Model architectures keep improving, but a lot of teams I talk to struggle more with training data than models.
Things like:
- noisy datasets
- inconsistent labeling
- missing metadata
- lack of domain coverage
Do people here feel the same, or is data not the biggest bottleneck in your experience?
submitted by /u/JayPatel24_
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