The more this site thinks about law firms training open weight models and renting their own GPUs, the less it seems to make sense. Here’s why.

Latham has got hold of its own GPUs to train open weight LLMs, meanwhile Kirkland is working with Palantir on its ‘own’ AI system, although as AL noted, it’s hiring staff with GPU experience, therefore it’s likely that they are going down the open weights route as well.

But why? Latham mentions in last week’s FT article that some client data is very sensitive so they need some of their AI capability to be on prem, or close to that. It also noted ‘consumption costs’, i.e. tokens. And Kirkland mentioned at the time of their announcement the importance of having their own thing, rather than relying on systems used by many other firms.

But, do these reasons stack up? Let’s explore some of the reasons why a law firm may or may not want to train its own open weights model.

Let’s do the big one first. A multi-billion $ law firm’s token costs are notable, but not something that would change the game for them. Legal tech companies are trying hard to develop routing systems to reduce reliance on the most expensive models. And nothing is stopping them from tapping a cheaper model directly either.…

Because you read this