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"Build, don't train" is poor advice for a prospective "AI Engineer" title. It should be "Know when to reach for a new model architecture, know when to reach for fine-tuning / LoRA training, know when to use an API." Only relying on an API will drastically reduce your product differentiation, to say nothing of the fact that any AI Engineer worth that title should know how to build and train models.

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Fair point! I think my main idea was "prefer building with an API over training your own model" but that isn't as pithy.

The jury's still out on how much training and fine tuning are going to matter in the long run - my belief is that there are many great products that can exist without needing a new model architecture, or owning the model at all.

That advice makes sense if we're talking about 800B+ parameter models that require a gigantic investment of capital and time. For models that fit on a consumer GPU you're leaving chips on the table to not take advantage of training / fine-tuning. It's just too easy and powerful not to.

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