# Why Scaling Laws Will Not Continue

OpenAI vs Anthropic vs X.ai: Who Wins and Why · How Far Will Model Providers Go Into the Application Layer · The End State for Models: Many Specialised or Few Generalised with Victor Riparbelli @ Synthesia

20VC · Jan 15, 2025 · 72 min · 16,261 words
Speakers: Victor Riparbelli, Harry Stebbings
Source: https://www.996.fm/episodes/20vc--ep-7f5c118e/

## Cold open

**Victor Riparbelli** [0:00]:

Mean, I think we're definitely in a bubble. Right? There's a lot of money that's gonna go up in flames in AI products. What I see a lot in the enterprise is buyers don't really know what they want. The real signal is not that you sign a contract. The real signal is renewal.

**Harry Stebbings** [0:11]:

This is 20 VC

## Intro

**Harry Stebbings** [0:12]:

with me, Harry Stebbings. Now six or seven years ago, this Danish entrepreneur walked into my office and presented his vision for the future. I did not invest, and it keeps me up at night. It is one of my greatest mistakes. Today, that same entrepreneur joins me in the hot seat. His company is now worth billions of dollars. Welcoming Victor Riparbelli, CEO and cofounder of Synthesia, the world's leading AI video communications platform for enterprises. And to date, Victor has raised over $250,000,000 from Accel, GV, NEA, and more. And check this out. More than a million users and 55,000 businesses love and use Synthesia today.

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**Harry Stebbings** [0:54]:

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## Conversation

**Harry Stebbings** [3:55]:

Victor, dude, we met, like, six, seven years ago when I was very, very young and, you know, very naive. I can't believe it's been that long, but thank you so much for joining me, dude. I'm glad to be here, man.

**Victor Riparbelli** [4:10]:

I'm still

**Harry Stebbings** [4:11]:

we

**Victor Riparbelli** [4:11]:

said

**Harry Stebbings** [4:11]:

before

**Victor Riparbelli** [4:12]:

for you that we're meeting under these circumstances.

**Harry Stebbings** [4:13]:

So am I. I said to you before, I I would have done better if I'd invested in every single company I'd ever met because it would have been you, Deal, Vanta, eleven Labs. I mean, oh god. I But wanna start today on some really exciting news that you have. So what is the exciting news you have for us today?

**Victor Riparbelli** [4:30]:

Yes. We just raised our Series D, which is super exciting, big milestone for us. We raised a $100,000,000 led by NEA with participation from all of our existing investors. So we're very excited to get it to 25 with a big war chest and, you know, just get to escape velocity, shut down the category that we're in, and win.

**Harry Stebbings** [4:47]:

First, amazing news. Congratulations. Thank you again for rubbing it in my face. My question to you is we were talking beforehand actually about the kind funding story of the business. Can you take me and I know it's not the schedule, but I still enjoy this. Can you take me to the seed round? People didn't get it. Just what happened, and how was that?

**Victor Riparbelli** [5:05]:

So this is back in '17, so it's a long time ago now, and the very short story is that we were a bunch of people. We had this sort of idea that in terms of AI, which back then wasn't really a term that most people thought about, but terms of AI would change how we create content. And the big shift was that back in 2017, when most people thought about AI, was about analyzing data, right, making decisions. That's kinda like that era of AI. But there was these early kind of GANs, which was basically a neural network that could kinda produce new data instead of just analyzing existing data. We thought that this was gonna be a world changing technology. We thought it was gonna change everything we know about how we create content from video, speech, audio, music, whatever, but we were focusing on video. I went out to the world with a great PowerPoint deck and we think a great vision, but I think understandably, most people thought we were pretty crazy. Right? We basically went out and said, look, in ten years, you're gonna be able to make a Hollywood film from your laptop needing nothing else than your imagination. That wasn't pitch that landed particularly well, especially not in Europe. We were based in London at the time. Why do you think that was? Because I think in Europe, the VC industry is still dominated by people who used to work in private equity, and that's a very different mindset than technologists. Right? So when you used to work in private equity, you're like a financier more than you're a technologist, and this was not a pitch you could understand for an Excel sheet. So we got turned down by, I mean, basically everyone, I think, like eighty, ninety investors, something like that. Including podcasters. Including podcasters.

**Harry Stebbings** [6:23]:

Who weren't in private equity and don't have that as an excuse. But, yeah, sure. And how much were you raising then?

**Victor Riparbelli** [6:29]:

The first round's a million dollars. We ended up doing it at the 5,000,000 post with Marc Cuban, who we sent

**Harry Stebbings** [6:35]:

Marc did one on five? One on five. Yeah.

**Victor Riparbelli** [6:37]:

And with today's valuation, 2,100,000,000. That's very

**Harry Stebbings** [6:41]:

He has, like,

**Victor Riparbelli** [6:42]:

15%

**Harry Stebbings** [6:42]:

today.

**Victor Riparbelli** [6:43]:

Something in that range.

**Harry Stebbings** [6:44]:

Wow. And then you went out and wanted to raise, like, 7. No?

**Victor Riparbelli** [6:48]:

So that was the later round. So that was back in 2017. We did a million at five. That kinda got us started. We went, like, twelve, eighteen months as you do. Went out to the market, felt like now we had a working technology. We were back then focused on on AI Dubbing, not the kind of avatar tech that we that we mostly have today. Again, learned a hard lesson. You know, we went out and were like, okay, we built this great technology. We have a great team. Let's raise 8,000,000. That completely failed and for, like, nine months, which is, like, dragging our feet. I made all the mistakes you can make as a founder. You I dragged out the funding process over nine months, like, different data points, different investors. It was a big shit show and we eventually had to rewind because we were running out of money and we ended up raising 3.1 and that kind of took us through to the Series A, which is when we had actually found product market fit and had like a sustainable business. But those two first rounds were very much rounds we raised based on story and it was a story back then that just didn't resonate that much because it was very hard for people to see what we had, how that could extrapolate that into everything that we came today.

**Harry Stebbings** [7:42]:

Today, that would have been a five to ten million round on a 40 to 50 given team and given vision. Would you have been as successful as you have been had you raised that round instead of the ones that you raised which were leaner and smaller?

**Victor Riparbelli** [7:58]:

So we talk a lot about this, and I don't think we would. I think if we'd raised eight, we would have a lot we could we could have done a lot more things, right, and we would have done more things. We would have built deepfake detection, which everybody wanted us to build. But remember, this is like this is like in 2018, right? At this point, AI video, to everyone outside of Synthesia, it was just deepfakes. People thought that that was gonna be like the big thing. And that is, of course, it's a problem and it's a real thing, but we always thought this is a subset of AI video. Most people are gonna use these technologies to create awesome creative content. But if we got that money, I think we would have built a team to do that, and that would have meant we've lost our focus. And I actually think that operating under the constraints that we had at the time really just focused us on our customers and selling the product. We were, like, ferocious about charging people from day one, even if it like, £500, right? And I think that focus and working on those constraints definitely helped us to get to the point where actually we found product market fit. I'm a big fan of, like, working under constraints. I really do think it forces a lot of discipline that easily gets lost the more money you have because you have more options. Right?

**Harry Stebbings** [8:58]:

You're also an angel investor now. How do you feel about the five on 25, 10 on 50 rounds with pedigreed founders coming from your massive names? How do you feel about them, and have you seen a trend in terms of how they perform?

**Victor Riparbelli** [9:11]:

Too much money too early is not healthy. Maybe some people are good at really having that discipline, maybe like second time founders, but it's very tempting to spend on things that you shouldn't be spending money on, especially when things are not working, right? I think once you clearly have product market fit, then a lot of things, a lot of decisions becomes a lot easier because they're more obvious, but before product market fit, it's really dangerous, I think, to be developing two, three, four things at a time, having 15 people working on your team when you're still at ideal stage, and I think a lot of people make the mistake of raising the money and then using it too quickly. One thing you cannot use money for or buy away with is product market fit, right? I think learning about your market, about your customers, it just takes time, and having a team of 20 people instead of five people trying to learn that, I think actually slows you down. You have to own that as a founder. I don't think we could have learned the same amount about our customers faster if we had more money back then. It really did take us like two years to just get into the minds of customers, understand video from like first principles, and I think people try and then you hire like a product manager to help you fix the product market fit problem because they're a product person, or you hire like a salesperson because you think you have product market fit and you just need to be someone who's better at selling it. Unless you have product market fit, like, you shouldn't have product managers and salespeople. Right? That is your job as a founder.

