Don’t listen to a vendor about AI, says John Willis, a well-known technologist and author in the latest episode of The New Stack Makers.
“They’re going to tell you to buy the one size fits all,” Willis said. It’s like going back 30 to 40 years ago and saying, ‘Oh, don’t learn how to code Java, you’re not going to need it — here, buy this product.'”
Willis said that DevOps provides an example of how human capital solves problems, not products. The C-level crowd needs to learn how to manage the AI beast and then decide what to buy and not buy. They need a DevOps redo.
One of the pioneers of the DevOps movement, Willis said now is a time for a “DevOps redo.” It’s time to experiment and collaborate as companies did at the beginning of the DevOps movement.
“If you look at the patterns of DevOps, like the ones who invested early, some of the phenomenal banks that came out unbelievably successful by using a DevOps methodology,” Willis said. “They invested very early in the human capital. They said let’s get everybody on the same page, let’s run internal DevOps days.”
Just don’t let it sort of happen on its own and start buying products, Willis said. The minute you start buying products is the minute you enter a minefield of startups that will be gone soon enough or will get bought up by large companies.
Instead, people will need to learn how to manage their data using techniques such as retrieval augmentation, which provides ways to fine-tune a larger language model, for example, with a vector database.
It’s a cleansing process, Willis said. Organizations will need cleansing to create robust data pipelines that keep the LLMs from hallucinating or giving up code or data that a company would never want to let an LLM provide to someone. We’re talking about the danger of giving away code that makes a bank billions in revenues or the contract for a superstar athlete.
For a company of any scale, the coding gets fun again when done right for a company using LLMs at scale with some form of retrieval augmentation.
Getting it right means adding some governance to the retrieval augmentation model. “You know, some structuring, ‘can you do content moderation?'” Are you red-teaming the data? So these are the things I think will get really interesting that you’re not going to hear vendors tell you about necessarily; vendors are going to say, ‘We’ll just pop your product in our vector database.'”
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