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7 months ago
How To Make History With LLMs & Other Generative Models

 
Originally published in Leigh Marie’s Newsletter, Sept 21, 2023.  

Or, I’m getting tired of market maps and am ready for some hotter takes.

It’s been well over a year since I published my overview of large language models, or “LLMs”. The magic of Github Copilot’s beta in early 2022 made me the most excited I’d been about a new technology since I got my first iPhone. I was (and remain) convinced that we are at the start of something big – big enough for me to write a large list of LLM application ideas and watch as many others published their large lists in subsequent months. There’s nothing wrong with a great market map, filled to the brim with potential startup ideas, but it inevitably leads to the question of where to focus. Sure, there are all of these opportunities, but let’s be real, what are the ones that a smart startup founder should go after? And which are flash-in-the-pan, waiting to be made irrelevant by a foundation model provider, a new architecture shift, or an onslaught of other early stage startups?

Over the past year I’ve talked to many founders, operators, and investors, and I’ve encountered the full spectrum of opinions regarding where new LLM/generative model-related $10B+ companies will be built. On one side are those who believe there are many opportunities to build “AI-native” companies (similar to the generational building opportunities from the move to the cloud) with feelings best summarized by this tweet.

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2 thoughts on “How To Make History With LLMs & Other Generative Models

  1. Pingback: How To Make History With LLMs & Other Generative Models « Machine Learning Times – AIoT World News

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