Comment by avalys

> For the right investor base, $10B in annual losses at OpenAI could be worth $2-3B in tax shields (depending on their bracket and how the structure works). That completely changes the return calculation

I know nothing about finances at this level, so asking like a complete newbie: doesn't that just mean that instead of risking $10B they're risking $7-8B? It is a cheaper bet for sure, but doesn't look to me like a game changer when the range of the bet's outcome goes from 0 to 1000% or more.

>> For the right investor base, $10B in annual losses at OpenAI could be worth $2-3B in tax shields

So just a loss for governments, or in other words, socializing the losses.

Amazon already has not been paying any sort of income tax to the EU. There was a lawsuit in Belgium but Amazon has won that in late-2024 since they had a separate agreement in/with Luxembourg.

Speaking for EU, all big tech already not paying taxes one way or another, either using Dublin/Ireland (Google, Amazon, Microsoft, Meta, ...) and Luxembourg (Amazon & Microsoft as far as I can tell) to avoid such corporate/income taxes. Simply possible because all the earnings go back to the U.S. entity in terms of "IP rights".

None of this is how taxes work.

> OpenAI's losses might actually be attractive to certain investors from a tax perspective.

OpenAI is anyways seeking Govt Bailout for "National Security" reasons. Wow, I earlier scoffed at "Privatize Profits, Socialize Losses", but this appears to now be Standard Operating Procedure in the U.S.

https://www.citizen.org/news/openais-request-for-massive-gov...

So the U.S. Taxpayer will effectively pay for it. And not just the U.S. Taxpayer - due to USD reserve currency status, increasing U.S. debt is effectively shared by the world. Make billionaires richer, make the middle class poor. Make the poor destitute. Make the destitute dead. (All USAID cuts)

> The real question isn't "can OpenAI justify its valuation" but rather "what's the blended tax rate of its investor base?"

Was that an organic "it's not A, it's B" or synthetic?

Can you explain it in another way? What you are saying is that instead of loosing 100% they loose 70% and loosing 70% is somehow good? Or are you saying the risk adjusted returns are then 30% better on the downside than previously thought? Because if you are, I think people here are saying the risk is so high that it is a given they will fail.

Whilst that is an option, it wont cover the share price hit from the fallout, which would wipe out more than the debt as when the big domino falls, others will follow as the market panic shifts.

So kinda looking at a bank level run on tech companies if they go broke.

It’s hardly a free option, by your numbers it’d be a 20-30% discount.

Lmao this is ridiculous. If MSFT really wanted the tax benefits they should’ve just wholly acquired OAI long ago to acquire the financial synergy you speak of.

Google has several enviable, if not moats, at least redoubts. TPUs, mass infrastructure and own their own cloud services, they own delivery mechanisms on mobile (Android) and every device (Chrome). And Google and Youtube are still #1 and #2 most visited websites in the world.

I have yet to be convinced the broader population has an appetite for AI produced cinematography or videos. Independence from Nvidia is no more of a liability than dependence on electricity rates; it's not as if it's in Nvidia's interest to see one of its large customers fail. And pretty much any of the other Mag7 companies are capable of developing in-house TPUs + are already independently profitable, so Google isn't alone here.

And yes, all their competitors are making custom chips. Google is on TPU v7. absolutely nobody is going to get this right on the first try among their competitors - Google didn't.

In this case the difference between its and it’s does alter the meaning of the sentence.

On paper, Google should never have allowed the ChatGPT moment to happen ; how did a then non-profit create what was basically a better search engine than Google?

Google suffers from classic Innovator's Dilemma and need competition to refocus on what ought to be basic survival instincts. What is worse is the search users are not the customers. The customers of Google Search are the advertisers and they will always prioritise the needs of the customers and squander their moats as soon as the threat is gone.

Agreed. Even xAI's (Grok's) access to live data on x.com and millions of live video inputs from Tesla is a moat not enjoyed by OpenAI.

The TAM for video generation isn't as big as the other use cases.

Hasn't it all been scraped by other ai companies already?

