Gaurav Misra

Getting into it, I think the first question behind the question that comes to mind is what exactly did we actually achieve with this AI revolution? What is actually the difference? AI existed before and it exists today. Obviously, there's something magical about what is there today. I think when you get into it, you realize that it's really about the ability to train larger and larger models.

Getting into it, I think the first question behind the question that comes to mind is what exactly did we actually achieve with this AI revolution? What is actually the difference? AI existed before and it exists today. Obviously, there's something magical about what is there today. I think when you get into it, you realize that it's really about the ability to train larger and larger models.

Yes, that's actually a combination of we have better hardware to do it. We have better ML architectures, like there's transformers, there's diffusion models, there's all these new types of architectural unlocks that we've created. And then there's other techniques that we've created too, which just allow us to train larger and larger models.

Yes, that's actually a combination of we have better hardware to do it. We have better ML architectures, like there's transformers, there's diffusion models, there's all these new types of architectural unlocks that we've created. And then there's other techniques that we've created too, which just allow us to train larger and larger models.

And turns out the larger and larger you make these models, the more problems they can solve, the better they can be at solving like text generation or like towards AGI or video generation or media generation in general. I think when you realize that, what actually you get to is that what really matters is the data at the end of the day.

And turns out the larger and larger you make these models, the more problems they can solve, the better they can be at solving like text generation or like towards AGI or video generation or media generation in general. I think when you realize that, what actually you get to is that what really matters is the data at the end of the day.

A lot of companies are like scraping the internet and the internet is also limited in some ways. There's only so much information on the internet even, and that's growing every day. But I think at the end of the day, beyond that, we're going to have to find what are those sustainable sources of data that can continue to grow bigger and bigger models.

A lot of companies are like scraping the internet and the internet is also limited in some ways. There's only so much information on the internet even, and that's growing every day. But I think at the end of the day, beyond that, we're going to have to find what are those sustainable sources of data that can continue to grow bigger and bigger models.

And I think that's going to be the fundamental question behind who actually ends up winning in a lot of these different areas that AI is excelling in today. I think for us, being on the video generation, video editing side, it comes down to like video data, which is actually much heavier, much rarer to find, not as common as text or even audio.

And I think that's going to be the fundamental question behind who actually ends up winning in a lot of these different areas that AI is excelling in today. I think for us, being on the video generation, video editing side, it comes down to like video data, which is actually much heavier, much rarer to find, not as common as text or even audio.

and potentially much more expensive to train on as well, much more limited in terms of being created in the world. And so that tends to be like a big challenge.

and potentially much more expensive to train on as well, much more limited in terms of being created in the world. And so that tends to be like a big challenge.

One of the big things that we're thinking about is how do we actually create a flywheel where we can ingest data on a continuous basis and a growing basis, and that data can actually create bigger and bigger models for us and keep us at the forefront. I also want to call out here, like there's a pretty fundamental difference between different types of AI companies that are out there.

One of the big things that we're thinking about is how do we actually create a flywheel where we can ingest data on a continuous basis and a growing basis, and that data can actually create bigger and bigger models for us and keep us at the forefront. I also want to call out here, like there's a pretty fundamental difference between different types of AI companies that are out there.

I think if you look at a lot of the text generation companies, they're not solving text generation. Like we don't call it text generation. They're actually kind of solving a totally different problem, which is intelligence. Intelligence is an unsolved problem. No one's figured that out yet. And yes, we're achieving some levels of intelligence in these models. And there's a long way to go.

I think if you look at a lot of the text generation companies, they're not solving text generation. Like we don't call it text generation. They're actually kind of solving a totally different problem, which is intelligence. Intelligence is an unsolved problem. No one's figured that out yet. And yes, we're achieving some levels of intelligence in these models. And there's a long way to go.

It may not end at human intelligence. There's people in the world who are really smart. There's people in the world who are not so smart. They both exist. And clearly, so there's a range of intelligence as possible. There's not one value for like you're intelligent or not. So yeah, is there a chance that there's the ability to go smarter than the smartest human? It's possible.

It may not end at human intelligence. There's people in the world who are really smart. There's people in the world who are not so smart. They both exist. And clearly, so there's a range of intelligence as possible. There's not one value for like you're intelligent or not. So yeah, is there a chance that there's the ability to go smarter than the smartest human? It's possible.

But that's a frontier that we've never reached. And so it's kind of solving this unsolved problem. But I think if you think about audio generation or video generation or music generation or these types of things, right, it's I think a little bit less of solving an unbounded intelligence problem and a little bit more of solving actually rendering a solved problem.

But that's a frontier that we've never reached. And so it's kind of solving this unsolved problem. But I think if you think about audio generation or video generation or music generation or these types of things, right, it's I think a little bit less of solving an unbounded intelligence problem and a little bit more of solving actually rendering a solved problem.