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We compare prompt chaining, with an introduction to langchain.ai, and why that vs a plugin.
We review 5 LLMs in 5 minutes, plus an LLM Directory. For the visuals, as we look at representative websites, check out the YouTube version: https://www.youtube.com/watch?v=1WN47vFWI4Q&list=PL3y876l-nINjAq1kFO7DOZd1AiKDWhaWT&index=1
We cover token distillation, using ChatGPT 3.5 to reduce the tokens of a previous response, which should be extremely useful when paying for more expensive APIs like ChatGPT-4
To see the screen, check the youtube version: https://www.youtube.com/watch?v=VxEVvVUnPLk&list=PL3y876l-nINjAq1kFO7DOZd1AiKDWhaWT&index=2
In this I look at whether this is the early days of AI or some significant plateau. For evidence, we look at both a technical piece of evidence on training performance, as well as a recent announcement from Databricks to try to answer the question
A Friday fun-day light-hearted bake-off between Google Bard and ChatGPT, playing with some prompts.
AI Everyday #2 - Matt discusses OpenAI announcing the ChatGPT Plugin architecture.
AI Everyday #1 - Matt recaps the keynote from nVidia GTC.
From the publisher's feed
Matt Wallace, Tech CTO, covers innovation in AI with an eye on interesting takes for executives, entrepreneurs, and software engineers.