[hobonation]

Is it me or do none of the AI companies have a "moat" in the Ben Grahmm sense.

I use their services, but I frankly don't care who provides it. I'll chase the chepest/best and have no issue switching from one to another.

The only moat I can see is Microsoft providing its services to companies in its Azure system. Nervous IT departments probably like that it's not leaving their control if Bob in the SAP team spins up some AI crap.

[RansomStark]

I've been thinking for a while, there's not real winners here except the incumbent technology providers. Hear me out: all models are converging towards the same level, gains are getting smaller and harder to come by. The models are commodities nothing more.

This is the leap, nobody really wants to front a model for someone else. If i build an agent, or a service that requires a model, I'd prefer to push the model onto someone else, preferably at no cost. This is a leap as I'm sure right now, most people / businesses are thinking actually i do want to own / front the model.

However, if you accept the leap the easiest way to do this is to make the model the users problem.

From a business point of view that makes things really easy, from a customer point of view, they simply have to accept whatever their vendor of choice is pushing down their throats.

So as a business I build for whatever model Google makes available to android, and whatever model windows bundles, and whatever model Apple bundles, and, excluding the long tail of Chinese vendors and Linux (sorry, its always left out) and that's it, problem solved, and the customer picks up the tab for the tokens

[rsoto2]

Step 2. Rising competition causes returns to fall below cost of capital.

https://www.youtube.com/watch?v=2J2Fb1bBufA

[crims0n]

Google has a bit of a Network Effect going... my vehicle got an OTA update to use Gemini. Between that, search, storage, and the YT Premium bundle it was enough to convince me to float a subscription.

[ceejayoz]

> my vehicle got an OTA update to use Gemini

G. A. H.

edit: Y'all downvoters want genAI in your cars?!

[californical]

It’s not interesting to talk about per HN rules, but I expect your downvotes are because your comment doesn’t add any substance or interesting new details, not because people disagree with you. Votes here are different than Reddit (oh you have 94k HN karma! You probably know that then)

[pseudosavant]

I've found that there is value in consuming AI services from your existing cloud provider. Customers and auditors have less of an issue with "we use AI services from AWS/Azure/GCP" if the data was already in those clouds and it doesn't expand the risks of data being breached, or trained on, by some other provider.

When you are already trusting 100% of your data, and computing on that data, to someone like AWS, it doesn't meaningfully increase risk to use an additional service, even if it is an AI service.

[boron1006]

I think anthropic with its enterprise strategy and google with its integration in everything have a bit of a moat.

But I switched from ChatGPT to Claude 3 months ago because my account was down for like 6 hours. I haven’t used it since. It’s too easy to switch away from chatbots on a whim. There is no moat for that.

[lelanthran]

> I think anthropic with its enterprise strategy and google with its integration in everything have a bit of a moat.

But... Anthropic doesn't have a moat. It's clear at this point that SOTA models are not a moat, and Opus 4.6-level (or GLM 5.2) is sufficient.

Google, though... they own the entire vertical, from the semiconductors to the end-user software. They may have a moat.

[LarsDu88]

The narrative that superintelligence is imminent is partially at fault here.

There are competing definitions of what intelligence even is, and the one that I find most striking is from Francois Chollet which is that intelligence can be boiled down to skill acquisition efficiency. This type of definition makes intelligence more akin to polishing a ball than growing a watermelon.

The superintelligence doomers warn that the watermelon is going to start growing exponentially and crush everyone. But what might actually be happening is that we are not growing a watermelon but rather polishing the ball until its really smooth and shiny. There's a point where you can get it to micron levels of polish but for most tasks (white collar text domains tasks), it's smooth enough! You will be able to go to the ball store and buy a low cost made in china ball for most tasks.

The real challenge is actually branching out domains and modalities to tackle things like blue collar labor. Over time, white collar work automatable or able to be made hyperefficient by LLMs will see LLM commoditization.

[Vexs]

Observationally, for people that /aren't/ using models to code but to just do their white-collar job, claude.ai /is/ AI, now. The entire perspective for how to use AI is through claude skills, claude projects, claude cowork, etc. They've massively won the corp buy-in at the moment I believe.

[rad-b]

Fully agree, that’s how I see most of my less technical coworkers reason about using AI. “Is there a Claude skill for that?” is a question I hear multiple times a week.

I see a lot of comments (incl 2 sibling comments) are always discussing whether there is a moat on AI. We agree there is no technical moat, there is nothing that Anthropic or any other AI lab could do that wouldn’t be quickly offered by other competitors too. However, _market penetration is the moat_. The deeper Anthropic is in relationships with orgs, the higher the cost of switching. Sure, for an individual it’s a 2-second job, but for a business it’s actual work of changing permissions, provisions, updating vendors etc. Nothing catastrophic but still real work, implying that Anthropic would need to drop the ball significantly to be swapped out, and wouldn’t be just because there’s a competitor who does everything kinda the same for kinda the same price (or slightly less).

