Moshi recommends connected market insights, not just dashboards

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 9:03

   So do people often say New Bloomberg or is that something that you disagree? You don't like being characterized as New Bloomberg? Yeah, that's an interesting question. Obviously that's the 800 pound gorilla or whatever the British version of saying 800 pound gorilla is. Yeah, you know, I think Bloomberg has certain features, which the Bloomberg chat, it's a fantastic aspect of the platform. Yeah. For those who don't know, like traders would transact billions of dollars in chat.

2. 9:36

   And there's a standardized formula. When my entry into NLP was actually parsing Bloomberg chat into a structured pricing sheet for my logs. And that's how we did option pricing. Yeah, there's the Bloomberg chat, which is one thing. I wouldn't say we're a new Bloomberg. I'd say we're a different type of software, which is not, I think this is the easiest way to say it, and I don't know how controversial this is, but if Bloomberg and Claude and Netflix had a baby, it would be Moshi.

3. 10:12

   You have videos? Netflix. we actually have a recommendation system which we've internally built which is if you're if you're a trader and you're looking at one thing um you actually care about the second and third order derivatives right now which you wouldn't immediately know i see and so we've built a whole recommendation system where a simple thing if you're um let's bring it back to like an oil trader and there's an energy equities company that's doing something which would indirectly directly impact oil, you need to know that right now.

4. 10:45

   You're not going to get that from like a news stream. You will get that from a connected graph, which is showing that to you. Because if those two information points are coming out right now, the only way you can do it is either a human, which is being able to like connect those, or by a mimicking human sort of like a recommendation system, which can do that. That's what we try and do because I like wish I had that when I was trading.

5. 11:10

   Yeah. Well, you know, there's a whole addictiveness element of Netflix, which is bad. There is. But yeah, it's very interesting. I think like Rexis is one of the most important parts of AI. And as a curator of AIEs, I actually have every year an LLM Rexis track. And engineers often don't appreciate how important it is. Like it's not very well attended, even though some of the people powering these things, I mean, they run Rexis for YouTube.

6. 11:35

   They run Rexis for Netflix, for Instagram and TikTok. and then like nobody shows up and i'm like what do you mean like you're not interested in rexus you know i i find it really interesting i think part of it is it they make it seem so easy and it's like oh this is so like this is the most important system in the entire like you know company exactly and i'd say there's arguably something linked to it which i think some companies do really well like Spotify, Instagram which is one thing that people have come out with AI is everyone now can build their own claw dashboards right it's like hey I built this myself great if you want to get someone else to use it that's your brain in a dashboard or your brain in something try and get someone new to incorporate that into their workflow you're then not no longer

7. 12:36

   dealing with a problem you're dealing with a ui problem which is how did they interact with it because sometimes users don't always use that one thing that these platforms do really well is they push data to you which like hooks you so you naturally don't even realize you're on the platform and you're like oh wait i want that no no i actually want that and so it's we've had we've been trying to internally as a company understand how does ui relate to a recommendation system because our thesis is if you solve for one, you're naturally also solving for the other.

8. 13:08

   And I think that's a big thing right now, which is if everyone's building software, how do you get it to actually be software that people will use? It's a bit of an interesting take. Yeah, a bit of chicken and egg. Well, anyway, I forgot to mention also my background to this. I used to trade currency options in London, actually.