The Evolution of Attention and Transformers

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The transformers architecture, developed by Google in 2017, revolutionized language translation. It allowed for variable length inputs and outputs, solving the constraint problem of earlier neural networks. The attention mechanism, a crucial part of transformers, simplified the architecture and improved GPU scaling. This led to the development of GPT models, including GPT-4, and further advancements in natural language processing.

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Today’s show:

Zapier’s Mike Knoop joins Jason to discuss the early days of Zapier before breaking down the evolution of app integrations and API usage (1:20). They dive into reducing friction for Zapier users, regulating AI, the limitations of present-day AI architecture, and more (43:06).

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Time stamps:

(0:00) Mike Knoop joins Jason

(1:20) Zapier’s origin story

(8:40) Zapier’s key inflection point and its profit-sharing model

(14:05) Zapier’s business model

(15:48) Embroker - Use code TWIST to get an extra 10% off insurance at https://Embroker.com/twist

(17:03) The evolution of app integrations and API usage

(23:41) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist

(25:00) Zapier demo + incorporating AI into your workflow

(36:43) Eight Sleep - Go to https://eightsleep.com/twist to check out the Pod Cover and get $150 off at checkout!