Moat can be in execution and not just in technology. McDonalds has no specific burger-making technology that no other restaurant can acquire, what they do have is a well-scaled execution. Sure, there are competitors, and sure there are new comers to the burger space with different recipes (e.g. smash) but that doesn’t mean McDonalds is going under. Market penetration is the moat.

[tart-lemonade]

People always underestimate the moat that is institutional agility/ossification. There may be no theoretical moat in software, but every time you switch HR or financial systems you find out the hard way just how many integrations have been built (directly or indirectly) around a specific way of thinking about organizational data imposed by the software containing it, all of which require significant rewrites for the new system's conceptualization. The costs of switching add up fast and the risks of delayed payments/paychecks significant, which is how you end up with companies paying $$$ for extended support on discontinued HR and financial software.

It's the same reason companies will pay for GSuite and O365 subscriptions concurrently because a handful of departments refuse to give up their desktop applications and others have Excel-based workflows that do not work in Google Sheets and do not care enough to learn Python or find someone in the company who can write a better system.

[lelanthran]

> The entire perspective for how to use AI is through claude skills, claude projects, claude cowork, etc

But as they have repeatedly pointed out, creating software is almost zero-cost now, so software cannot be a moat.

After all, all of the Claude software can be vibe-coded by any competitor; that's the dream that Anthropic has been selling anyway...

[rsoto2]

doesn't matter. that just means they've incentivized all competitors to enter the market and let's be honest none of their tools are that novel.

https://www.youtube.com/watch?v=2J2Fb1bBufA

[boron1006]

I guess I’m thinking a lot of companies seem to be getting Claude code subscriptions. It usually takes some time and effort for an org to switch away from one solution. In the meantime a lot of workflows get more and more tied to Claude in particular.

It’s not much of a moat, but it’s more than a lot of orgs have.

[bpavuk]

obligatory correction: the semiconductor layer is still owned by TSMC and Samsung. Google sketches chip designs for them to implement - that's the lowest layer they control. I am not denying that this is impressive.

[rsoto2]

google might have tons of integration. But if it invested too heavily into AI then it will also suffer when increased competition causes returns to fall:

https://www.youtube.com/watch?v=2J2Fb1bBufA

[nradov]

The moat is shifting from technology to access to proprietary training data. It doesn't matter how good your LLM platform is if you don't have good data to feed the training run. Public Internet data and published media is already mined out. Now the frontier LLM vendors have shifted to licensing proprietary data that's locked up behind corporate firewalls, and even hiring human domain experts specifically to create new training content in target verticals. You'll see the effects of this next year, although it might not be obvious to those who mostly only use LLMs for coding tasks in popular programming languages for which there was already a lot of training data.

[lelanthran]

> Now the frontier LLM vendors have shifted to licensing proprietary data that's locked up behind corporate firewalls, and even hiring human domain experts specifically to create new training content in target verticals.

That's a losing proposition for any token provider - it's expensive and slow, and when you're done everyone with money to rent a last-gen H100 is going to distill your "closed" model anyway.

[dragonwriter]

> That's a losing proposition for any token provider

The specialized models for targeted verticals being discussed may well not be sold by tokens, but instead be behind the scenes powering dedicated packaged solutions where the customers don't have raw access to the model. Token providers still won’t have a moat, but AI isn't just selling tokens.

[solatic]

AWS and Google at least own their own hardware (Trainium and TPUs, respectively). It's a moat in the sense that designing, building, and deploying your own chips at scale is quite a feat and not easily replicated. The vertical integration will allow them to continue to be profitable once the models get good enough and competitors' prices race to the bottom. Google has Gemini; AWS may not deploy its own models (yet?), but that's not necessarily a losing position, as long as the market is able to run models sourced elsewhere on Trainium and the price is right.

[rsoto2]

That's exactly what giant train corporations thought. "We own all the railways, we've squashed the competition"

and they STILL went out of business because they over-estimated the demand for their shitty rails they built to the middle of nowhere. Same with "AI."

https://www.youtube.com/watch?v=2J2Fb1bBufA

[amlib]

Isn't specialized hardware also a big risk? GPUs are more amenable to any big changes that may happen in the next 5, 10 years of AI research. Maybe we won't even be talking about LLMs anymore. Maybe matrix multiplication won't even be the main primitive.

[moduspol]

If matrix multiplication isn't the main primitive, I think we have a lot of pain coming our way.

[amlib]

Maybe that is far fetched, but I could see them specializing for some super high dimension multiplication and meanwhile 5 years later turns out "all you need" are 3x3 matrices and suddenly 90% of your specialized hardware is now dark silicon :)

[foobiekr]

Their "own" as in built by Marvell and Broadcom. Especially Trainium but also TPU4.

[selicos]

The adoption of standards like skills and agent setup helps a ton. Nobody wants to be locked into an AI vendor like with cloud systems in general. And companies can't hold on to the #1 spot across multiple areas for very long, so users are even more motivated to move their process and stack between coding tools and AI companies behind them like Claude code.

Vendor lock in cannot happen, or you're bankrupt.

