Mark Blyth

While we're on utility value of data, when we look at effectiveness of agents, I've had Alex Wang at Scale.ai on the show, and he said the hardest thing about building effective agents is most of the work that one does in an organization, you don't actually codify down in data. You remember when you were at school and it says, show your thinking or show your work.

While we're on utility value of data, when we look at effectiveness of agents, I've had Alex Wang at Scale.ai on the show, and he said the hardest thing about building effective agents is most of the work that one does in an organization, you don't actually codify down in data. You remember when you were at school and it says, show your thinking or show your work.

You don't do that in an organization. You draw on the whiteboard, you map it out, and then you put down what you think in the document. The whiteboard is often not correlated in a data source. To what extent do we have the data of showing your work for models, agents to actually do in a modern enterprise?

You don't do that in an organization. You draw on the whiteboard, you map it out, and then you put down what you think in the document. The whiteboard is often not correlated in a data source. To what extent do we have the data of showing your work for models, agents to actually do in a modern enterprise?

You don't do that in an organization. You draw on the whiteboard, you map it out, and then you put down what you think in the document. The whiteboard is often not correlated in a data source. To what extent do we have the data of showing your work for models, agents to actually do in a modern enterprise?

To what extent do you think enterprises today are willing to let passive AI products into their enterprises to observe, to learn, to test? And is there really that willingness, do you think?

To what extent do you think enterprises today are willing to let passive AI products into their enterprises to observe, to learn, to test? And is there really that willingness, do you think?

To what extent do you think enterprises today are willing to let passive AI products into their enterprises to observe, to learn, to test? And is there really that willingness, do you think?

You said about smaller models. Help me just understand again. I'm sorry. The show is very successful, Arvind, because I think I asked the questions that everyone asked, but they're too afraid to actually admit they don't know the answers to. Why are we seeing this trend towards smaller models?

You said about smaller models. Help me just understand again. I'm sorry. The show is very successful, Arvind, because I think I asked the questions that everyone asked, but they're too afraid to actually admit they don't know the answers to. Why are we seeing this trend towards smaller models?

You said about smaller models. Help me just understand again. I'm sorry. The show is very successful, Arvind, because I think I asked the questions that everyone asked, but they're too afraid to actually admit they don't know the answers to. Why are we seeing this trend towards smaller models?

And why do we think that is the most likely outcome in the model landscape to have a world of many smaller models?

And why do we think that is the most likely outcome in the model landscape to have a world of many smaller models?

And why do we think that is the most likely outcome in the model landscape to have a world of many smaller models?

Will Moore's law not mean cost goes down dramatically in actually a relatively short three to five year period?

Will Moore's law not mean cost goes down dramatically in actually a relatively short three to five year period?

Will Moore's law not mean cost goes down dramatically in actually a relatively short three to five year period?

Where does it become a barrier and where does it not?

Where does it become a barrier and where does it not?

Where does it become a barrier and where does it not?