Exactly. Toyota's CEO also explained a few weeks ago that they need to build cars for the whole world. Many countries are not ready yet with infrastructure for electric cars.
I would also add since insurance companies don't want to insure the transportation of batteries in container ships, it makes it difficult for Toyota to produce electric cars in all regions, it would mean they would always need to have a battery factory nearby.
https://toyotatimes.jp/en/toyota_news/1055_1.html#anchorTitl...
> are not ready yet with infrastructure for electric cars
The same infrastructure they need for everything else in their life. I bet they have way better access to electricity than they do hydrogen. Or even gasoline, frankly. Solar panels are cheap.
Your post is very interesting. Thanks for sharing.
If your focus is narrow enough the vanilla gpt can still provide good enough results. We narrow down the scope for the gpt and ask it to answer binary questions. With that we get good results.
Your approach is better for supporting broader questions. We support that as well and there the results aren’t as good.
Thanks for reading it! I agree that binary questions are easy enough for vanilla GPT to answer. If your problem space fits them - great. Sadly, the space I'm in doesn't have an easy mode!
Not op but someone that currently runs an ai contract review tool.
To answer some of your questions:
- contract review works very well for high volume low risk contract types . Think slas, SaaS… these are contracts comercial legal teams need to review for compliance reasons but hate it.
- it’s less good for custom contracts
- what law firms would benefit from is just natural language search on their own contracts.
- it also works well for due diligence. Normally lawyers can’t review all contracts a company has. With a contract review tool they can extract all the key data/risks
- LLM doesn’t need to provide advice. LLM can just identify if x or y is in the contract. This improving the process of
review.
- context windows keep increasing but you don’t need to send the whole contract to the LLM . You can just identify the right paragraphs and send that.
- things changes a lot in the past year. It would cost us $2 to review a contract now it’s $0.2 . Responses are more accurate and faster
- I don’t do contract generation but have explored this. I think the biggest benefit isn’t generating the whole contract but to help the lawyer rewrite a clause for a specific need. The standard CLM already have contract templates that can be easily filled in. However after the template is filled the lawyer needs to add one or two clauses . Having a model trained on the companies documents would be enough.
Do you think LLMs have meaningfully greater capabilities than existing tools (like Kira)?
I take your point on low stakes contracts vs. sophisticated work. There has been automation at the "low end" of the legal totem pole for a while. I recall even ten years ago banks were able to replace attorneys with automations for standard form contracts. Perhaps this is the next step on that front.
I agree that rewriting existing contracts is more useful than generating new ones--that is what most attorneys do. That said, I haven't been very impressed by the drafting capabilities of the LLM legal tools I have seen. They tend to replicate instructions almost word for word (plain English) rather than draw upon precedent to produce quality legal language. That might be enough if the provisions in question are term/termination, governing law, etc. But it's inadequate for more sophisticiated revisions.
Didn't try Kira but tried zuva.ai, which is a spin off from them. We found that the standard LLM performed at the same level for classification for what we needed. We didn't try everything though. They let you train their model on specific contracts and we didn't do that.
For rewriting contracts keep in mind that you don't have to actually use the LLM to generate the text completely. It is helpful if you can feed all the contracts of that law firm into a vector db and help them find the right clause from previous contracts. Then you can add the LLM to rewrite the template based on what was found in the vector db.
Many lawyers still just use folders to organize their files.
I also built an AI contract review ai tool and talked to > 100 lawyers. What I found is that lawyers want technological advances but only if they work 100% of the time.
Also helped lawyers looking for a CLM, and they rejected something if it caused any inconvenience.
I launched a contract review tool about year ago[1].
The legal liability is an issue in several countries but contract generation can also be. If you are providing whatever is defined as legal services and are not a law firm, you will have issues.
> If you are providing whatever is defined as legal services and are not a law firm, you will have issues.
that is a big reason why we haven't integrated AI tools into our product yet. Currently our business essentially works as a free product that is the equivalent of a "stationary store" of you are filling out a blank template and it is your responsibility what happens. This has a long history of precedence since for decades people could buy these templates off the shelf and fill them out themselves.
Giving a tool to our users to answer legal questions opens a can of works like you say. We decided that the stationary store templates are a commodity and should be free (even though our competitors charge hundreds for them) so we make money providing services on top of it.
I would also add since insurance companies don't want to insure the transportation of batteries in container ships, it makes it difficult for Toyota to produce electric cars in all regions, it would mean they would always need to have a battery factory nearby. https://toyotatimes.jp/en/toyota_news/1055_1.html#anchorTitl...