Railroads carried the goods that everybody used. That’s like almost 100% in a given country.

The pace was slower indeed. It takes time to build the railroads. But at that time advancements also lasted longer. Now it is often cash grabs until the next thing. Not comparable indeed but for other reasons.

> just three years- around 900 million users on a weekly basis.

Well, I rotate about a dozen of free accounts because I don't want to send 1 cent their way, I imagine I'm not the only one. I do the same for gemini, claude and deepseek, so all in all I account for like 50 "unique" weekly users

Apparently they have about 5% of paying customers, the amount of total users is meaningless, it just tells you how much money they burn and isn't an indication of anything else.

It is beside the point, but

> I think AI will be far more impactful

is not correct IMO. Those are two very different areas. The impact of railroads on transport and everything transport-related cannot be understated. By now roads and cars have taken over much of it, and ships and airplanes are doing much more, but you have to look at the context at the time.

Paid user base or free user base? Because free user base on a very expensive product is next to meaningless.

Railroads enabled people and goods to move from one place to another much easier and faster.

AI enables people to... produce even more useless slop than before?

I thought that, too, but lately I've been using OpenCode with Claude Opus, rather than Claude Code, and have been loving it.

OpenCode has LSPs out of the box (coming to Claude Code, but not there yet), has a more extensive UI (e.g. sidebar showing pending todos), allows me to switch models mid-chat, has a desktop app (Electron-type wrapper, sure, but nevertheless, desktop; and it syncs with the TUI/web versions so you can use both at the same time), and so on.

So far I like it better, so for me that moat isn't that. The technical moat is still the superiority of the model, and others are bound to catch up there. Gemini 3 Preview is already doing better at some tasks (but frequently goes insane, sadly).

>Anthropic is building moat around theirs models with claude code, Agent SDK, containers, programmatic tool use, tool search, skills and more.

I think this is something the other big players could replicate rapidly, even simulating the exact UI, interactions, importing/exporting existing items, etc. that people are used to with claude products. I don't think this is that big of a moat in the long run. Other big players just seem to be carving up the landscape and see where they can can fit in for now, but once resource rich eyes focus on them, Anthropic's "moat" will disappear.

A GPT wrapper isn't a moat.

All those features are basically prompts in various formats, not much of a moat.

If the “moat” is not AI technology itself but merely sufficient other lines of business to deploy it well, then that’s further evidence that venture investments in AI startups will yield very poor returns.

Try “@gmail” in Gemini

I think this is a problem for Google. Most users aren't going to do that unless they're told it's possible. 99% of users are working to a mental model of AI that they learned when they first encountered ChatGPT - the idea that AI is a separate app, that they can talk to and prompt to get outputs, and that's it. They're probably starting to learn that they can select models, and use different modes, but the idea of connecting to other apps isn't something they've grokked yet (and they won't until it's very obvious).

What people see as the featureset of AI is what OpenAI is delivering, not Google. Google are going to struggle to leverage their position as custodians of everyone's data if they can't get users to break out of that way of thinking. And honestly, right now, Google are delivering lots of disparate AI interfaces (Gemini, Opal, Nano Banana, etc) which isn't really teaching users that it's all just facets of the same system.

That kind of makes it sound like AI is a feature and not a product, which supports avalys' point.

I tried it, but nothing happened. It said that it sent an email but didn't. What is supposed to happen?

Also, Google doesn't have to finance Gemini using venture capital or debt, it can use its own money.

> I don't think we've seen any groundbreaking new research or architecture since the introduction of inference time compute ("thinking") in late 2024/early 2025 circa GPT-o4

It was model improvements, followed by inference time improvements, and now it's RLVR dataset generation driving the wheel.

> in 5-10 years, most entry-level laptops will be able to manage a local 30B sized model

I suspect most of the excitement and value will be on edge devices. Models sized 1.7B to 30B have improved incredibly in capability in just the last few months and are unrecognizably better than a year ago. With improved science, new efficiency hacks, and new ideas, I can’t even imagine what a 30B model with effective tooling available could do in a personal device in two years time.

