I wanted to start a broader practical use cases thread around AI Projects.
A useful angle is performance, but it also connects with learning curve. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Projects is genuinely useful and where it still needs improvement.
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A useful angle is performance, but it also connects with learning curve. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Projects is genuinely useful and where it still needs improvement.
Photo by on