**Harry Stebbings** [10:23]:

Do you think that journey's ever done, though? Because I didn't believe in product market fit being this, like, we have product market fit. You have product market fit with creators. Tick, you say. Just and then suddenly you need to move into SMBs. Well, you don't have product market fit with them, you have it with creators who are independents, and then you need it with enterprise. And so I just see product market fit as this ever moving chapter book 100%. Which is different. And so actually, can you ever afford to move away from customers? And does it not always become more impossible with bigger teams?

**Victor Riparbelli** [10:51]:

I totally agree with you. And I think a successful company is a long series of product market fits, but you need that initial spark, right? Once you have that, you have something to build on. The bigger you get, the more bigger company you're building. You need new product, new product market fit essentially. And I actually do think that that's one of the things as a founder that you should always be focusing on. What is the next market? What is the next product you're targeting? Right? But in our case, we have I would say we have like a bunch of product market fits already. And those, I think you can hire super smart people that can run with it, make it great lines of businesses, make it great products. But I think pushing to those next product market fits and like where the company needs to be in two or three years, think I that remains to be the founder's job.

**Harry Stebbings** [11:30]:

You said about kind of the importance of capital constraints, cockroach mode. I think you hadn't touched your a when you raised your b. You hadn't touched your b when you raised your c, and now you haven't touched your c when you raised your d. Well, then why raise it?

**Victor Riparbelli** [11:44]:

Well, I think when you have the money, you do spend it. Right? I think for us, it's been more a matter of just we've always been obsessed about actually building a business, having great unit economics, and making sure that we're a business that generates money and revenue and that we're always in control of our own destiny rather than being, like, tied to a VC parachute. And so I think we've always just spent conservatively, but it's also very clear, right, that if you know where to spend the capital, it is an amazing asset, right? So building a great go to market team, for example, mean, that does cost money and that there's like a cash flow thing of you have to hire a bunch of people that are really great, they have to train, they take nine months before they wrap up, and then the investment is worth it. You wanna have capital, when we wanna have a really healthy balance sheet so that you can chase any opportunity that comes ahead of you. For us, like, we wanna build like a really, really big company. I think there is easily a $50,100,000,000,000 dollar company to be built in the space that we're in, and we wanna win that. You're not gonna win that by bootstrapping all the way. Right? I think that's that's that's a myth.

**Harry Stebbings** [12:39]:

How does Synthesia become a 50 to $100,000,000,000 company? Can you just paint that picture for me?

**Victor Riparbelli** [12:44]:

So I think we're in the early stages of a shift in how we communicate. If you think of most communication today, it's it's text based, right? Send emails, text, we read things, and text is a great technology. We built the world up to where it is today, but it's it's actually like a pretty bad way of compressing information. You lose a lot of context when you transform, like, your thoughts into something that's written down in in a document, right? As humans, we're much better at consuming visual content. We like to hear things. We like to see things. We like to feel things in the physical world. We can't do that yet. But it's very clear that, like, higher fidelity content like video and audio is a better way of training, informing, and entertaining people. The reason that we're using that much text today is because text is the only scalable way we have of essentially storing information and sharing information, right? But that's changing now because the more we don't need cameras and microphones and capturing things in the physical world around us, the more we can get video creation, audio creation to be as scalable as text. And once that happens, there isn't really any reason for us to use text anymore. This sounds a bit crazy, but I actually do think that maybe not us, but maybe our kids' kids, gonna be one of last generations to help read and write as, like, the default way of communication, I think will increasingly just consume everything via video and audio. I think you have all the trends that like, you look at TikTok. Right? I don't if you're on TikTok, but

**Harry Stebbings** [14:03]:

Every night, I actually watch it from twelve till 12:30, and then I send my team notes on what I think works and doesn't in transitions, fades, music. Yes.

**Victor Riparbelli** [14:11]:

I do exactly the same thing. I think TikTok is a great example of how how video truly can be the default of how we consume information, right? There's almost no text left in the interface. Even comments, right, people people respond to comments with videos. And so they've really started to build out this graph of like how we communicate with video as like a default video. There's still a long way to go, but if you believe that that is true and that not just your TikTok scrolling at night, but if you're trying to buy a software product, you actually don't wanna read a whole bunch of stuff and jump on calls with people, you wanna watch a video. And at some point, you probably wanna watch an interactive video, right, where you just, you know, with your voice, say, hey, can you show me how this functionality works over here? And the video will just like switch over to that. And when you do custom support, right, you're not on the phone, you're reading long knowledge articles, you're watching videos, again, probably they'll be interactive. Then all the world's communication is the market, right? And so when we started the company, we always talked about and we still, you know, it's a very important part of our thesis is that our market is not video production because all video production today, that's an interesting market, but all of our all of our market is text. Right? Text and slides is the market that we are targeting, and that market is infinitely big. And if you manage to capture just 5% of all the world's text communications and turn that into video, I think you have probably more than a $100,000,000,000 company.

**Harry Stebbings** [15:26]:

We're gonna go into kind of future and how we see the future. I do just wanna remain on the actual funding. Yeah. Is it bad to raise money to dissuade competitors to win a market and use capital as a weapon?

**Victor Riparbelli** [15:37]:

I mean, I think it can backfire if you don't know what to use the capital for. You start doing stupid things. Right? But

**Harry Stebbings** [15:43]:

is this round a signal to other people, don't fucking come here?

**Victor Riparbelli** [15:48]:

I mean, sure, it's a part of it. Right? But I think more than anything, this round is raising the capital to build the best product in the category. So, I mean, every time you raise the signal, like hiring people, you send signals to competitors and to VCs, etcetera. But that's not the I I have never made a decision to Synthesia based off what our competitors do or don't. I think that's that's a bad way to run a company. Do you not pay attention to competitors? Call you pay attention to competitors, and now we have lots of them. Right? I think it's great to have someone to kinda play ball against to some extent. One of the interesting things about Synthesia is that when we raised our A to B to C round, it was very much a secret how fast we were growing and how much people loved the product. A lot of people looked at it from the outside like, oh, yeah, there's like a few people in like learning and development and training that thinks it's like a cool thing to spend time on making these AI videos. Right? And what we actually saw from the inside was, holy shit, this is huge. And and training and learning was the first market we targeted, but this is clearly just the beginning. But from the outside, it looked like, oh, it's this cute UK company doing these avatars. It's kind of fun, but most people probably don't use it for anything else than just making a fun video for their mom. And so for many years, we had to market to ourselves, and then slowly people started to realize that, okay, actually this is maybe not just a flash in the pan cool demo. Maybe there's something real under the hood. And so we started getting a lot of competitors. We have one particular competitor that, I mean, literally verbatim copied our mission statement, like everything I say. They they, like, just copy everything that we do.

**Harry Stebbings** [17:09]:

Who is that?

**Victor Riparbelli** [17:10]:

They know who they are. But they they copied everything that we do from the the way we talk about the product, talk about the market. Of course, that's annoying, right, but that's capitalism. That's good. And then eventually, you start to learn from your competitors. They do something right, they do something wrong, and it's actually very helpful. It's really difficult to pioneer space because you have no feedback loop except for whatever you do and how the market reacts to that, right? And seeing what competitors are doing and seeing what works and what doesn't work is extremely powerful. I think for us, at least, that's been a very powerful thing for us the last twelve months. I think the reason that we had a massive re acceleration in kind of the second half of the year, and a big part of that is actually because our competitors did a whole bunch of marketing for the category. We clearly had the superior product, so that actually helped us quite quite significantly. I don't think you always have to be the first to do something. If you're good at being a fast follower, that's also very powerful. It's a different way of running the company when you have a lot of, like, feedback signals in the market around you, but it's much more fun, and I think it helps you get to the right answer for your customers much faster, which ultimately is the most important thing.

**Harry Stebbings** [18:13]:

Dude, before we kind of dive into kind of journey and elements there, I do just wanna discuss AI landscape today. Yeah. A lot of I I speak to so many CEOs, and they're like, Harry, you and your tech bros, you sell me the ROI to enterprise. We're still kinda waiting. Where are we at in the AI hype cycle cycle today?

