Inception's Mercury Revolutionizing AI with Diffusion Models

What this video covers

The founder's journey and the psychological aspects of building a startup, including embracing risks and navigating startup culture shock. It also touches on the technical aspects of Inception Labs and its AI development.

Transcript

So earlier this year we were the first in the world to release a commercial scale diffusion language model that we we call this model Mercury. So that's why why I decided to to start inception because I was so excited by the technical results and I saw a huge opportunity right everybody else I mean LLMs are the core of the Genai revolution everybody's talking about LLMs but under the hood everybody's kind like all these LLMs are kind of like clones of each other. they're all building on the same technology and we had something significantly better, right? And so I just saw a huge opportunity and I decided to yeah do it the Stanford way, take the risk and and uh and uh you know go all in and and and build it out myself. >> So I guess for the people that are listening then Stephano, what ended up being the business model of basically the company of of Inception? I mean what's what

how do you guys make money? >> Yeah. So we spent the you know first uh probably six to nine months of the company just developing the the technology basically purely R&D scaling up the the kind of like ideas that we had and actually building a commercial scale diffusion language model. So earlier this year we were the first in the world to release a commercial scale diffusion language model that we we call this model Mercury and you can think of it as a as a competitor to the to Chad GPT to Gemini to quad um that is based on a completely different stack completely different technology and we're going to market with this uh diffusion language model uh we our model is available through uh an API platform form and uh our business model is we are providing access to this model to enterprise customers and developers around the world who are building uh geni applications on top of

these diffusion language models that are much faster much cheaper and that's enabling them to deliver much better experiences in their in their apps because the models are so fast right you don't have to wait so long to get high quality results else.

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