> One could say that the introduction of the personal computer became a "race to the bottom." But it was only the start of the dot-com bubble era, a bubble that brought about a lot of beneficial market expansion.

I think the comparison is only half valid since personal computers were really just a continuation of the innovation that was general purpose computing.

I don't think LLMs have quite as much mileage to offer, so to continue growing, "AI" will need at least a couple step changes in architecture and compute.

> But I think the more exciting fact is that we can probably expect LLMs to get a LOT cheaper in the next few years as the current investments in hardware begin to pay off

Citation needed!

We don’t need anecdotes. We have data. Google has been announcing quarter after quarter of record revenues and profits and hasn’t seen any decrease in search traffic. Apple also hinted at the fact that it also didn’t see any decreased revenues from the Google Search deal.

AI answers is good enough and there is a long history of companies who couldn’t monetize traffic via ads. The canonical example is Yahoo. Yahoo was one of the most traffic sites for 20 years and couldn’t monetize.

2nd issue: defaults matter. Google is the default search engine for Android devices, iOS devices and Macs whether users are using Safari or Chrome. It’s hard to get people to switch

3rd issue: any money that OpenAI makes off search ads, I’m sure Microsoft is going to want there cut. ChatGPT uses Bing

4th issue: OpenAIs costs are a lot higher than Google and they probably won’t be able to command a premium in ads. Google has its own search engine, its own servers, its own “GPUs” [sic],

5th: see #4. It costs OpenAI a lot more per ChatGPT request to serve a result than it costs Google. LLM search has a higher marginal cost.

I personally know people that used ChatGPT a lot but have recently moved to using Gemini.

There’s a couple of things going on but put simply - when there is no real lock in, humans enjoy variety. Until one firm creates a superior product with lock in, only those who are generating cash flows will survive.

OAI does not fit that description as of today.

I'm genuinely curious. Why do you do this instead of Google Searches which also have an AI Overview / answer at the top, that's basically exactly the same as putting your search query into a chat bot, but it ALSO has all the links from a regular Google search so you can quickly corroborate the info even using sources not from the original AI result (so you also see discordant sources from what the AI answer had)?

Whilst those other layers are useful, none of them are particularly hard to build or rebuild when you have many millions of dollars on hand.

One doesn't need tens of billions for them.

You're absolutely correct! ( ;) )

The issue is that generation of error-prone content is indeed not very valuable. It can be useful in software engineering, but I'd put it way below the infamous 10x increase in productivity.

Summarizing stuff is probably useful, too, but its usefulness depends on you sitting between many different communication channels and being constantly swamped in input. (Is that why CEOs love it?)

Generally, LLMs are great translators with a (very) lossly compressed knowledge DB attached. I think they're great user Interfaces, and they can help streamline buerocracy (instead of getting rid of it) but they will not help getting down the cost of production of tangible items. They won't solve housing.

My best bet is in medicine. Here, all the areas that LLMs excell at meet. A slightly distopian future cuts the expensive personal doctors and replaces them with (few) nurses and many devices and medicine controlled by a medical agent.

I was really hoping, and with a different administration I think there was a real shot, for a huge influx of cash into clean energy infrastructure.

Imagine a trillion dollars (frankly it might be more, we'll see) shoved into clean energy generation and huge upgrades to our distribution.

With a bubble burst all we'd be left with is a modern grid and so much clean energy we could accelerate our move off fossil fuels.

Plus a lot of extra compute, that's less clear of a long term value.

Alas.

But some people do believe that AI is all hype and it will all go away. It’s hard to find two people who actually mean the same thing when they talk about a “bubble” right now.

> don't expect AGI or Super intelligence to take that long

I appreciate the optimism for what would be the biggest achievement (and possibly disaster) in human history. I wish other technologies like curing cancer, Alzheimer's, solving world hunger and peace would have similar timelines.

Yeah except that models don't propel communities towards new heights. They drive towards the averages. They take from the best to give to the worst, so that as much value is destroyed as created. There's no virtuous cycle there...

