Given the propensity for these big tech companies to hoover up/steal any information they can gather, running these models locally, with local fine tuning looks quite attractive.
at the end of the day you still have to sell this product to the sorts of companies that are far and away all microsoft 365/google workspace clients and we're gonna have to figure that out one day or another
think inside the box
I myself just have proof of a single customer having their own private Cerebras rack. There are rumors about several more customers with on-prem Cerebras.
The reality is that many datasets include stuff that has been absolutely stolen or haphazardly stored online, stuff like emails, texts, conversations, our credit histories, really any information about people that exists in a large quantity has already made its way into these LLMs one way or another.
An AI trained solely/additionally on specific datasets, with the intent of predicting human behavior exactly, should yield successful and highly accurate predictions from rather general demographic data combined with an individuals location history/current their location, plus really any third substantial thing - could be browsing history, or purchases, activity on social media, that should be all that's necessary to rather accurately put everyone into a box.
The most frustrating thing is that there is a box for the people that refuse to be put into a box.
GCP offers hundreds of models in its Vertex AI, including all "open source" (actually open weights) models, and the ability to fine tune for your specific needs. This blog post is from 2023 [1].
(disclaimer: I work at Google, but not on the Cloud team)
[1] https://cloud.google.com/blog/products/ai-machine-learning/s...
So it's true that you can't encrypt compute tasks of this type end-to-end, so you can't know if unauthorized parties mine your data. However, Microsoft is very unlikely to mine your data (for "you" being e.g. any of the many multinational corporations that already run all their office work through Azure-hosted Outlook, Office, SharePoint, etc.), or to let others mine it, because if it ever came out, your customers' lawyers would be after you, your lawyers would be after Microsoft, and the whole thing would explode into a multiple-billion-dollars shitshow and might even get a government or two involved.
That's the working assumption that makes Microsoft well-positioned to eat any fledgling self-hosted DeepSeek market in the business space. They already have things set up at a level that is trusted by governments as well as corporations in critical industrial sectors, with huge financial and legal exposure.
(Presumably Google and Amazon are in a similar position here, though I've only seen this personally with Microsoft/Azure, so that's what I can comment on.)
For contract breach civil crime like this, there is zero chance it ends with jail time.
On top of that, "everything is securities fraud" - and since that does carry potential jail time, corporations generally try to avoid pissing off parties that would be able to frame a contract breach (and its consequences) in terms of investment fraud.
EDIT:
For starters, almost all data a multinational corporation generates and processes is subject to export control regulations, which are broad, full of special cases, vary over time, space and politics, and most importantly, violations of them come with huge fines and criminal penalties[0] for both businesses and individuals involved. The only reason Microsoft can get a corporation like this to migrate to O365 and run their back-office in Azure cloud is by solid, tested contractual guarantees that the data will be processed in ways that will keep the customer compliant with applicable regulations. Now, I'm not a lawyer, but it's not particularly hard to draw a line from "Microsoft snooping on enterprise customers" to securities fraud.
I mean, even in context of hosting a DeepSeek derivative, we're talking about a cloud service offering enterprise customers secure training on company data. "Company data" may involve, e.g. detailed documentation or specs for software for designing advanced optical systems, which may sound benign until you make the connection[1]: "advanced optics" includes applications in advanced laser systems, which basically means weapons (e.g. ranging, missile targeting, anti-missile countermeasures). Obviously, regulators around the world (and the US in particular) would be very unhappy to see such information crossing through the wrong borders. For both the affected customers and the cloud service, this is high stakes game; a random startup isn't in a position to enter it.
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[0] - E.g. in US, up to $1M per violation and up to 20 years in prison, possibly at the same time; see https://www.bis.doc.gov/index.php/enforcement/oee/penalties.
[1] - This was a real intro example used in export control training I went through some years ago.
A small random startup is unlikely to play in the securities sandbox until they have enough resources to hire enough lawyers to keep themselves out of prison and the fines "reasonable"(i.e. not enough to incentivize actually doing something about the fine being imposed other than to at least temporarily stop doing the action).
When was the last time securities fraud ended in jail time by any S&P 500 company? My quick web search returned no instances ever(but I could be wrong).
My point here is that OP's startup won't be able to compete with incumbents for enterprise money, and since the incumbents already provide this kind of service cheaply and reliably for customers of any size, all while handling applicable security concerns, OP's startup won't be able to compete with them for smaller customers either.
Given the current US government is headed by a person that just looks to take what he wants - your assurances aren't comforting.
Sure, but that's not some unexpected gotcha - it's just a plain fact of geopolitical reality, managed by international treaties and accounted for in laws and contracts around the world. A multinational enterprise isn't like a person subscribing to a free plan of a random SaaS because the "sign up" button was the right shade of green - there are armies of lawyers on both sides, tasked with navigating applicable regulations (including GDPR and export control laws) and finding out a way to make things work.
When they can't, the deal simply doesn't happen.
What actually happens is you have people seeing no evil, hearing no evil and speaking no evil - by going lalalala - hoping that because everybody else is doing it they won't get fired.
This happens because alternatives seem too hard.
There is no evidence of this happening in the last 20 years. None.
And if there was it would be the complete unravelling of the entire cloud concept.
So you're talking about solving a problem no one has.
Plenty of evidence of companies and governments using spying for commercial/national ( sometimes the same ) advantage.
So let's say you are a big company, and suddenly the US government decides you are a competitor in a nationally strategic industry - is your data safe if held by a US company?
However, if both training and operating costs of a DeepSeek-like model are as small as they are, the companies best able to offer this service are... Microsoft, Amazon and Google. And second best are... teams inside the would-be customer enterprises themselves. $6M to train and $6K to run is effectively free for such companies; there is no moat here. The services that enterprise customers would happily buy instead of building are... operations, and assuming legal liability if the model turns out not to be safe from copyright infringement lawsuits. But those are exactly the services those companies are already buying from Microsoft, Amazon and Google.
Maybe they could skin the robotic bureucrats in vintage scifi appearance as well to have the whole consistent experience when you go to the building permits bot, there could be small talk about the latest Beatles record etc.
(I'm reiterating my prediction wrt. AI and moats - the only mid-term moat there can be is in human labor. Hardware vendors benefit from selling better hardware to more people for less; software and research are cheap to scale, datasets eventually leak or get reproduced. Human labor is the one thing that doesn't scale, and except for an economic crisis, only ever gets more expensive with time. Whatever edge one can get by applying human labor that cannot be substituted by AI - like RLHF and its evolutions - is the one that will last all the way to AGI; past that, moats won't matter anymore.)
One of the many reasons I'm firmly on the side of making the training of large neural models exempt of copyright considerations for everyone.
edit: apparently in the EU the situation is complicated by new AI specific legislation in the works: https://www.morganlewis.com/pubs/2024/02/eu-ai-act-how-far-w...
As someone not familiar with investment sourcing or SME financing. Could you break down the maths/accounting? How do you go from sinking 40k in a business to losing 6.5k if you turn the lights off at the end?
I would invest more than the initial $30K on optimization after the servers have found paying customers and thus have proven commercial viability. I would invest in software development, finetuning, retraining and above all reverse engineering GPU and neural engine instruction sets and adapting these open source models to the more than 2 quadrillion operations per second that these 48 servers can do.
Because if that exists, I want to buy them all.
You would be wise to do the software development I mentioned, do more sales and support than was covered under my initial $3000 labour fee. But that you can pay for with the revenues, it would not be the initial investment to see if it is viable as a business.