Now I want to take a quick moment to give you a flyby of five different ways that llms are used commercially,
and you probably know of 50 more, but it's good to take a moment to look at them and to be food for
thought for you to consider other commercial applications of llms.
And while we're doing this, also be thinking about how you would assess the right model for these different
problems, using the kinds of leaderboards and the arena that we've already talked about.
The first one I wanted to show you is a company called Harvey, which uses llms in the field of law,
and you can read through their site, but it gives products for lawyers that will do things like answering
questions on on law, what what is a claim of disloyalty?
And I believe it also does things like looking through legal documents to find key terms and the like.
It makes so much sense to be applying llms to the field of law that it's a no brainer.
It's a classic example of needing to use language and nuance and apply it to difficult business Challenges.
Here's another.
And this is near and dear to my heart because this is my day job.
This is Nebula.
Uh, Nebula io, which is using llms to apply to the world of talent and recruitment, helping managers
to hire and engage with great candidates.
But it's also helping people to explore and understand where they can be most satisfied and successful.
Using Llms to understand the content of people's careers.
Again, it's the kind of use case that makes so much sense.
This one is one that I find particularly annoying.
I am, uh, upset by this particular company.
Blooper AI um bloop, which is a platform that ports.
Legacy code into Java.
And the reason that I find this, uh, galling is because I wish I had thought of it.
It's such a great idea.
It's such an obvious idea.
Obviously.
Brilliant.
As soon as I heard it, I thought, oh, that's a great idea.
Uh, so of course there is tons of COBOL code out there and other legacy code.
And it's it's a huge challenge for large corporations to figure out how to maintain this code, as people
increasingly don't want to work with languages like COBOL.
And there's a lot of legacy code that people can't read and understand.
Um, and it's such a perfect use case for coding models that can learn different programming languages
and then can use that to port from one language to another, and presumably can do things like adding
in comments and test cases and everything else.
Um, so, uh, yes, it's uh, dang it.
They've they've obviously, uh, really struck on a fantastic idea.
Uh, I think this is a great looking product from a Y Combinator backed company.
And, uh, yes, congratulations to to bloop.
And I love the name bloop.
Uh, on on less uh, memorable name would be, uh, this Salesforce product Salesforce's Einstein copilot
health actions Quite a mouthful, but I will say that aside from the slightly clunky name, the product
itself again is one of those ones that's like, oh yes, that makes sense.
Uh, a sort of, uh, dashboard that can be used by healthcare practitioners, for example, to do things
like summarize for a care coordinator, the outcomes of a medical appointment, saving presumably tons
of time, and giving this kind of very compelling summary of what happened, uh, which for all we know,
could be a Gradio app because that easy.
Uh, but it's probably something Salesforce, uh, but it's such a good use case makes a lot of sense.
And obviously, uh, no doubt Salesforce is going to do really well with that product.
And then I came across Khan.
Mingo Khan.
Yes.
I think it's probably how it's pronounced conmigo.
Um, uh, which is, uh, the Khan Academy.
Uh, presumably, uh, with a mingo at the end of it.
Uh, and this is an LLM based platform to be a companion for teachers, learners and parents.
And what a great idea again.
And the Khan Academy is a obviously a fabulous resource, and I'm sure that this is something that this
solution is something that will be immensely valuable.
And the application of LMS to education is something which is again a no brainer, absolute no brainer.
So across these different examples, law, talent, coding, the medical field and education, you can
see the impact that LMS will be able to make in each of these products.
And I'm sure you have many other examples yourself, but hopefully, as I say, this has given you food
for thought and also interesting to think about how you would be assessing different models that you
would pick to solve any of these problems.
To state the obvious, of course, for this one, no doubt we'd be looking at the medical LMS leaderboard
and hugging face, and here we'd be looking at many of the coding metrics, not just human eval for
Python, but the coding metrics for other languages too.
Okay, with that we will go over to wrap up.