Sequoia Capital Guide to Generative AI

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👀 Today’s Thing: Sequoia Capital Guide to Generative AI

🤖 Big-time venture capital firm Sequoia Capital published a colorful, easy-to-read guide to generative AI. The essay places the tech in historical context, maps the Gen AI application landscape, and predicts how this all will upend supercharge affect creative disciplines (writing, graphics, gaming, etc) over the next decade.

🎧 Want to go deeper? Check out my podcast episode with Pat and Sonia, the paper’s authors.

📖 Backstory

☞ Generative AI is artificial intelligence that creates (generates) text, images, audio, and other types of data.

☞ Text and image generation tools like GPT-3 and MidJourney caught techies’ attention in 2022, but #GenAI had its watershed moment with the release of OpenAI’s ChatGPT. The user-friendly chatbot attracted 100 million users in just two months, making it the fastest-growing consumer application in history.

☞ Gen AI applications are typically built atop Large Language Models (LLMs), which excel at natural language processing (NLP) — understanding and communicating in human-like language.

🔑 Keys to Understanding

🥇 AI has been disrupting factory work and other blue-collar jobs for years now, but Gen AI is seen as the first legitimate threat to knowledge workers.

🥈 Early adopters in research and industry have been using Gen AI for some time now. Insiders say Gen AI will turn writers, graphic designers, and software coders into “conductors” — high-level project managers who orchestrate Gen AI tools that create the actual text, pixels, and code faster and cheaper than any human could.

🥉 Sequoia: “The rate of progress is incredibly high—we have gone from narrow language models to code auto-complete in several years—and if we continue along this rate of change and follow a “Large Model Moore’s Law,” then these far-fetched scenarios may just enter the realm of the possible.”

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Until the next thing,

- Noah

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