01:06:06 · Luca Ferrari
[01:06:06] S0: Well, I mean, by doing, we are very active. We have built our own models, but it's mostly narrow. We certainly don't compete on the frontier models. We sometimes build narrow purpose models to do something very specific. And if you have a very specific use case, you can often build a model that's just as good as the frontier models at that very narrow time. It's awful at everything else, it may be completely incapable of doing anything else, but at that one thing, can be even better, and if not way cheaper. So for example, if you use, I don't know, meetup, the events product, we own it and the recommender system, the system that once you search for something or you're looking for inspiration will determine which events and groups to show you, that's built in house and to the best of our benchmarking and knowledge, it's just as good as if we were to use like some of the frontier models, which obviously comes for essentially for free, as opposed to these models being very expensive. So we do some of that, most of our work is studying third party models, sometimes fine tuning them if they're open weights, certainly combining them and leveraging for the different activities and optimizing which ones we use for which activities as I was describing before. So we're very hands on in the field, and therefore it's relatively easy to stay abreast of advances. But I will say, I've never seen any industry or new technology progress as fast as AI has over the past, especially the last three, four years. And so I feel that I make an effort to catch up this week, and maybe for a few months I need to focus on M and A or something else, then I feel like I'm completely outdated on my knowledge. It is quite... It's exciting. I'm an engineer at heart, but also, like I said, particularly as this is quite dangerous, think that speed is not ideal.
01:08:04 · S1
[01:08:04] S1: I'm curious, what do you think the question is about AI that people aren't asking?
01:08:16 · Luca Ferrari
[01:08:16] S0: Oh, that people aren't asking. I mean, don't know, it seems that people are talking about it so much that they've asked all sorts of questions. I think it's maybe, the main issue is whether we're answering these questions in a satisfactory way. For example, I think most people agree that this is scary in many ways. And yet, frankly, I don't think anybody has done anything truly meaningful to make it safer. Even the labs themselves, I'm sure they're investing in safety, I don't know enough, but they're rushing to be market leaders, or they're dead, their valuations would probably drop 90 if there was a perception that they're losing ground. And know, they're trying to survive and thrive this year, next year. So I'm sure, you know, there's more they could do, be more cautious, but that would come potentially at existential. It would drive existential risks for them as companies. Governments, I don't know, they're maybe talking about it, but I haven't seen anybody do anything meaningful. The EU created the AI Act, which I find it to be highly harmful to the industry and solves none of these problems, like the real existential threats, humanity doesn't really tackle those. So maybe an interesting question that people have been asked, at least haven't heard being asked is why are we failing to do something about it? Because people are asking what we should do, nothing is happening, I haven't heard a lot of people say, what's currently preventing fixes to being proposed and deployed? You know, what's the root cause of this inability to do something about it? Because if we were to fully understand the root causes, then maybe we would stand a chance to do something useful.
01:10:25 · S1
[01:10:25] S1: What's been the biggest difference, you're a global company, The biggest difference in perception and application of AI in Europe versus US. And I also apologize. I'm totally taking up all of the air right now with these AI questions, but I understand I have a very intelligent engineer in front of me. So I'm gonna ask them, but what do you think is the biggest difference between the perceptions and actual applications?
01:10:48 · Luca Ferrari
[01:10:48] S0: Well, think every time there's something moving very quickly and being newsworthy, there is a lot of exaggeration and misunderstanding. I I think on the one hand, some people think AI today can do more, and this is typically people who don't really use it, but mostly read about it, they think it can already do everything for you, and it's a lot more advanced than it is. As impressive as AI models are, I think today they still have very glaring limitations across most use cases. So I don't think we're at a point where you could hand over the keys of your life or work to AI, and you could actually trust it to add significant value, think there will be a good risk that things could go awry, but the trajectory is certainly very promising. Then there are people who rightfully fear that AI will destroy jobs, and I've changed my mind at this point recently, but it's certainly a very important topic. But rather than thinking of proactive ways of protecting prosperity and people more than workers, people, they go on the defensive and they try to come up with these more protectionist regulation or approaches, which are obviously an awful idea, because a country that doesn't embrace AI, unless every country in the world stops progressing in this field, which I would say we could put in the bucket of the impossible things pretty much, again short of world war, a country that does not fully embrace using AI best into complete irrelevance and basically, becoming third world, and probably, maybe even just a few decades. So that's a certainly a dumb approach, although it's a populist approach and as such, help occasionally get votes. Yeah, maybe those are some of the more remarkable extremes I've seen, but we could talk about it for a long time.
01:12:51 · S1, Luca Ferrari
[01:12:51] S1: We can talk about it for a very long time. We have to get to the walking portion, but before we do that, I just want to ask you, what are you most looking forward to in the next twelve months? [01:13:04] S0: Well, there are many things, but I'd say probably further progress in our in house technologies, especially taking advantage of AI. We have very, very big plans and we're seeing massive progress. I do think that, you know, we talked about it before, Spoons, you know, the central team, $4,000,000 in revenue per member of that team, and this has grown tremendously. It was about $1,000,000 just two, three years ago. I think we're about to see this keep rising pretty fast, and a lot of that, some of it is scale, just bringing together this business and integrating them all together creates tremendous leverage, a lot of it will be technology and so I'm really, I can't wait to see some of the things we're working on and we have in mind actually come to fruition, I think it'll be extremely exciting. We try to constantly reinvent what running a business effectively, efficiently looks like, be at the cutting edge of that, so that we can then go out into the world and buy businesses for really good prices for sellers and deliver high returns, the technological aspect of that progress is very exciting to me. [01:14:17] S1: Amazing, well, thank you so much for hosting us here today and having us at Bending Spoons in Milan. This is amazing. So excited for all of the other conversations we're going to have with your team. Thank you so much. Thank you.