Dario Amodei

In many ways, the manner and personality of these models is more an art than it is a science.

In many ways, the manner and personality of these models is more an art than it is a science.

Yeah, so there's different processes. There's pre-training, which is, you know, just kind of the normal language model training. And that takes a very long time. That uses, you know, these days, you know,

Yeah, so there's different processes. There's pre-training, which is, you know, just kind of the normal language model training. And that takes a very long time. That uses, you know, these days, you know,

Yeah, so there's different processes. There's pre-training, which is, you know, just kind of the normal language model training. And that takes a very long time. That uses, you know, these days, you know,

tens, you know, tens of thousands, sometimes many tens of thousands of, uh, GPUs or TPUs or tranium, or, you know, what we use different platforms, but, you know, accelerator chips, um, often, often training for months.

tens, you know, tens of thousands, sometimes many tens of thousands of, uh, GPUs or TPUs or tranium, or, you know, what we use different platforms, but, you know, accelerator chips, um, often, often training for months.

tens, you know, tens of thousands, sometimes many tens of thousands of, uh, GPUs or TPUs or tranium, or, you know, what we use different platforms, but, you know, accelerator chips, um, often, often training for months.

Uh, there's then a kind of post-training phase where we do reinforcement learning from human feedback, as well as other kinds of reinforcement learning that, that phase is getting, uh, larger and larger now. And, you know, Often, that's less of an exact science. It often takes effort to get it right.

Uh, there's then a kind of post-training phase where we do reinforcement learning from human feedback, as well as other kinds of reinforcement learning that, that phase is getting, uh, larger and larger now. And, you know, Often, that's less of an exact science. It often takes effort to get it right.

Uh, there's then a kind of post-training phase where we do reinforcement learning from human feedback, as well as other kinds of reinforcement learning that, that phase is getting, uh, larger and larger now. And, you know, Often, that's less of an exact science. It often takes effort to get it right.

Models are then tested with some of our early partners to see how good they are, and they're then tested both internally and externally for their safety, particularly for catastrophic and autonomy risks. Uh, so, uh, we do internal testing according to our responsible scaling policy, which I, you know, could talk more about that in detail.

Models are then tested with some of our early partners to see how good they are, and they're then tested both internally and externally for their safety, particularly for catastrophic and autonomy risks. Uh, so, uh, we do internal testing according to our responsible scaling policy, which I, you know, could talk more about that in detail.

Models are then tested with some of our early partners to see how good they are, and they're then tested both internally and externally for their safety, particularly for catastrophic and autonomy risks. Uh, so, uh, we do internal testing according to our responsible scaling policy, which I, you know, could talk more about that in detail.

And then we have an agreement with the U S and the UK AI safety Institute, as well as other third-party testers in specific domains to test the models for what are called CBRN risk, chemical, biological, radiological, and nuclear, which are, you know, we don't think that models are

And then we have an agreement with the U S and the UK AI safety Institute, as well as other third-party testers in specific domains to test the models for what are called CBRN risk, chemical, biological, radiological, and nuclear, which are, you know, we don't think that models are

And then we have an agreement with the U S and the UK AI safety Institute, as well as other third-party testers in specific domains to test the models for what are called CBRN risk, chemical, biological, radiological, and nuclear, which are, you know, we don't think that models are

pose these risks seriously yet, but every new model we want to evaluate to see if we're starting to get close to some of these more dangerous capabilities. So those are the phases. And then it just takes some time to get the model working in terms of inference and launching it in the API. So there's just just a lot of steps to actually making a model work.

pose these risks seriously yet, but every new model we want to evaluate to see if we're starting to get close to some of these more dangerous capabilities. So those are the phases. And then it just takes some time to get the model working in terms of inference and launching it in the API. So there's just just a lot of steps to actually making a model work.

pose these risks seriously yet, but every new model we want to evaluate to see if we're starting to get close to some of these more dangerous capabilities. So those are the phases. And then it just takes some time to get the model working in terms of inference and launching it in the API. So there's just just a lot of steps to actually making a model work.