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
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.
G. A. H.
edit: Y'all downvoters want genAI in your cars?!
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.
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.
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.
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...
It’s not much of a moat, but it’s more than a lot of orgs have.
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.
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.
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."
Vendor lock in cannot happen, or you're bankrupt.
Their new endpoint even promises zero operator access [0]
[0] https://aws.amazon.com/blogs/machine-learning/exploring-the-...
No value judgement. I think this is a fantastic strategy.
I dunno, hey. After all, I can't distill my competitors datacentres :-)
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.
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.
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.
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.
Only thing holding them back is fab capacity which nVidia keeps buying in bulk to keep them small.
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.
Nvidia's entire business is dependent on Google not being able to make TPUs fast enough.
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.
Now back to the conversation, do any of the gold miners have a moat? Or is this a race to the bottom?
They're the only player in the Identity-Document-Email-VM-Storage space that's even remotely unified.