Chris Smith is a longtime engineering leader who has been in the trenches of building with AI & machine learning for years. He’s led the development of data systems & strategies at tech giants like early Google, Yahoo, and Sun; S&P 500's like Live Nation; and a wide variety of startups.
In this conversation, we dive into a key topic that I’ve avoided until now: AI. AI is an enabling technology that’s essential to develop a baseline understanding of so you can be informed enough to reason about it.
We talk about:
what AI really is (versus machine learning, or applied statistics)
how to build a mental model so you can reason about AI options
how to think about incorporating it into your product and/or operations
We also recorded a short, bonus episode on a simple way to think through the level of investment needed to figure out what AI might do for your product.
Topics discussed
(00:00) AI industry at inflection point, causing chaos
(09:05) Machine learning, neural nets, and generative AI
(14:03) Generative AI: LLMs + broad understanding
(21:56) Open source models improve specialized problem solving
(25:06) Access to data leads to competitive advantage
(32:53) AI training improves productivity and learning speed
(42:51) Reduced investment in GPT models speeds results
(48:47) Expectation mismatch leads to brand perception risks
(53:54) Non-technical work is crucial for AI product success
(57:30) Building a computer vision product from scratch
(01:03:14) A strategic approach to refining and testing prototypes
(01:08:04) Closing learning loops
Links & resources mentioned
Find the full transcript at: https://podcast.makethingsthatmatter.com/chris-smith-how-to-add-ai-to-product/#transcript
Send episode feedback on Twitter @askotzko , or via email
Chris Smith
Bluesky @xcbsmith
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People & orgs:
Travis Corrigan - Head of Product, Smith.AI
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Books:
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