[twoodfin]

Amazon Bedrock is probably middlemanning an insane amount of token consumption these days for the same reasons.

[unreal6]

Is Bedrock a "middleman?" I believe that they run all inference inside of AWS data centers, on their own infrastructure.

Their new endpoint even promises zero operator access [0]

[0] https://aws.amazon.com/blogs/machine-learning/exploring-the-...

[twoodfin]

Sure, but fundamentally they’re acting as a distributor of someone else’s product in the form of the frontier models. That’s a classic middle-man.

No value judgement. I think this is a fantastic strategy.

[wmf]

Weights are worth far more than data centers.

[jimbokun]

Why?

Seems like open weight models keep catching up to state of the art within a few months, at most. Doesn’t seem like much of a moat to me.

[twoodfin]

If/when open-weight models do catch up (i.e. become the dominant product in demand), Amazon transitions from a middle-man to the supplier with the best economies of scale.

Great business either way. You could even draw an analogy to Linux/OSS & the origins of AWS. They started as basically an infra middle-man for other people’s technology. But as the core tech commoditized, they transitioned into selling their own higher level services at scale—like Bedrock.

[lelanthran]

> Weights are worth far more than data centers.

I dunno, hey. After all, I can't distill my competitors datacentres :-)

[mikeweiss]

You may not care, but a lot of people I know care what brand chat bot they use personally,. usually it's tied to trust and reputation more than anything else. People are fickle.

[anon291]

Nvidia has a moat. Hardware is hard. No one really competes with them for general compute

[FuriouslyAdrift]

AMD Instinct is their direct competitor for compute and they are better per dollar, better per watt, and out competing on raw performance.

Only thing holding them back is fab capacity which nVidia keeps buying in bulk to keep them small.

[HDThoreaun]

AMD is held back by their interconnect and firmware disadvantage compared to nvidia. They’ve been trying really hard to create their own cuda, but rocM and HIP still aren’t very popular especially for research.

[pocksuppet]

And their repeated refusal to either implement CUDA or reimplement everyone's CUDA libraries on their own platform. They say that AMD never misses a chance to miss a chance.

[anon291]

Have you ever actually had anyone work with these chips? Developer ux on amd is terrible.

[FuriouslyAdrift]

Yes. We have a quad MI300A server and run several inference models on it. For $107k it has saved us so much money on tokens already and it's a heck of a lot faster than cloud services.

[anon291]

Do you do research? Because if you don't, then you're not the target market for general purpose AI compute chips.

[FuriouslyAdrift]

We use it for business analysis in a manufacturing environment (inputs from sensors, databases, external signals, etc.)

We also use it as a programming tool to design software, ingest logs and do analysis, find patterns in data, etc.

We bought it because we were burning through too much cash with Claude and Gemini.

[lelanthran]

> Have you ever actually had anyone work with these chips? Developer ux on amd is terrible.

Just how much of dev ux do you need? A foundational library, of course, but as the AI companies keep saying, their models can vibe-code what's needed for those chips anyway.

[foobiekr]

Nvidia's moat is the IBM, Microsoft moat:

I am about to spend $20M, if I buy anything other than Nvidia, and things go wrong, I am going to get blamed, and if things go right I will get no credit. This is why AMD is making no progress outside of very narrow cases and supercomputing.

[nradov]

I thought that Nvidia's moat was more in CUDA? Hardware is hard but we've already seen other companies like Google design neural processors with compute efficiency close to Nvidia.

[dsl]

General compute is also the worst solution to the problem.

Nvidia's entire business is dependent on Google not being able to make TPUs fast enough.

[foobiekr]

Google would have to start selling them (the real ones, complete with interconnect) to third parties. If google does that, though, Nvidia is done.

Unlike AMD, Google can actually ship software. AMD has never shipped good software other than drivers (maybe) in the entire history of the company, including both ATi's history and true AMD. They have always relied on Intel to provide the software.

[therobots927]

Oh great, good to know the shovel seller has the market cornered.

Now back to the conversation, do any of the gold miners have a moat? Or is this a race to the bottom?

[unreal6]

> I use their services, but I frankly don't care who provides it. I'll chase the chepest/best and have no issue switching from one to another.

For the hyperscalers, there is an ease of remaining in the Azure/AWS/GCP fabric from a data provenance perspective, particularly for regulated industries or large, risk-averse enterprises. There's also, of course, a certain network egress tax in most cases.

[rawgabbit]

Uhh. I actively and vocally avoid all things Microsoft. I see Microsoft and I immediately think buggy software with zero security.

[esikich]

That's fine, but your inexperience with large companies that are MS's bread and butter doesn't really give you any credibility here. It's the standard for a reason.

[hobonation]

Can concur. I hate them with a passion, but corps love them, and I hate to say it... with good reason.

They're the only player in the Identity-Document-Email-VM-Storage space that's even remotely unified.

[dragonwriter]

Maybe so, but you clearly aren’t a representative sample of corporate decision-makers when it comes to AI (or broader IT) services.