AI Business Boats don’t rise with these models, they remain tethered to the old dock and sink.

Sinking businesses?

AI businesses are getting steamrollered by OpenAI & others. Business cases have to be moated against attack by the new releases, as the new model will do what you do but quicker, better & cheaper. Boats don’t rise with these models, they remain tethered to the old dock and sink.

The trend is towards huge compute, large models with massive investment, effort and expertise to build and role out. Your service, built on top of the model is simply done better by using the model directly. This makes AI different from all other technology we have ever invented.

The internet created millions of businesses as it was an empty platform. AI is abundantly rich, deep & wide, trained on content that takes hundreds of 1000s of years to read. We will never catch up. The internet was a sea on which we could all sail. A LLM is an ocean that can gobble us up.

The problem is that many businesses are also tethered to this old internet model, with proprietary content and platforms,. which are slow, shallow, difficult to use and functionally limited. Intelligence has been unleashed on a new platform tat is easy to use, multimodal and fast.

ChatGPT4o will make GPT4 available for free. This is astonishing, so much power, for free, perhaps the one feature that will change things the most in their announcement.

You have to make some big bet strategic decisions as a startup.

Bet 1: LLM scalability and progress will run our of steam, allowing faster and betters products to build upon their limited success. If you get this wrong you sink.

Bet 2: Open source products will be available that have the same functionality as closed proprietary models. Here you have a chance to float on the open source movement. 

Bet 3: Build around the success of the behemoths , with consultancy, projects for large companies and so on but that doesn't give you the big revenues you imagine.

In the end you are betting against entities that have huge amounts of capital, the ears of investors and the ability to deliver. Talent is also in short supply.

So what is the new business model(s)?

Hackathons are interesting as they tend to flush out all the low hanging fruit and use the existing models and services to get things done. Most of the this low hanging fruit is rotten by the time it hits the ground. What it does do is establish business demand and use cases.

Multimodality in all its forms, huge context windows and ability to read the screen through Co-pilot have laid waste to developed applications.

So one must identify where you lie on the supply chain.

If you are building some extra functionality on top of a model, but using that model for delivery, the danger is obvious, that an improvement in the model can eat you alive.

If you have a unique asset that can be used for access, such as a large publisher, you stand a chance if you can prevent leakage.

If you have part of a service that AI does not deliver but enhances, you have a chance.

Devices - forget it.

Road to monopolies

This is a worry, as this is the road to monopolies, possibly even a single monopoly, as we may get a runaway effect where one model excels and outperforms all others. The singularity may be in business. This is worrying and governments are ill-prepared to deal with this.

They compete with each other to offer low tax regimes and companies take advantage of this. Even in supra-national entities, like the EU, have massive tax theft by allowing the large US tech companies to set up shop in the lowest tax regimes, largely Ireland.

Some may succeed but, by and large (literally), the trend is towards huge compute, large models, fine-tuned that take massive investment, effort and expertise to build and role out. Your service, built on top of the model is simply done better by users using the model directly. This is what makes this technology different from any other technology we have ever invented. 

Altman and many others have observed the disaster that is the European Tech industry. It gets crushed by negativity, bought out by the US and strangled by regulation. The problem is not AI but politics and economics. We need to get this sorted and fast.