Mike Krieger

The bridge is unfortunately associated with suicides. Like, let's make sure that the model doesn't guide people in that direction. And if it does, let's put in the right safeguards. So that's kind of a, like, trivial example because it was like an Easter egg we shipped for basically two days and then wound down. But it was, like, very much at its core there.

Even as we prepare model launches, again, I have the urgency, like, let's get it out. Like, I want to see people use it. And then you, like, actually do the timeline. We're like, well, from the point where the model is ready to the point where it's released, like, there are things that we are going to want to do to make sure that we're in line with our responsible scaling policy.

Even as we prepare model launches, again, I have the urgency, like, let's get it out. Like, I want to see people use it. And then you, like, actually do the timeline. We're like, well, from the point where the model is ready to the point where it's released, like, there are things that we are going to want to do to make sure that we're in line with our responsible scaling policy.

Even as we prepare model launches, again, I have the urgency, like, let's get it out. Like, I want to see people use it. And then you, like, actually do the timeline. We're like, well, from the point where the model is ready to the point where it's released, like, there are things that we are going to want to do to make sure that we're in line with our responsible scaling policy.

What I appreciate about the product and the research teams here is that it's not seen as standing in our way. It's like, yeah, that's why this company exists. I don't know if I should share this, but I'll share it anyway. At our second all-in since I was here,

What I appreciate about the product and the research teams here is that it's not seen as standing in our way. It's like, yeah, that's why this company exists. I don't know if I should share this, but I'll share it anyway. At our second all-in since I was here,

What I appreciate about the product and the research teams here is that it's not seen as standing in our way. It's like, yeah, that's why this company exists. I don't know if I should share this, but I'll share it anyway. At our second all-in since I was here,

Somebody who's very early here stood up and was like, if we succeeded at our mission, but the company failed, I would see this as a good outcome. I don't think you would hear that. You definitely would not hear that at Instagram. Not because we were bad people, but if we succeeded in helping people see the world in a more beautiful visual way, but the company failed, I would be super bummed.

Somebody who's very early here stood up and was like, if we succeeded at our mission, but the company failed, I would see this as a good outcome. I don't think you would hear that. You definitely would not hear that at Instagram. Not because we were bad people, but if we succeeded in helping people see the world in a more beautiful visual way, but the company failed, I would be super bummed.

Somebody who's very early here stood up and was like, if we succeeded at our mission, but the company failed, I would see this as a good outcome. I don't think you would hear that. You definitely would not hear that at Instagram. Not because we were bad people, but if we succeeded in helping people see the world in a more beautiful visual way, but the company failed, I would be super bummed.

I think a lot of people here would be very bummed too, but that ethos is quite unique.

I think a lot of people here would be very bummed too, but that ethos is quite unique.

I think a lot of people here would be very bummed too, but that ethos is quite unique.

Broadly, we have our research teams. We have the team that sits most closely between research and product, which is a team thinking about inference and model delivery and everything that it takes to actually serve these models, because that ends up being the most complex part in a lot of cases. And then we have product.

Broadly, we have our research teams. We have the team that sits most closely between research and product, which is a team thinking about inference and model delivery and everything that it takes to actually serve these models, because that ends up being the most complex part in a lot of cases. And then we have product.

Broadly, we have our research teams. We have the team that sits most closely between research and product, which is a team thinking about inference and model delivery and everything that it takes to actually serve these models, because that ends up being the most complex part in a lot of cases. And then we have product.

I would say if you just sliced off the product team, it would look similar to product teams that You know, most tech companies with a couple of tweaks. One is we have a labs team, and the purpose of that team is to basically stick them in as early in the research process as possible with designers and engineers to start prototyping at the source rather than wait until research is done.

I would say if you just sliced off the product team, it would look similar to product teams that You know, most tech companies with a couple of tweaks. One is we have a labs team, and the purpose of that team is to basically stick them in as early in the research process as possible with designers and engineers to start prototyping at the source rather than wait until research is done.

I would say if you just sliced off the product team, it would look similar to product teams that You know, most tech companies with a couple of tweaks. One is we have a labs team, and the purpose of that team is to basically stick them in as early in the research process as possible with designers and engineers to start prototyping at the source rather than wait until research is done.

I think I can go into why I think that's a good idea. That's the team that got spun up right after I joined. And then the other team we have is our research PM teams, because ultimately we're delivering the models using these different services. And the models have capabilities like what they can see well, you know, in terms of multimodal or