I‘m aware this means leaving the original topic of this thread, but would you mind giving us a rundown of this whole Japan 1989 thing? I would love to read a first-person account.

> Cash is Oxygen. You hoard it to survive the inevitable crash. For OpenAI, Cash is Rocket Fuel. They are burning it all to reach "escape velocity" (AGI) before gravity kicks in.

For OpenAI, cash is oxygen too; they're burning it all to reach escape velocity. They could use it to weather the upcoming storm, but I don't think they will.

> Just try to compete with OpenAI, let's see you calculate the price of attempting it. Scale it to 300, 500, 800 million users.

Apparently the DeepSeek folks managed that feat. Even with the high initial barriers to entry you're talking about, there will always be ways to compete by specializing in some underserved niche and growing from there. Competition seems to be alive and well.

> chips with brain matter and or light

The... what now?

You seem to have forgotten that the ruling class requires tax payers to fund their incomes. If we're all out of work, there's nobody to buy their products and keep them rich.

Pretty much every major historical trend of Western societies in the second half of the eighteenth century, from the development of the modern corporation to the advent of total war, was intimately tied to railroad transportation.

Transportation of people, yeah, but it still carries a majority of inter-city freight in North America.

Umm yes? The metro even if not a big deal in the states is like a small but quiet way it has changed public transport, plus moving freight, plus people over large distances, plus the bullet train that mixed luxury, speed and efficiency onto trains, all of these are quietly disruptive transformations, that I think we all take for granted.

Railroads built America and won multiple large wars.

What exactly is "second" place? No-one really knows what first place looks like. Everyone is certain that it will cost an arm, a leg and most of your organs.

For me, I think that, the possible winners will be close to fully funded up front and the losers will be trying to turn debt into profit and fail.

The rest of us self hoster types are hoping for a massive glut of GPUs and RAM to be dumped in a global fire sale. We are patient and have all those free offerings to play with for now to keep us going and even the subs are so far somewhat reasonable but we will flee in droves as soon as you try to ratchet up the price.

It's a bit unfortunate but we are waiting for a lot of large meme companies to die. Soz!

A penny saved is a penny earned

Did you try asking chatgpt to explain?

You weren’t around pre Google were you? The only thing Google learned from other search engines is what not to do - like rank based on the number of times a keyword appeared and not to use expensive bespoked servers

Isn't it really the other way around? Not to say OpenAI and Anthropic haven't done important work, but the genesis of this entire market was paper on attention that came out of Google. We have the private messages inside OpenAI saying they needed to get to market ASAP or Google would kill them.

Yes they did, at least twice in the 19th century. It was the largest financial crisis before 1929

Your view is ahistorical.

I still find it so fascinating how experiences with these models are so varied.

I find codex & 5.2 Pro next to useless and nothing holds a candle to Opus 4.5 in terms of utility or quality.

There's probably something in how varied human brains and thought processes are. You and I likely think through problems in some fundamentally different way that leads to us favouring different models that more closely align with ourselves.

No one seems to ever talk about that though and instead we get these black and white statements about how our personally preferred model is the only obvious choice and company XYZ is clearly superior to all the competition.

There is always a comment like this in these threads. It’s just 50-50 whether it’s Claude or OpenAI.

I’m not saying that no company will ever have an advantage. But with the pace of advances slowing, even if others are 6-12 months behind OpenAI, the conclusion is the same.

Personally I find GPT 5.2 to be nearly useless for my use case (which is not coding).

For me OpenAI is the worst of all. Claude code and Gemini deep research is much much more better in terms of quality while ChatGPT hallucinating and saying “sorry you’re right”.

I use both and ChatGPT will absolutely glaze me. I will intentionally say some BS and ChatGPT will say “you’re so right.” It will hilariously try to make me feel good.

But Gemini will put me in my place. Sometimes I ask my question to Gemini because I don’t trust ChatGPT’s affirmations.

Truthfully I just use both.

codex is sooo slow but it is good at planning, opus is good at coding but not at good at seeing the big picture