**Victor Riparbelli** [18:32]:

I think that's pretty spot on. What I see a lot in the enterprise is buyers don't really know what they want. A lot of people have been told that they need to have an AI strategy, they need to execute on an AI strategy, which means they are very willing to have conversations. They're also very willing to spend their innovation budgets on doing things, but they don't really know what they actually need and want. They don't understand the technologies well enough to kind of themselves figure out what do they need for their business. And that is both an opportunity, but I think it's also a problem for a lot of AI startups that doesn't have that customer obsession. It's great because you have a lot of budget available and people are extremely willing to do things and sign up for pilots and POCs because they wanna deliver to their boss that AI strategy. But when they don't know what they actually want, it's very difficult to prove the ROI to them. Right? So what's

**Harry Stebbings** [19:19]:

the problem? Is the implementation?

**Victor Riparbelli** [19:20]:

I think the problem is that to be successful today as an AI company, think you need to be extremely customer centric. You need to deeply understand your customers. What are their problems? How can your product help solve whatever specific problem that they have? Now, that sounds like pretty obvious, right? That's not like AI specific. But the issue is that today there's a lot of companies who do a lot of cool technologies and they go out and they kind of convince the customers that whatever they're building is the right thing. It'll help solve some big problem for them. But maybe it doesn't really work or they haven't understood the customer's problem deep enough. And so you now have this thing where the AI startup kind of thinks that they're delivering real value, but actually it's not a good signal because on the other side, you have a buyer who's like, just spend a lot of money on doing something, and they'll say, yeah, works really well because they just spent $100,000 in doing but eventually they will churn, right, because it doesn't actually work or doesn't actually do the thing that that you want it to do. And so that's a problem because the AI startups think they're doing the right thing, think they're delivering value, but at some point you're gonna be hit by that wall of churn where all your 12 contracts begin to phase out because you're not actually delivering value, right? Are we seeing that wall of churn moment now? I think a lot of companies are seeing that big time, right? And I think what's very unique about AI the last couple of years is that people are extremely willing to part ways with their money. People don't mind paying on a consumer level like $30 a month to try out something that looks cool. Enterprise level, sign up for 50 ks pilot to do something. But the real signal is not that you sign a contract. The real signal is renewal. And I think there's too many AI startups who optimize or have optimized too much for, like, closing new contracts, not for the renewal. Right? If you optimize for the new contracts, not the renewals, unless you've hit the right thing, which, of course, some people do, then you're in for a whole whole bunch of trouble.

**Harry Stebbings** [21:00]:

What do you think is the biggest misconception people have about where we are today versus where we really are?

**Victor Riparbelli** [21:05]:

I mean, I think we're definitely in a bubble. Right? I don't think that's necessarily a bad thing. I think that's how capitalism works. Right? For a lot of money, a lot of products at the world, and you try to do, like, a million different things at once and you kind of see what sticks. And that's the right way to innovate. That's Darwinistic by nature. But I think there's a lot of there's a lot of money that's gonna go up in flames in AI products that either just aren't that valuable or things that eventually become features in some of the big cloud providers.

**Harry Stebbings** [21:29]:

What is getting money today that people think will be very valuable that you don't think will be?

**Victor Riparbelli** [21:34]:

Buzzwords always kinda, like, take me out. When people say they're, like, building AI agents to do all sorts of different things, that always, like, lights up my bullshit detector a little bit. But I just feel like when you're like overly obsessed about like the technology and like the latest buzzword, that's usually like a yellow flag for me. Maybe I'll give you one concrete example. I really, really hate it when people call like AI employees. I think it's so dumb. I think it's not helpful to build useful technologies that people want to adopt, and I just think it's the wrong way of thinking about that you're gonna have like AI employees doing all sorts of different things for you. These are algorithms. It's a piece of software. Like, you wouldn't say that like Myro or Figma is like an AI employee that like sits and takes people's design and and put it onto something. Right? I understand that it's because people think these things gotta be making decisions autonomously, but I just don't think it's that different from software that we already know.

**Harry Stebbings** [22:18]:

Did you agree with Zuck in his Rogan episode when he said by mid this year, we're gonna have AIs that will be as capable as mid level software engineers?

**Victor Riparbelli** [22:28]:

I think in general in the tech industry, we're very good at, like, setting really high expectations and then not always meeting them. I always strive with these, like, hype cycles to, like, stay positive but rational. What does that mean? Well, it means like, yeah, sure, probably at some point that will happen. I care most about what I know to be true today and in the next couple of quarters, and I'll kind of adjust our strategy based off that. I think it's very clear we're gonna have very capable AIs that can produce software. I also think when I speak to a lot of developers that, I mean, we're not at the point yet, right, where you just like sit down and say, hey, build me, like get the next social network with these functionalities and just comes up with it. I think building software is a lot harder than that. And I think what we see a lot with I have seen in the last two years, a lot of cool demos, and that's great. That's a good start, right? But what we really want to see is this applied mass scale in production because you can prompt a Tetris game in the browser or something like that. That's great. But if you look at most software out there today, it's very complex and it's not just technology, right? It's lot of humans, it's customers, it's feedback loops, and I don't think we're anywhere near being able to automate those things. But I definitely think that a great software engineer will be way more productive in the next six, twelve to eighteen months. But, you know, there's some, like, podcast at some point, especially like twelve months ago, like, all software is dead, right? In the future, it's gonna be, you just gotta go on to, like, whatever LLM. You're just gonna say, make me a copy of mondi.com. You're gonna deploy it. You're gonna sell at one tenth of the price. It's gonna be great, and all the existing come into that. And I think that's like a really, really naive view of what it's like to build a business. Technology and lines of code is super important, but as you know, right, you've built your company yourself. It goes way deeper than that, and I think it really for me, that's things that people who've never built operate a company.

**Harry Stebbings** [24:06]:

But it also assumes that you're gonna continuously upgrade and improve them yourself. Can you imagine having to continuously upgrade and improve 150 different internal tools? Totally agree. Unbelievable. Speaking kind of rational and clear mindset around where we are today, I think everyone acknowledges that we're seeing the complete commoditization of foundation models. Do you agree with that from what you see, and how do you see the foundation model landscape evolving?

**Victor Riparbelli** [24:32]:

For sure. I think what it'll come back to, as it always does, like distribution is king and great products are king. And of course, there will be new LLMs that'll be better and more powerful, as everyone else is excited to see what GPT-five kinda has in store. But I do think we are seeing the commoditization of the text generation layer, right? For most of the use cases that we'll see LLMs transform the worlds we know it today, I think the current generation technologies are good enough. It's about, of course, improving the base models, but it's a lot about building the product, the scaffolding around it. I definitely think we are seeing that, right? Like if we're seeing x and Elon Musk catching up pretty quickly and Anthropic has a really great product, a lot of people prefer those models over OpenAI's. OpenAI has a huge distribution mode, and I think they've really managed to capture, like, the consumer version of the world here, and that's definitely gonna be really viable. But I think it's a lot of distribution product from now on.

**Harry Stebbings** [25:23]:

So you've got $10,000,000. Okay? And you can put it in OpenAI at $1.60, Anthropic at 60, or Axe at 50. Which one would you do?

**Victor Riparbelli** [25:33]:

I would do x because I think there there's the most asymmetric upside if Elon delivers what he usually does. We've all heard of that data center that he built in ten days or something, right? I think I would just never bet against Elon, and I think the upside potential there is huge. And I also think the fact that he owns x is really, really powerful. OpenAI clearly managed to capture the consumer as in the destination that you go to to use an LLM. I think we'll see LLMs being a part of many different apps, and I think owning x along with building the LLMs is actually really powerful, especially for the real time information that will be able to feed into the models directly from x, and the fact that x, of course, already has, like, hundreds of million users that that, in theory at least, could start using their LLMs rather than going to OpenAI.

**Harry Stebbings** [26:21]:

What is the differentiator that will create the winner? Is it data? Is it you know, a lot of people have said to me, x because of Elon's access to compute. Is it distribution where OpenAI would win? Is it data where you could say OpenAI or x would win? Which one is it?

