limits of what LLMs can do.

Ignoring whether LLMs could actually achieve some poorly-defined version of AGI, everyone else on this thread pointing out that we can't afford the real costs is also correct.

Put simply: every time you ask your favorite frontier model a question, it's using roughly the same amount of energy as running the AC for a 4000 sq ft house in Houston in the summer. Small gains in efficiency will change that to a 3500 sq ft house over time, but you're still using a ton of energy.

To make matters worse, adding more parameters to the models ("hyperscaling" - how the "brilliant people" think we'll hit AGI) grows those costs fast. Doubling the number of parameters is like turning your house in Houston into a middle school in terms of energy usage.

Put more starkly in context: the human brain does the same thing with about the same amount of energy needed to run an LED lightbulb (and really a lot less, since that energy is also doing everything else to keep you alive).

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u/AGreasyPorkSandwich 11h ago

And yet, energy requirements vs compute has always and so far will continue to trend down

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u/atxgossiphound 11h ago

I addressed that in my previous response. Costs will come down, but only by small percentages. And scaling the models will wipe out any cost savings.

To go a little deeper: LLMs are one of the few compute tasks that uses processors to their fullest (they mostly do a single operation - add/multiply over and over and over). Most of the energy savings we've seen over the last few decades is for software that doesn't push processors that hard and has a lot of "idle" time where the processor can be put into a power saving mode. You can't put the processor in power saving mode when there are more numbers to run through the add/multiply unit.

The "4000 sq ft to 3500 sq ft" is meant to showcase this: improvements to add/multiply will come in small increments, but they will not be at the same scale as we've seen elsewhere and increasing the model size will use up those savings.

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u/sobrique 11h ago

Yeah. I think we will see some emergent uses of technology that are build on the same foundations - having lots of highly coupled GPU compute is an enabler for a bunch of other AI adjacent things as well. (I mean, that's a pretty fuzzy term too now of course).

I think commercially there is maybe a business model to be found.

One is 'business tooling' - plenty of businesses pay a subscription for Office, Email, Video calling, various productivity applications, etc.

I can see there being a niche for a more flexible/auditable enterprise service, which includes at least legal assurances around data exposure, for when someone inevitably uploads some sensitive company IP to it.

I can also see some second generation task specific models, that aren't general purpose like LLMs, but much more focussed on particular sectors or datasets. I mean algorithmic trading seems like one where if you could make an AI-type tool that's even slightly reliable, it'd be worth a fortune.

But some design/exploration/research tasks likewise MIGHT be able to deliver commercial value off such things.

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u/CrashB111 11h ago

Just one more Data Center bro, we're so close bro. Just another ruined small town, bro. We've nearly made our AI God, bro.