Common mistakes include: underestimating data engineering and infrastructure work, treating modality integration as a final step rather than a core architectural component, assuming models that work well alone will combine easily, and not accounting for regional language data variability in India which causes performance drops in production.
Common mistakes include: underestimating data engineering and infrastructure work, treating modality integration as a final step rather than a core architectural component, assuming models that work well alone will combine easily, and not accounting for regional language data variability in India which causes performance drops in production.
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Common mistakes include: underestimating data engineering and infrastructure work, treating modality integration as a final step rather than a core architectural component, assuming models that work well alone will combine easily, and not accounting for regional language data variability in India which causes performance drops in production.
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