**Victor Riparbelli** [26:36]:

Clearly, there are still gains to be made from scaling, I think, especially if you look outside the domain, but like in video, audio, etcetera, three d. So you agree that scaling laws will continue? I think they will continue, but I don't think it's just gonna be linear, like whoever has the most compute is gonna win. The world rally works in those ways. Something will happen, right? Someone will come up with an algorithm that can that is like 10, a 100 times as efficient as what it is today. I I think compute is important, but I actually also think data is actually, I would say compute algorithms and data, maybe. I think in algorithms, what what everyone is trying to build into models in AI systems today is control, right? We've proven these things extremely capable at replicating the real world, producing video that looks real, audio that looks real, text that sounds real. But what we all really want to do is get a deeper level of control over these things. In my world, right, it's like you have some of the big video generation models. I can't delineate what we do versus what SARA does of Runway or something like that. You take SARA and Runway, these models, extremely capable, extremely powerful. Powerful, right? You type something in. Basically anything you type in, it'll actually spit out. And that's really, really powerful and it's a great demo, but to really be able to use this, you have to be able to say, I want this same character in a different scene. I want the character to say this particular Like, there's so many layers of control and those are very hard to build in because every time we try to build them in, it decreases the overall fidelity because all of sudden you're trying to make the model do what you want it to do rather than just replicate whatever it real kind of looks like. And so I think getting those layers of control in is gonna be difficult. I think that is gonna be of algorithms figuring out, like To what extent is Grok's

**Harry Stebbings** [28:06]:

lack of layers of control a problem or a benefit?

**Victor Riparbelli** [28:10]:

Well, is controlled in, like, content moderation, and then there is, like, in controlling the output. Right? So the thing that I'm talking about here is, like, the slot machine kind of thing. You type something in, you get something out. Then you try and change the problem, but you pull the slot machine again, right? And it's very frustrating for trying to get to something specific because the model just doesn't really put it out. You want have some degree of control in there. I think on the moderation, that'll be interesting to see how going to pan out, right? I think we're definitely in the middle of like a vibe shift with Soccer Park also pulling back moderation, which I think in general, I'm I'm in favor of that. I don't think that like humans moderating content is the right way forward. I think community notes.

**Harry Stebbings** [28:44]:

Do you think

**Victor Riparbelli** [28:44]:

that made

**Harry Stebbings** [28:45]:

the right decision to pull back on moderation?

**Victor Riparbelli** [28:47]:

We've all seen the statement. I don't have the actual details of it, but I think it is directionally correct that having humans sitting down and evaluating content is not the right way of doing it. I think what we've seen with products like Wikipedia, for example, is that the collective power of people working together to arrive at some sort of truth is really, really powerful. And I think community notes is kind of like taking that Wikipedia way of thinking about the world and trying to implement that into every single piece of content. And it's not easy and it's not solved yet, but I do think that is the right way for us to have some degree of control of what people do and say. Where it gets really messy is this kind of gray content. We have the problem at Synthesia as well, right? We have basically a product internally for content moderation. The hard thing is you have what we call the green content, the content that everyone agrees is great. That's 99.9% of the content. You have the red content, hate speech, violence. Most people will agree that that's bad as well. Then you have all the gray middle and that's where it gets difficult. I think this is the content that Sock is talking about here where he's gonna let off controls. This is essentially like you're making cryptocurrency content, for example. When is it like a really enthusiastic entrepreneur who just started a new coin that he or she definitely thinks is gonna change the world? When is it an outright fraud of like trying to get well meaning people to dump their money into something they think is going go up 10x? Those lines are very difficult to draw, right?

**Harry Stebbings** [30:03]:

And like, bluntly, is Synthesia liable? Are you the arbiter of justice on what is good or what isn't? Also, if something is an opinionated rant that I put out there, maybe it's right and fair, but it upsets a lot of people. Do you see what I mean? Are you the arbiter of right and wrong?

**Victor Riparbelli** [30:17]:

Yeah. So today we are, and that's a decision that we have made. We had a lot of discussion about this in terms of how do you what's our approach to this problem? And for me, it again comes back to the customers, right? We're an enterprise product. It's important that the avatars that we have are not seen to be used in all sorts of wacky content online. We don't, as a company, have We don't see ourselves as having to uphold any kind of right of free speech. And frankly, from a business perspective, having someone pay me $30 a month to create very questionable conspiracy content is just not good business. So for me, all of those things kind of lined up. Our enterprise clients, they don't want avatars to be affiliated with content that doesn't kind of match their brand, and economic for us, it just doesn't make sense. So we've taken a very strict approach, which means that we are actually going and being the arbiters of truth, and we definitely have people who are unhappy with that.

**Harry Stebbings** [31:07]:

Staying on models models before we go down this rabbit hole. Just in terms of models, I obviously speak to many investors over the last eighteen months. And when Synthesia has come up, bluntly, they've said, like, amazing and amazing what they've done, but OpenAI are gonna move into this. This is the most obvious play for OpenAI to move into. This and customer customer service service is is always always kind of the two. How far do you think model providers go into the application layer, and how do you assess that?

**Victor Riparbelli** [31:32]:

I think this is like classical VC brain. Too much focus on the technologies, right? Like, you know, you speak to think there's a big misconception about Synthesia is that we're like an avatar company, and it's kind of a fair assumption to make because you go to our website, if you, like, see about us online, like Avatars is a headline feature for the company, right? It's one of the things that made us where we are today. If you go and talk to our customers, they don't buy us for the avatar model. They buy us for the workflow. Like the way we've taken the entire video value chain, you get an idea, so you make a draft for that video. You don't have to use a camera or a voice over artist, right, because we have the AI models for that. We give you a great editor, like using PowerPoint or Canva. We give you a distribution mechanic with an AI video player that's made to serve multilingual content. The list could go on and on. Right? You talk to our customers today. The reason we have million dollar plus contracts is not because people are like, oh, I wanna make an avatar video. It's because they wanna convey a message to someone and they wanna do that with the highest efficiency and engagement and in the best workflow, frankly speaking. And that is so much more than just the models. So, of course, we wanna win on the models and we are gonna win on the models, and our specific niche here is humans presenting content, right? Whereas all the other companies, yes, SARA, Runway, all these guys are doing amazing AI video things, but they have a much, much kind of wider merit of what they're doing. They're trying to build true foundation model video models, and maybe we'll be customers of those one day. Maybe we'll be partners. The only thing I care about right now is voice overs and humans presenting to the camera. Right? And I think in that niche, and if you take the entire platform as a whole, that's how we win. I think that's something we're gonna see the next couple of years is that the winning companies are gonna be the ones that are not overly obsessed about the AI component of their platforms but who build for workflow. And I think, you know, as I move into going to 2025, model's super important for us, but expanding across the value chain, we increasingly need the publisher of videos for our customers as well, which means that instead of like using YouTube or another kind of enterprise video hosting platform, they use us directly. And I think that's where you're gonna see a lot of the value being created. There's gonna be a few foundational companies that'll be very big. They already power us with, know, of course we use OpenAI, use Anthropic. What do you use most and has that changed over time? We're most using OpenAI.

**Harry Stebbings** [33:38]:

Is that shifting more to Anthropic?

**Victor Riparbelli** [33:40]:

Yeah. We shift some workloads to Anthropic. We're also using Gemini, actually. I think in general sense is that it's a lot about, like, pricing. Some models are definitely, like, better at things than others, but we have, like, a lot of, like, workloads that that or big workloads moderation, for example, is one of them. So I think pricing is important and, again, like the scaffolded infrastructure around it. How did you think about

**Harry Stebbings** [34:00]:

the question of whether to build your own models? How do you think about that?

**Victor Riparbelli** [34:03]:

We only wanna build models if we think we can be the best in the world at it, which in general for us means that it's a narrow domain and that it is directly tied to a bigger workflow. And so we always work backwards from what our customers are trying to do. If we think we can be the best in the world at it and we think there are compounding advantages of building that model, then it's great for us. And what that means very specifically is that for humans presenting to camera, to dialogue driven content, that's what wanna be the best in the world at it.

**Harry Stebbings** [34:31]:

Do you think in the future we will have a world of many smaller models that are specialized, or do we have three general massive models?

**Victor Riparbelli** [34:41]:

Yeah. I think there will be some concentration for sure in the big companies. But it's kind of interesting because, like, specialized models, right, it's still very technology centric. I think there'll be many, many, many different that people use in their daily lives to run their businesses, and a lot of those will probably use models that are like an open source thing that's kind of tuned specifically for something and integrated into an overall platform. And if you think of that as a specialized model, then yeah, I think we'll see a lot of specialized models, but it's very like tech industry to talk about models all the time, right? Like, I think most people, we will interact with models like we do in ChatGeebings or whatever today for sure, but a lot of like the things that you won't notice as a consumer when you're just like using someone else's platform or product, there'll be a lot of like workflows in background that are also driven by LLMs. You'll definitely see a lot of companies building their own specialized LLMs, right? But I think we should think more about like products than models.

