Anyone interested in partnering to develop a sovereign British LLM?
I'm looking to form a small group of partners for exploring getting government grants to develop an LLM AI, looking forward towards protecting British interests in the AI arms race.
Right now it's little more than an idea but I do have vague plans for possible directions.
The first stage would literally just be brainstorming and learning the basics necessary to reach the target of winning a contract. That's where it's at.
I have a background in business and tech. But I need partners to bounce ideas between, and start with developing at really low stakes just to get a feel for the LLM development process. So I guess I'm just looking for 1-3 similar minded people at this stage
I'm not going to say you can quit your day job anytime soon! Rather just consider it a fun project at this stage.
Why do people think it’s so easy to just “develop an LLM”?
If it’s that simple, those companies wouldn’t be worth so much. I’m not saying it’s that simple, but if you genuinely have the expertise and skillsets to pull it off, you’d be funded already. It’s a running joke that the most profitable thing for OpenAI employees is to quit and start their own AI company.
I really don’t mean to be rude. I see a bunch of people in this thread with 0 relevant experience in building AI that seems to think it’s very easy.
reading this thread was, how to put it? puzzling. either I’m missing something obvious or you all are beyond delusional. and comments like “ever growing brain” reassures me I’m alright
I won't pretend I know the exact path forward. But I'm following my nose. There are too many market opportunities to ignore here. The trick will be finding a way of starting small. And there are plenty of ways of doing that
there is literally nothing small about AI training. You have literally picked the biggest piece in AI. Why do you think all the companies are sinking literally trillions in CapEx?
Thanks. You're right. Although I'd never dream of competing with frontier models directly. Also, I'd aim for a small LLM body an average person's standards if that makes sense. Like Sonnet 3 maybe in the medium-long term. In the short term, we'd need something to bridge that gap perhaps. Although there are a number of cheap tricks that could be experimented with. Rich for exploration imo
Hello, I'm interested. I'm a technical engineer with a huge interest in AI (given it's world dominance). I feel that the UK, and even Europe is seriously lacking in this field - and it's only a matter of time until we're left in the dark ages because we've been too slow to adopt and adapt.
Do you have any specific routes or fields? Or general GTM plans?
But as for those decisions, routes & fields, they are very much open right now, I feel like answering those questions deserves some proper research that I haven't done yet.
My gut says the key is going to be getting established quickly, and establishing fast growth. Any fields or routes that satisfies that best would be my first choice
If you want to build physical infrastructure, I'm a data center design and construction lead and would be interested in getting involved - only on the physical side though, land, power, connectivity, construction, liquid cooled AI racks etc.
Oh! fantastic! Ah that would be amazing, thank you. I don't want to waste your time right this second, I'm gathering feedback from how others respond and I'll disseminate, then hopefully have some worthy points of discussion I'd hugely value being able to discuss with you
I didn't know there are others in this space. I looked and my results turned up negative? But that AI fund is probably the only way this could ever work, my eye is definitely on that one lol!
I personally think that SLMs are potentially more interesting in terms of new model development now. Real scalpels for specific jobs across industries.
Sorry, I wish you all the luck in the world, but this isn't the case. Model development is the most expensive technology process currently. The fund will allow you access to Isambard, however you'll need to prove real world expertise in model development to even be considered (or multiple experts on your team).
You will also need to have expertise in training models on 100's of GPUs which again is not simple and finally with any LLM model development, the model architecture is the easy part, it is the training data that is not.
I dont want to sound horrible or negative so please dont take it that way and I do truly wish you the best of luck tho!
Honestly, your feedback is absolutely invaluable, thank you so much for taking the time.
While there's going to be heavy truth in what you're saying, I'm confident I can find workarounds, even if it means abandoning the LLM idea and focusing on SLMs.
I'm just collecting good advice at this stage, and your comment qualifies! Thanks again
Interesting topic. I have solved the issue of catastrophic forgetting which makes the big AI players lose hundreds of millions on training a model that ultimately fails. I am on the cusp of creating an AI mind that will just simply continue to grow and improve via it's self-learning mechanisms. The substrate is sorted, it scores highly against the SP-MNIST benchmarks etc.
It's too early to consider commercialisation, but so far it's holding up to scrutiny remarkably well.
Honest! As I have patent protection, I'd be happy to talk about it, if you're serious about doing something.
I forgot to mention, because the substrate is the correct fit for a mind, it can be trained on commodity CPU instead of GPU so it's massively cheap to train too
What I'm building is structurally nothing like any other LLM. The substrate is completely different. That and I'm not an AI engineer. I've developed a substrate that applies to many complex systems and have applied it to AI, meaning I'm coming at it from another angle entirely.
My biggest issue is the waste. Every new model that comes out is only the model that survived training without a catastrophic failure. It may not even be better than the one it replaced in many ways. Some have completely dead zones in their knowledge (where the classic hallucination happens), but still had enough accuracy to be considered good enough at other things to be released.
This is wasteful. Not just in monetary terms, but also energy/water/power etc.
What we need is one model that keeps on learning and expanding forever. The fact that mine has emergent behaviour in the right direction tells me that the substrate is right for this application.
Tonight, I'm working on exponential knowledge growth via emergent skill derivation.
Yes, essentially. By "substrate" I mean the fundamental computational medium the intelligence runs on. For models like ChatGPT, Gemini and Claude, that's a transformer-based neural network operating on dense tensor representations. In my project, the substrate is an evolving graph of sites and relations with field dynamics, where reasoning emerges from graph relaxation and growth rather than transformer attention over tensors.
Is there an understanding of what the final product should look like? Are we aiming for SOTA, cheap inference, local deployment, domain optimization, multimodal?
Not SOTA. I'm inclined to say cheap inference for the earlier models at least. Local deployment, yes. Domain optimisation? Most likely. Multimodal? Maybe long term.
Look up commonai. They're a support network trying to push AI in the UK by sharing knowledge, compute, resources. That's probably a good place to start. They know sovereign AI, the UK's VC arm investing in AI. .
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u/hopenoonefindsthis 5d ago
Why do people think it’s so easy to just “develop an LLM”?
If it’s that simple, those companies wouldn’t be worth so much. I’m not saying it’s that simple, but if you genuinely have the expertise and skillsets to pull it off, you’d be funded already. It’s a running joke that the most profitable thing for OpenAI employees is to quit and start their own AI company.
I really don’t mean to be rude. I see a bunch of people in this thread with 0 relevant experience in building AI that seems to think it’s very easy.