f you are old enough to remember “vendor lock in” you will certainly be sensitive to the new challenge – putting your sensitive corporate data into someone else’s LLM – and a stranger forever owns what they intuit from your data.

Any clever query builder can likely access the sensitive information you put up into that LLM while you were thinking you were building a competitive advantage.

Welcome to the data sovereignty challenge – the immovable object up against the irresistible force of your board of directors making you do artificial intelligence – now, regardless of the cost.

Companies and governments have been sold the nonsensical, false narrative that the way to do A.I. is with unbounded large language models – using oceans of data – to which you gleefully contribute yours – to train an A.I system.

That is no longer the case.

The first issue with the ungainly LLMs is they are generally unbounded.

They try to answer almost any question for any person under any circumstance.

If you believe there is enough data in the universe which, when put into an LLM, answers the question “why is man” you need to stay away from A.I. budgets.

More leading firms are now adopting the concept of constrained, models – which solve, or address, a single problem with massive scale.

Once you determine or agree that your business or government program needs to answer problems in a domain, bounded by certain information types, you open the door to small language models.

The problem, the LLM guys will tell you, is that you need the massive data of a META or Twitter/X to get the best training for those models.

Aha! Sounds good but isn’t true – and we have the proof.

The issue of data sovereignty is exactly the one you are about to face with these LLMs – putting your data in someone else’s cloud – which can be in a country you abhor, run by your enemies – or competitors – wait until your board finds that out!

The alternative is taking lots of SMALL language models that run in Fractal instances that you control and aggregating them – with your data never leaving your control – so you get the benefits of scale, the benefits of far lower costs, while retaining data sovereignty.

This is where Fractal, designed from the bottom up to be fully distributed – with no cloud, no central point of control, enables scale far beyond any LLM, while you retain data sovereignty.

Let’s do an exercise.

You set up a Fractal system with 1,000 nodes, or Fractals.

Maybe 100,000 or millions, but unless you are Apple Computer doing a proof of concept, let’s go with the 1,000.

You allocate your data to 200 Fractals, each under your sole control.

Some are in the cloud, some are in your data center, some are at a customer site or all are behind your firewall – your configuration choice.

You fire up the training models and run them – in this case, you can even choose to do so without a data center at all – something Fractal is pretty much known for.

Regardless, you now have security and control on every piece of your data.

Nobody but you controls your data – no one else can see it or touch it.

When your board member calls to see how it’s going, you report that you built a huge training model, with over a thousand nodes – but you protected your data sovereignty at every step.

You received all the benefits of a state-of-the art training model, yet, unlike the LLM guys, nobody but your firm or agency saw, touched or received your sensitive data.

40 years ago every CIO, back then called VP of IT, sweated vendor lock in.

They feared a DEC, IBM, Burroughs – would tie their systems to vendor hardware and they would be owned by that vendor.

Today, with A.I. the CIO and board are learning when they participate in someone else’s LLM they have something worse than vendor lock in.

They lost the ownership of their data – forever.

They may have given up their most valuable intellectual property – to an LLM run in a distant place, out of their control.

So adopt data sovereignty; data is your most important asset.

Fractal distributed models – brought together – are more powerful than any LLM, and you get a good night’s sleep.

Without an data center – with sustainable computing – available today.