**Harry Stebbings** [35:31]:

Final one on models then. We talk way too much about Final one on models. GPT-five has taken so long, dude. Everyone is like, ugh, when's it coming? It's been delayed, delayed, delayed. How do you think about the delay, and do you think it will surpass expectations or fall beneath them when it does release?

**Victor Riparbelli** [35:50]:

I think it's gonna be incredibly difficult to do anything that can mirror the ChatTipTee moment when it first came out. As humans, I think we saturate incredibly easy. We often forget how crazy just like tippity free actually is when you use it. Right? So my sense is that when they release something, it'll probably be good and there'll probably be a whole bunch of tech nerds who'll be very excited about all the things you can now do. And maybe I'm wrong and it's just like super intelligent thing. They'll just like self improve and save the world. But I think it'll come out and it'll be like good. It'll be definitely better than the previous things, but I think most people will not like care that much because the bar for someone to really care that much is incredibly high, right? And there's all this talk about is it like AGI is not AGI, and I think all those things are kind of riddled, like what's the definition of AGI, right? If you took ChatGPT two hundred years back in time, right, in England, and you showed someone this magical thing you've built, you'd be burned at the stake. If you did it fifty years ago, people would definitely think this is AGI. I am talking to a computer that knows everything about the world. This is absolutely batshit, right? And then today, feel like, oh, it's just a stochastic parrot, and I don't know what's true or what's not true there. I think it'll be very powerful. I don't think it'll have as much as kinda like the cultural moment that ChatGeebency created initially. And as I said earlier, I think elements of this that there'll be like a small group of people who really care deeply about what benchmark does it work against and it's like slightly better in this area and in this area. And I think that's awesome, but I think for the average business around the world, the current models are already pretty good and can solve a lot of problems.

**Harry Stebbings** [37:22]:

One of my favorite quotes is Eleanor Roosevelt, and this is what I aspire to, not necessarily what I am clearly. But she said, great minds discuss ideas, average minds discuss events, and small minds discuss people. But I wanna discuss the future across a couple of different segments with that in mind and, like, discussing ideas. When we look at the future of content creation this is my life, dude. Yeah. What does the future of content creation look like in, say, five years?

**Victor Riparbelli** [37:47]:

I I think what has happened in very broad strokes is that we democratized distribution with the Internet. There are no gatekeepers. Anyone can make a website. Everyone can share their content online. That's been really, really powerful. Then we saw, to some extent, the democratization of content creation because all of our smartphones have cameras in them, the price of camera equipment dropped, all those things which, I mean, this setup, like, thirty years ago would probably have been like a 100 x the price of what it is today. What's about to happen now is that we're truly gonna democratize content creation. We're gonna change the world of making content from something that you need to where we capture things with sensors in the physical world to being able to generate everything digitally, right? And that's going to have huge implications. When you think about text, that's just like a fabric of society. We don't really think that much about text, right? But text went through this journey of like, you know, the printing press is like one of the first really big inventions around text. Then we invented the keyboards, the computers, and now text is everywhere and everyone can create content all time. It's entirely digital, right? And that's really powerful. With something like music, we've somewhat also seen that go from being something we generally do in the real world and capture with sensors to something we can do digitally. So most music today is not made with real instruments, right? It's made with software instruments. I can recreate almost any song I want without real instruments. I can synthesize that on my computer. And that changed the music industry in many, many, many, many different ways. And I think we're to start to see the same with the video and audio industry where you are going to be able to bring your ideas to life without needing much more than just your imagination. And this is gonna have a whole bunch of effects. Most obvious one is that the price of creating content is gonna go to zero. Just like it costs you nothing today to write a book, everything is free. In the not too distant future, the price of creating a Hollywood film, from a purely technical perspective, I think is gonna be zero as well. That's gonna mean we're gonna have a deluge of content, an absolute deluge of content. It means that people like yourself, YouTube creators, everyone else can compete with Hollywood in terms of what they can bring to life. Today, there's like still the separation of like Hollywood content, so like all the Netflix series that we watch, the really high production value things, and then there's like the YouTubers who can do like prank videos and podcasts and kind of like fun things. But like even for for you, right, it'd be very difficult for you to make, like, a Hollywood style production because it'd just be like it'd be very, very, very expensive. Right? That's gonna, like, flatline, which means that the best ideas and the best content is gonna win, and I think that's gonna be pretty

**Harry Stebbings** [40:04]:

I think we are so far away from this. This is someone who creates content for a daily living. Yeah. When I look at the clipping tools, they are so far off what my team is able to do upstairs. Yeah. It's incomparable. I don't see that being two years out. There's there's a lot of knowledge involved. It's highly ambiguous what bit's important of this episode. Depending on what we wanted to achieve, we could totally cut six different bits as being the best for a highlight reel. And so I find these, like, clipping tools as, hey, everyone's democratized. I think content's less democratized than ever.

**Victor Riparbelli** [40:38]:

Yeah. And I totally agree with you. I think a very important delineation is when I say that you're just gonna need your imagination, that doesn't mean that it doesn't require skill. Right? It means that the kind of sort of technical barriers, you don't need to have a camera anymore. You don't need to be necessarily like amazing at visual effects. A lot of the stuff will be able to be done automatically, but it'll put more emphasis than ever on being a great storyteller, understanding what's important, on asking the right questions, on if you're creating fictional content, combining things that work in the cultural side guys but still stands out a little bit enough that it's interesting for people to watch, right? So I think all those things will be more important than ever. What would be less important? Well, knowing the right people to distribute your content, having spent like eight years in becoming the world's best visual effects artist because you can get a lot of help with that from AI systems, but the storytelling piece is gonna remain exactly the same. And I also think what we are gonna see is that the value of real content is gonna be higher than ever because we have a of AI generated content, and I think that'll be a genre of itself. But just like we still like to watch people play piano or know that someone that the artist we're watching is actually, like, a real person, I think that will carry over to this world as well.

**Harry Stebbings** [41:43]:

Will we have more human made or AI made content in five years?

**Victor Riparbelli** [41:47]:

Definitely AI made content, for sure. But I think what's actually more important is what content surfaces, right? Because if you go to YouTube today, I mean, it's like I don't know what the status, but it's probably like 95% of all videos have, like, less than 10 views or something. So the content is there. It's a matter of, like, what what actually gets surfaced. But

**Harry Stebbings** [42:04]:

this was my point, which is when you reduce the cost as much as we are here with AI and we increase supply side so much, What is the future of discovery?

**Victor Riparbelli** [42:12]:

I think a lot about this, and I think I think TikTok is actually a really great product, potentially like a bit of an unpopular opinion. When I look at my TikTok feed today, I would say it's 90% highly informative, educational, really great content. It's about music production. It's about the music that I like. It's about politics, about tech. I see your face once in a while. I think it's an amazing feed of interesting people. What TikTok has done really well is that they built the graph based on your interests, not on your kind of social connections. There's a bit of that as well. And I think that model is actually extremely powerful. What I do want to see is a bit more control over your algorithm, right? So today it's basically like I think think everyone has this intuitive thing, which is like if you see content you don't want to see more, you swipe really quickly because you know the algorithm will kind of notice that you swipe quickly past that, so you're kind of almost trading the algorithm to yourself. I think that's like an awesome way of doing it, but a bit more control. Maybe we can say like these particular topics just don't show it to me. I'm not interested in it. And then I also think what TikTok has done really well is because they have this really great interest graph, they know a lot of people who are very interested in specific areas. When you post a piece of content yourself, they basically show that content to, like, a couple of 100 of people and they quickly sense, do those 100 people like the content or not like the content? Right? And if they don't like the content, you go in the trash. If someone kinda likes it a little bit, they'll show it to a bit more people and they'll try to figure out what's actually great content. I mean, you look at TikTok's usage, right, I think that's very clearly working really well. Should TikTok be banned? I tend to believe that it's a moral panic more than anything. Clearly, TikTok has built an amazing product. I don't think it's a brainwashing machine. I don't think it's a propaganda machine.

**Harry Stebbings** [43:45]:

My thing is like the denigration of social media, which is like, to your point, you said it's educational, it's about music. Mine is like motivational speeches, air fryer recipes, and like workout routines. Mine is highly additive to my life in positive ways. Just like a diet can be chocolate and sweets or, you know, vegetables and fruit, you choose your own content diet, and that is a human responsibility. I think it's unfair to demonize social.

