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"We have to spend a lot of time preparing high-quality data before we train the model. Just as a chef would spend a lot of time to source and prepare high-quality ingredients before they cook a meal, a lot of the emphasis of the work in AI should shift to systematic data preparation.“

Andrew Ng
Co-Founder @Google Brain
Founder @Coursera

"Even after 4 years I still haven't "solved" labeling workflows. Labeling, QA, final QA, auto-labeling, error-spotting, diversity massaging, labeling docs & versioning, ppl training, escalations, data cleaning, throughput & quality stats, etc."

Andrej Karpathy
Senior Director
@Tesla

“But the real-world experience of those who put them into production shows that (...) it's often the quality of
data (...) that makes your AI project succeed or fail.”

Edouard D'Archimbaud
Co-founder & CTO
@Kili Technology