The problem with Empire of AI is that it takes such a scattergun approach and doesn't really build a coherent thesis. It is also very difficult to draw clear directional information from the book.
I can strongly agree that OpenAI should not have put Kenyan workers in the position in which they were. I can also agree that they should take steps to ensure that it does not happen again. Hao's frequent retelling of the story in interviews tells me nothing about what is being done to address this concern.
The criticisms of potable municipal water usage by datacentres in the book are hard to fault, but they have little to do with what most people think of as generative AI. Again, it does little to aid understanding of the resource usage of contemporary datacentres and the politics of their siting.
Hao's other frequent complaint about the generality of large language models also doesn't land with me, because it is their very generality and ability to draw on a plethora of fields (often unexpectedly and without prompting) that makes them so useful to me and many others. Combined with the ability to research and treat these as jumping off points, the generalized models become tools for broadening ones' horizons.
The problem with Empire of AI is that it takes such a scattergun approach and doesn't really build a coherent thesis. It is also very difficult to draw clear directional information from the book.
I can strongly agree that OpenAI should not have put Kenyan workers in the position in which they were. I can also agree that they should take steps to ensure that it does not happen again. Hao's frequent retelling of the story in interviews tells me nothing about what is being done to address this concern.
The criticisms of potable municipal water usage by datacentres in the book are hard to fault, but they have little to do with what most people think of as generative AI. Again, it does little to aid understanding of the resource usage of contemporary datacentres and the politics of their siting.
Hao's other frequent complaint about the generality of large language models also doesn't land with me, because it is their very generality and ability to draw on a plethora of fields (often unexpectedly and without prompting) that makes them so useful to me and many others. Combined with the ability to research and treat these as jumping off points, the generalized models become tools for broadening ones' horizons.
https://archive.is/Z6dsF