**Victor Riparbelli** [44:13]:

I totally agree. And I think that's the paradox because probably for you or maybe for me, like, built algorithms to be productive to our lives. We're kind of starting to find our way into, how do we build a really awesome media ecosystem that is driven by citizens and experts rather than journalists and politicians, and where we still have some of the control that you can argue has been good around the previous generation of media where a few corporations owned the newspapers and there's this chain of command of like before content goes out the door, it's been reviewed by, like, six different people. I think what just always happens in the world is that we invent new things as humans and we learn as we go, right? And there are definitely some negative consequences. I don't think anyone would disagree with that, but I think we are finding our way. I am actually very optimistic about the future moving into.

**Harry Stebbings** [44:57]:

I also think the quality of the content that you consume is inherently better. I mean this in the nicest way, but I think the content that we produce on venture capital is inherently 10 times better than the content that a journalist or a large publication produces because it's my job day in, day out. I live and breathe this.

**Victor Riparbelli** [45:12]:

Yep. Exactly. Exactly. I did a TED Talk, like, a few months back, but I could talk about this. I I but I could talk about this because I think this Sorry. You did a TED Talk?

**Harry Stebbings** [45:22]:

I did a TED Talk. You made it. Big thanks. That seed round.

**Victor Riparbelli** [45:28]:

No. What I actually talk about there is that my my kind of, like, provocative opening statement is that we may be the last generation to read and write. Right? And I think there's lot of, like, moral panning about TikTok, for example. Like, are people's attention spans decreasing massively? And maybe those are real problems, but what if we're just tired of overly dense, long, boring content? And that actually a two minute long TikTok video is a better way of understanding a topic than a twenty minute long YouTube video, which is a better way of understanding a topic than a 300 page book. What do you

**Harry Stebbings** [45:57]:

say to the fact that we're just then dopamine junkies getting jacked on two minute clips because we can't be asked to read a five minute piece?

**Victor Riparbelli** [46:04]:

I think dopamine junk is for everything. Like, I think that's how we govern our lives most of the time. Right? I mean, I I totally get the analogy, but is it all the dopamine addiction if you do sports every day? Whatever thing you do that, like, makes you feel good, I think most of the things we we do risk to try and make ourselves feel good in some way. One of the problems is, like,

**Harry Stebbings** [46:21]:

identity misuse or fraud. How do you think about the future of identity verification, both for you and cross platform?

**Victor Riparbelli** [46:27]:

I do think we need some degree of identity verification for some of the big spaces that we use. I think we need to know somewhat where content comes from. Who created it? When was it created? How was it created? So I think we need identity verification to some extent, but I also think we need to take that all the way down to kind of like the content level. So if you imagine that you fingerprinted, you know, Chasam, the app on your phone? Of course. Yeah. If you imagine you had like a Shazam, for every single piece of content on the Internet, you could say, hey, this picture was originally uploaded, you know, like five years ago. It was uploaded first time by like Harry. Maybe in the future it also, like, this was partly made with Synthesia. You're watching a dark version, so this is kind of AI for translation. Whatever kind of signals we can give around content. If you had that and identity verification and community notes, every time you scroll past a piece of content, you would see if it's verified or not verified. Today, everything well, it's changed a bit now, right, but it used to be that only celebrities had verified accounts. Why was that? Well, that's because a lot of people tried to make an account pretending to be some celebrity. And so as a consumer, when you see that trusted verified sign, that tells you that that's actually the celebrity posting that content, right? I think we should try and flip that around so that everyone and all content is kind of verified if we have the provenance trail of it. We know kind of where it came from, maybe how it was created and some other kind of things around it, and that'll give you like a green checkmark on that content. And it should stick out like a sore thumb if something is not verified. So if there isn't a fingerprint for the content, if we don't know where it's from, that should be the thing that sticks out, not the kind of verified sign on a celebrity's page. Does that make sense? Yeah. Does that

**Harry Stebbings** [47:52]:

not inherently lower the value of your content, though? Why would lower the value of your content? Because your content is AI generated, it wouldn't have the green tick.

**Victor Riparbelli** [47:59]:

No, because I think that I think right now, it's like, is it real or is it fake? We're already in a world where, like, most content that we consume today is, to some extent, fake, right? Like, most pictures on Instagram have been, like, touched up in some way, shape, or form. When it leaves the sensor, they already do, like, color corrections and a whole bunch of other things. And so I think this line will just increasingly blur, and I think it'll be less about how you made something and more about the content itself. You could make a video of you talking about something, and in a couple of years no one will be able to tell if it's actually real or not, but it won't really matter that much. What matters is that you made it, right, and that whatever you say in that video is something that you actually wanted to say more than how you made it. It's a bit like we don't care if content uses green screen today. We don't care that much if when you go to see a Hollywood film, right, I know that's fiction, but you don't care how it's made. You care if it's a good film or if it's a bad film. Yeah. We should evaluate content based on the content itself. And in here, how it was produced certainly is a signal, but it's also signal. When was it produced? Who produced it? Are you watching the original version? Are you watching an edited version of it? It's really hard, right? It's because it's like right around the corner, but you can imagine a world where you can begin to build a chain of like, where was content originally created? What happened to it since? Are you watching an edited version? Maybe you're watching a twenty five second outtake from Harry's podcast show and you wanna watch the full segment. Click here. You can trace it back to actually watch the full episode. We can begin to build these kind of things. And the reason I mentioned Chassam is that Chassam exists because this was a commercial problem for essentially YouTube, right? Record companies were telling them, hey, people are uploading videos on YouTube where they're using copyrighted music. We're gonna sue you out of existence. If you don't fix this problem and pay us some money. I said, what do they do? Well, okay, what do we have to detect if something is actually copyrighted, right? So when you upload a video to YouTube, as I'm sure you know, they'll scan it and if there's copyrighted music in it, it'll either either take it down or most of the time, it'll just put an ad in the middle of it and it'll pay something back to the license holders. Now, what's actually happening here, right, is that you're uploading a piece of content and in, I mean, milliseconds, that piece of content is held up against a database of billions of songs. From that little short clip, like a four second clip of a song, it actually identifies in milliseconds what song it is, and if it's a copyrighted song, they'll put something in there. So if you imagine that happening as well, you upload a video and I upload a video on my channel maybe with this interview, right, but I've cut out ten minutes of it. It'll just say, this is actually a piece of of this is a clip from Harry's original podcast, which was released two weeks prior to Victor putting this in his YouTube channel, and if you wanna watch the full thing, can click to it here. So we begin to build this chain of content and we can identify where things came from. That does require we have a centralized database, decentralized ideally, right, where you just write every time you make content, no matter if you're making a video on Synthesia or taking a picture with your camera. You register it in this I kinda hate to say it, but it could actually be a blockchain, where you register the first time a piece of content was created and we then upload content to different social platforms or distribution systems. You check it against that just to see if disinformation one the big problems about the what people mostly do, right, is that they take a picture from a war five years ago and they say, This happened yesterday in whatever country. And if you had a system like this, if I tried to do that, actually what it would do is it would say, Well, this picture was uploaded five years ago. So when you're looking at this picture, it'll have a little blog of notice under the community notes, right, but the automated version of community notes saying this picture was actually taken by a BBC journalist like seven years ago. A lot of the stuff is hard, but we actually have a lot of pieces of the technology to get there. And I think when we think of like content identity verification, we think of moderation, creation. I think we are beginning to see the birth of an entirely new content ecosystem that will look very different than what we have today.

**Harry Stebbings** [51:28]:

How will that new content creation ecosystem change the labor markets of content? And what I mean by that is which roles are legitimately threatened and which will be created?

**Victor Riparbelli** [51:39]:

I think the very technical roles, like camera operation, those types of things, they'll probably, like, fade away, and I think a lot of emphasis will be put on creativity, storytelling, being relatable. All those things that makes great content, I think will be more important than ever. It's

**Harry Stebbings** [51:57]:

a bit If you're like a thumbnail designer today or a visual effects person today, like, who is threatened and whose job's gonna be created?

