My guest today is Alexandr Wang, the CEO and founder of Scale AI. Alexandr founded Scale in 2016, having been inspired to accelerate the development of AI through his work at Quora and his studies at MIT. Specifically, Alexandr realized there was a lack of infrastructure solutions for producing high quality data, the lifeblood for AI models. Today, Scale provides data solutions to leading AI teams at Meta, Microsoft, OpenAI, Flexport, the US Air Force, and many others. This time last year, the business was valued at over $7 billion.

Our conversation is a primer on AI. We discuss the building blocks beneath successful artificial intelligence, AI’s role in both the public and private sector, and why data is the new code. We also cover the similarities and differences between AI and software from an investing perspective and what inspiration Scale takes from AWS. Please enjoy my great discussion with Alexandr Wang.

For the full show notes, transcript, and links to mentioned content, check out the episode page here.

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This episode is brought to you by Lemon.io. The team at Lemon.io has built a network of Eastern European developers ready to pair with fast-growing startups. We have faced challenges hiring engineering talent for various projects and Lemon.io offered developers for one-off projects, developers for full start to finish product development, or developers that could be add-ons to the existing team. Check out lemon.io/patrick to learn more.

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Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.

Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more.

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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

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

[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 Storage and Compute equivalents in the AI space

[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 in 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

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