Alex Wiltschko

price. There could be something fundamental we don't understand about the world. This is an existential risk that we can never really remove. But we continue into the darkness and into the fog regardless. What we're trying to do is never lose sight of the mountaintop, which is we fully digitize the human sense and it's personal, it's portable, it's affordable.

price. There could be something fundamental we don't understand about the world. This is an existential risk that we can never really remove. But we continue into the darkness and into the fog regardless. What we're trying to do is never lose sight of the mountaintop, which is we fully digitize the human sense and it's personal, it's portable, it's affordable.

And our philosophy for doing that is not to climb up the sheer face of the mountain to that single goal, but to find a route up that mountain with a shallow enough grade where at some points we can stop and build a business. The philosophy here, and I've seen other startups kind of fail to do this, is build along a responsible path

And our philosophy for doing that is not to climb up the sheer face of the mountain to that single goal, but to find a route up that mountain with a shallow enough grade where at some points we can stop and build a business. The philosophy here, and I've seen other startups kind of fail to do this, is build along a responsible path

that makes you harder to kill over time as opposed to makes your likelihood of success even riskier over time. Because I want to do this for my whole life, I don't want to just flip this company and sell it. I really want this to survive. It has to survive. And so we're building in our strategy a way to make that much more likely than not.

that makes you harder to kill over time as opposed to makes your likelihood of success even riskier over time. Because I want to do this for my whole life, I don't want to just flip this company and sell it. I really want this to survive. It has to survive. And so we're building in our strategy a way to make that much more likely than not.

Oh, yeah. If you look at the org chart, you're like, oh, it's an AI company that married a chemistry company.

Oh, yeah. If you look at the org chart, you're like, oh, it's an AI company that married a chemistry company.

Technology usually proceeds on an S-curve, right? It sucks, it sucks, it's getting better. Oh my gosh, it's getting better super fast. And we're pretty much done. It levels off. And I think we're pretty close to the right side of that S-curve with text. We kind of blew past it, but yeah, we passed the Turing test. I regularly am fooled and curious whether or not this was written by ChatGPT or not.

Technology usually proceeds on an S-curve, right? It sucks, it sucks, it's getting better. Oh my gosh, it's getting better super fast. And we're pretty much done. It levels off. And I think we're pretty close to the right side of that S-curve with text. We kind of blew past it, but yeah, we passed the Turing test. I regularly am fooled and curious whether or not this was written by ChatGPT or not.

So text works. And then Ilya Setskovor, who is really one of the progenitors of modern AI for text, got up at the main AI conference, NeurIPS, and said, look, there's one internet and we've trained on it, right? There's no more data, right? So yes, there'll be some remaining tricks. We'll make it cheaper. We'll make it better. We'll add reasoning.

So text works. And then Ilya Setskovor, who is really one of the progenitors of modern AI for text, got up at the main AI conference, NeurIPS, and said, look, there's one internet and we've trained on it, right? There's no more data, right? So yes, there'll be some remaining tricks. We'll make it cheaper. We'll make it better. We'll add reasoning.

But like we're out of the raw fuel that drove a ton of the innovation in text. And I think also similarly for images, right? Like we've downloaded all the world's images and all the image models are trained on all those images. Video, we're not done yet because it's super expensive. So like we're not quite at the end of the curve. Those are just three modalities, right?

But like we're out of the raw fuel that drove a ton of the innovation in text. And I think also similarly for images, right? Like we've downloaded all the world's images and all the image models are trained on all those images. Video, we're not done yet because it's super expensive. So like we're not quite at the end of the curve. Those are just three modalities, right?

There's drug discovery, right? There's chemistry, design of chemistry to treat diseases. There's materials design. There's all kinds of things. And what I'm concerned with at Osmo is marching up the S-curve of a human sense, right? So we're on text, we're on vision and images. Those are handled by really brilliant people.

There's drug discovery, right? There's chemistry, design of chemistry to treat diseases. There's materials design. There's all kinds of things. And what I'm concerned with at Osmo is marching up the S-curve of a human sense, right? So we're on text, we're on vision and images. Those are handled by really brilliant people.

But as far as I can tell, we're the ones who are driving AI up the S curve for Cent. And we're really at the far left. So we're just starting to take off right now. And the thing that is the fuel here is data. And so... Yes, we use specific kinds of AI models. We even use LLMs in some of the work that we do. They're super useful. Our philosophy is the right tool for the job.

But as far as I can tell, we're the ones who are driving AI up the S curve for Cent. And we're really at the far left. So we're just starting to take off right now. And the thing that is the fuel here is data. And so... Yes, we use specific kinds of AI models. We even use LLMs in some of the work that we do. They're super useful. Our philosophy is the right tool for the job.

And so we're not going to take a dogmatic approach and try to shove everything into an LLM, although LLMs are extremely useful for this. And I think actually they will get more capable over time for even what we do. But most of what's under the waterline, most of the iceberg, as it were, is just creating the data, right?

And so we're not going to take a dogmatic approach and try to shove everything into an LLM, although LLMs are extremely useful for this. And I think actually they will get more capable over time for even what we do. But most of what's under the waterline, most of the iceberg, as it were, is just creating the data, right?