**Victor Riparbelli** [52:05]:

I actually think that most of those roles will have a natural transition to something different, assuming that you're open minded enough to do it. So visual effects, for example. Right? As we talked about before with, like, making clips, AI can do a first pass asset, which may be better than random, it's way worse than what you can sit down and do yourself, right? But you plus AI can probably be really, really good, right? Because if it's a two hour episode, it just figures out all the right plays that could be interesting and shows you that, and you can kind of choose for yourself. If you're a visual effects artist, probably what it means that you'll, just like a software engineer, right, means that you'll probably be a 100 times as efficient, instead of relying on 20 other people to create a digital clone of me by modeling my face, you're just prompted a control of river. I think if you're good at that, you'll be even more powerful in this new world. I think we'll have much more content creators than we have today. Just like if you look at pre internet, pre computers, how many people wrote things? Very few people, Right? Like, in the 1930s or 40s, most people didn't create text. There was specific people like secretaries and then typewriters later on. Now, all of us produce content all the time, and I think that'll be a big trend. I think most of the rate limiting and how quickly AI becomes a part of our daily life is actually not the technology. As I said earlier, I think we have very, very powerful LLMs that can do a lot of great things, but the rate limiter is people, right, because people have to use these things. They have trust these things. They have to pay them, buy them, integrate them. I mean, with technology, that's always the case. Right? It takes a long time. Dude, the final one I

**Harry Stebbings** [53:29]:

have to talk about is location. You decided to do this in London, which I love as a Londoner, but it's a different choice. Why did you choose to do this in London?

**Victor Riparbelli** [53:40]:

The honest question is because I couldn't get to The US. I mean, I didn't like, an amazing CV before I started in DGN. I couldn't get The US, like, basically, you need to get sponsorship if you wanna go to The US, right? I couldn't really get that. I wanted to start a company, knew a few people there. So I just kinda like moved on OpenAI actually and spent a year.

**Harry Stebbings** [54:00]:

So how would Synthesia have been different, do you think, if you'd been in The US?

**Victor Riparbelli** [54:03]:

I still do think that the chance of success is higher if you're in The US on the West Coast. I think there's a lot of pros, especially like the last six, seven years. It got a lot better to build here, but I do still think that there is a lot of advantages to being in in The US. But I think Europe is catching up pretty quickly. What are the pros of being here? One big one, which is talent. It kinda goes both ways in some sense. But if you look at the ecosystem in the valley, one thing is kinda like the price of talent, is just enormously high. Right? But there's other things like loyalty, for example, that I think are less spoken about. I think in The US, you have a lot of people who are very driven and they basically view their career as like building a portfolio of stock options in different companies, and hopefully one of them will kind of explode and they'll be very rich, which is a rational way of thinking about it and it makes a lot of sense, right? But it also means that it's a more transactional relationship I think people have with their employer. People are much easier to jump ship, right? They have one or two bad quarters. You may lose a lot of good people because, hey, there's this other cool thing on the block over here that I'll go to and work at instead. In Europe, I think people, for better and for worse, right, I think people are they think less like that, right? As you of course know, like stock options in Europe, people still view it as like a random lottery ticket, not really as part of their compensation because no one in Europe knows anyone who got rich off working in a startup because we don't have that many successes here. Are you seeing that attitude change? I am seeing that attitude change a little bit. It's gonna take a long time to change because the way No matter what I tell people who work at Synthesia, no matter how much they can kind of read the news and see all this stuff, what people care about is like, do they know someone, do they have a cousin who made $2,000,000 of being early in a startup? In The US, especially in the Valley, everybody knows someone who made $2,000,000 of working in a startup, and they know several of them. That makes you feel like you can do it as well, right? Here it's very kind of abstract, oh, yeah, people, these companies made. Before But we really see that, and that just requires like a bigger ecosystem with more exits, more big companies and so on, I think it'll get there, it'll take a long time. But what I think you get in Europe is you get more loyalty in the sense that people care lot about like working a place that they like working, working with interesting problems, having great colleagues, And I think that's a pro that's like less spoken about. Do think people work as hard? Honestly, I don't really have a strong sense that people work way harder in the Valley. Like, know a couple of great friends who've moved over there and opened offices. I have not heard from any of them that like, wow, people just work so insanely hard. There's probably like a percentage of people there that work like really, really hard, but I think we have those people here as well. Think that's more like a personality trait that's dispersed all across the world, but I don't think if you take like an average software engineer in the Valley that they work, like, harder than we do in in Europe.

**Harry Stebbings** [56:31]:

Why do you think it's gotten better building here? I feel it's gotten much worse building here in the last six months. Do you share my opinion?

**Victor Riparbelli** [56:40]:

Yeah. I mean, I think it's kind of very interesting to see what the new government is gonna do, right? I think they have a lot of great cards on their hand. Like, we have a lot of great companies that are actually building here. And I think what's important about what we're seeing in the London ecosystem is that we're actually building global leaders, not just like regional winners of like expense management or something like that. Like, you have 11 Labs who are leading in voice. You have us, which is leading in enterprise AI video. You have Wave, which is definitely like doing self drive. We have a lot of like great companies that actually become global leaders. I think it's really important that the incoming government doesn't screw this up because it's a massive How could they screw it up? I think they could screw it up by, like, over taxation, like, all the all the kind of usual things that I think everyone is talking about. Right? I think what they can do to make it better. Think The UK has a brand problem. What do you mean? I think we disagree on this, but I actually think The UK is a pretty good place to build in general. I come from Denmark. Right? That would have been a terrible place to build a company like that. That would have been impossible, basically. I think with SEIS, EIS, I think there's a lot of, like, good things that have happened in the ecosystem. You have all the talent. I think the venture ecosystem has gotten better. Even though it's still very PE centric, I still think it has gotten better. There's also still a lot of ways to screw it up, right? And I see a lot of people who are leaving, especially after the recent administration. My phone is

**Harry Stebbings** [57:52]:

just literally, hey. Where are you moving? What would you advise me? Where do I move to? From billion dollar founders every single day. So my question to you is you're sitting down with Kyr Starman. You can advise him on what he can do to make the best developers wanna build here, the best founders wanna stay here. What would you advise him?

**Victor Riparbelli** [58:09]:

The obvious things like, you know, corporate tax, entrepreneurs' relief, like, all those things make it, like, really attractive to build here because we are in stark contrast to Europe, which is in many places a terrible I think it's different because you're from here. You're British, right? I'm from Denmark and I think we always, with our wherever we're from, we're much more negative. I moved here and I've seen a lot of the positives around it. But I think don't screw up the fundamentals, right? Don't raise the taxes too much. Make sure we still have great relief schemes for people who create jobs, create economic productivity, and those sort of things. On the brand problem, that of course starts with the fundamentals like crimes on the rise, living costs, all those things that I think you've also been very vocal about. Those are big but those are big problems. Right? Sorry. But but what I actually would say, though, is that

**Harry Stebbings** [58:52]:

But also the consistent negativity from this Labour government. It's like stand up and say London is open for business. Yeah. Not negative, negative, negative. Sell the store. Yeah.

**Victor Riparbelli** [59:01]:

No. I agree. I totally agree on that. And I think that comes a bit back to the brand problem because I actually do think that as much as we have a lot of people here who want to leave to The US, one of my learnings has been that actually a of people wanna come to London as well, especially from The US. Like, I've I've in our journey, I've seen that it's actually easier to move people from The Valley to London than from The Valley to New York, which feels kind of counterintuitive. But a lot of people wanna come and experience the European lifestyle. Right? They like the cultural heritage. They like the fact that London is a cultural melting pot. All the things I also love about London, on a personal level, right? If you worked a bit more on the brand, I just think you could attract a lot of great people to also come here and build, but of course it starts with the fundamentals, right? Now, you look at California versus London in terms of like taxation and things like that, I'm not sure you can that say there's a massive difference, right? California is also like Super high taxes. It's very high taxes and pretty rough. So I wouldn't over index on that, but I think definitely a case of double down, right? There's a lot of good things happening in The UK and I think if we don't screw it up, we just need one or two companies to become plus $10,000,000,000 companies headquartered in The UK. Then I think we'll really start to see the ecosystem grow.

**Harry Stebbings** [60:05]:

Couple of $10,000,000,000 companies, and they crystallize those axes. Wait for it. Wait for it. And they IPO. Yeah? Where do they IPO, though? That's the point. I don't know. Synthesia, Nasdaq.

