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Show Notes

[00:03:04] - [First question] - The role that AI and data play in geopolitics and foreign policy

[00:07:21] - The end state of a digital arms race akin to nuclear weapons

[00:08:53] - Current state of things writ large and how the public and private sectors differ

[00:11:33] - The flow and importance of talent when scaling AI and whether it’s more important than software

[00:14:29] - His thoughts on how to communicate categories of what AI can do well and what is still a ways out but excited about

[00:20:18] - The process of creating an AI model and the stages of development

[00:23:19] - A growing trend of data becoming more valuable than code itself

[00:27:16] - Principles of building a great engine for gathering data

[00:29:04] - The state of technology around annotating data writ large

[00:31:31] - What Scale does as a business and their product lineup

[00:35:08] - The Store and Compute equivalents in the AI space in regards to Scale

[00:37:08] - How Scale fills the gap in producing better and cleaner data

[00:39:52] - What Scale will look like in 10 years if their vision is fully realized

[00:41:11] - Where AI is in the S curve of acceleration and where AI and software intersect

[00:44:32] - Questions to ask about how to incorporate AI and data sets into your business

[00:46:23] - What worries him about the proliferation of technology that makes AI more accessible to the masses

[00:48:27] - The most interesting AI model he’s ever come across and collapsing the friction between human intent and programmable outcomes

[00:51:51] - The kindest thing anyone has ever done for him