I wanted to start a broader future possibilities thread around Meta AI.
A useful angle is quality versus speed, but it also connects with productivity. 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 Meta AI is genuinely useful and where it still needs improvement.
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A useful angle is quality versus speed, but it also connects with productivity. 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 Meta AI is genuinely useful and where it still needs improvement.
Photo by on