**Victor Riparbelli** [60:16]:

No. But it's a joke. I mean, the London Stock Exchange, like, they need to they need to fix that. They need to put some liquidity in the system. I don't know. I'm not a financier, I don't know what they need to do to fix it. But I mean, that is a disaster, right? And I think we've seen, unfortunately, great companies really suffer under that. A 100% you have done. Yeah. It's not very attractive. Do you think

**Harry Stebbings** [60:36]:

that's actually a problem, though, or not? Like because the answer is, who gives a shit? Like, liquidity is the liquidity in whatever market you get it in.

**Victor Riparbelli** [60:43]:

I agree. Synthesia goes public on NASDAQ. It

**Harry Stebbings** [60:46]:

still makes a thousand people in London in the office millionaires who have early stock.

**Victor Riparbelli** [60:51]:

I agree. I I don't think that's my, like, top three of things that needs to be needs to be fixed. What is your top one that needs to be fixed? Keep the reliefs for entrepreneurs, for people who create things, maybe even make them better because that's very attractive. I think there's also a whole bunch of things that you could do in terms of subsidizing GPU costs, for example, that would incentivize for, like, UK data centers. Would be interesting, right? That's an actual competitive advantage. Obviously, don't overregulate. We haven't seen much regulation yet. The consensus that there's a little bit of a wide shift from the last administration to this one in terms of regulation. Don't look at Europe as an example, right? Europe has all the AI regulation and none of the AI companies. Staying the course to some extent and not screwing it up, I think is I think is really important.

**Harry Stebbings** [61:33]:

I wanna do a quick fire with you, my friend. So I say a short statement. You give me your immediate thoughts. Does that sound okay? Cool. So what do you believe that most around you disbelieve?

**Victor Riparbelli** [61:42]:

I think that playing computer games is probably one of the best things a kid can do for, like, future success in their life.

**Harry Stebbings** [61:49]:

Why do computer games make for better entrepreneurs? Because Toby at Shopify said that if you can run a clan, it's better than university.

**Victor Riparbelli** [61:56]:

That's exactly what I did in World of Warcraft. No. Actually, what I think it is is that we are probably the first generation that really had access to, like, especially a bit more complex strategy games. Basically, what you learn throughout life is like decision making to some extent, right? And computer games is a microcosm of the universe. Right? And you can run so many simulations, and it may not look like it for parents if you're playing, like, Warcraft three or Red Alert or whatever game that you're playing World of Warcraft that you were playing back then, but actually what you're doing is you're training yourself to make a lot of decisions really rapidly and to understand what the implications of each decision that you make are in some kind of game that you're playing. But life is a game. Careers is a game. Building companies is a game to some extent, right? And I think we're just the first generation where you actually can sit by yourself and get so many iterations in that would have otherwise been impossible. Like, you can't sit down before the computer era and simulate lots of small decisions in how to run a business. You just couldn't do it, right? You had to actually build a business and run a business. Here you can play Rollercoaster Tycoon. And of course, Rollercoaster Tycoon is not like running a real theme park, even if it's just like 20% of being the CEO of a real theme park, right? I think that teaches you a lot. And so I think the decision making and kind of sense of strategy you build from that is, I think, highly valuable because it's a two way feedback mechanism. Right? You can sit down and read books about things, but I think what's powerful about computer games is that there's this kind of constant feedback loop.

**Harry Stebbings** [63:21]:

What trait are you slightly ashamed of but that has contributed to your success?

**Victor Riparbelli** [63:26]:

I am a generalist in the, like, purest sense of of the word. And, you know, when I was younger, I wanted to be wanted to be an artist, wanted to be like a great computer programmer, developer, and I just, like, never really excelled at any of them. I still have a dream of, like, making the music improve one day, but I think what I'm really good at, I know a lot of things about lots of, like, very random things. I'm just extremely curious. I'm not like an expert in anything specific, but I have a very, very wide range of interests, and I think like my neural network has been trained on like so many random things, like how elevators work through a black metal in Norway, to like how people make techno music, like all these kind of different things. And I kinda used to be a bit annoyed at myself, like, why can't you just sit down and become like, you know, the world's best music producer or like the world's best programmer, AI researcher, something like that? I think now I've realized that my power is actually the fact that I'm like decent at like a lot of things. I think especially in my role, right, what you do is you make decisions and you get ideas and you can't force those things. I think I really truly believe that those come from your subconscious, and the more food and diverse things you put into your brain, the better you get at, like, making analogies and pattern matching and those kind of things.

**Harry Stebbings** [64:29]:

Vidu told me you were the resident DJ, which I thought was a brilliant brilliant description. Tell me, the heaviest things in life are not iron or gold, but unmade decisions. What unmade decision weighs on you most?

**Victor Riparbelli** [64:43]:

So I did a degree in kinda split computer science and business at university, and I really kicked myself for not just taking a STEM degree, like a pure CS degree. Studying business, controversial opinion, is, like, mostly useless. There's been, like, 10 ideas in business, and if you learn those, you'll be pretty well covered. I should just do, like, a pure CS degree or pure math or engineering, something like that.

**Harry Stebbings** [65:04]:

What have you changed your mind on in the last twelve months?

**Victor Riparbelli** [65:07]:

I think that one of the things I've changed my mind on in this whole AI hype cycle, I think when you're in the middle of these cycles and you see, like, all these things getting funded, all these, like, you know, competitors pop up, you get a lot of, like, noise and a lot of, like, Oh, should we do these things? Should we, like, listen too much to what the market says? Like, Someone is doing this over here. And I think I just really learned the lesson again, although I think we've stayed the course really well, to never do things out of guilt of other people doing it or looking too much at competitors or what the broader kind of AI landscape is doing. Like, listen to the customer. They're the ones who pay your bills, and ultimately, they're the ones that you need to to make happy. I had a period where maybe over indexed a little bit too much on, like, what other companies are doing as, like, the AI space in general, like, what's happening there as, like, the most valuable signal as opposed to the customers. Maybe more like a relearning of a fundamental lesson than building startups.

**Harry Stebbings** [65:55]:

You can only choose one investor from your cap table for your next company.

**Victor Riparbelli** [66:02]:

I can't answer that.

**Harry Stebbings** [66:03]:

You can. I won't let you out of this room. You can choose one investor. Who would you take?

**Victor Riparbelli** [66:10]:

That's a hard one. I would take Marc Cuban again because he truly believed when absolutely no one else believed in us. I'll be forever grateful to him for doing that.

**Harry Stebbings** [66:20]:

Boom. That is a clip. You think in clips when you're me these days. Penultimate one, what about the way that your parents brought you up? Would you do deliberately differently with your future kids?

**Victor Riparbelli** [66:32]:

My parents' generation, they saw computers as this inherently socially isolated thing of you're just sitting and dopamine addicted to like clicking buttons. Exactly what people say about TikTok today, right? The reality is usually much more nuanced than I think for me when I played computer games as a kid. First of it's a very social thing, both because you play with other people online, and I think our parents have a hard time believing you can be friends with people that we haven't met in real life. And second of that is like a waste of time, right? As I said, why do think you're playing strategy games? I would sideline that with like solving math problems or like reading STEM books. Of course, everything in moderation. That's one thing I'll definitely I'll definitely encourage my kids to play great computer games.

**Harry Stebbings** [67:09]:

Every parent is, like, questioning their own parenting decisions listening to you. Final one. I presume you've had some secondaries now. Does having some secondaries have the mentally freeing effect that people often say it does? I I definitely think so. I definitely

**Victor Riparbelli** [67:24]:

think so. Not having to worry about, like, financial stress and having everything you own in one stock, I definitely think frees you up to make make better decisions. So I definitely I mean, everyone I need Angel Mess, and I definitely encourage, like, take secondaries off the table when you can. I'm 100% certain that if we take no secondaries at all, we would definitely have thought about selling much earlier, and you might have made more rational decisions. Right? This has

**Harry Stebbings** [67:47]:

been

**Victor Riparbelli** [67:47]:

one

**Harry Stebbings** [67:48]:

of my favorite shows. Like, honestly, it's painful. Like, it sucks, to be honest. Like, when someone you met years ago is now a guest on the show, it's like, ugh. We have it sounds so dickish. We have, like, a high bar for where you have to be to get on the show, and that just shows what a fuck up it was for me. So thank you so much, dude, and you've been amazing. Thanks, dude. This was great. I am just in so much pain right now. I cannot believe that I had the chance to invest in that company at below a $20,000,000 valuation. Oh, it pains me. Victor, what an incredible guess. What an exciting future ahead. If you wanna see that episode in full, you can check it out on YouTube by searching for 20 VC. That's two zero VC. But before we leave you today,

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