// data sourcing

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AI Labs Mine Slack Messages for Training Data

Companies building large language models are increasingly licensing or accessing employee messaging data from Slack, treating private workplace communications as a scalable training resource. This creates a direct financial incentive for companies to monetize their users' unguarded conversations, while workers often have no visibility into or control over whether their messages are being used to train competing AI systems. The arrangement exposes a structural fact in AI development: the most valuable training data isn't public datasets or purchased content, but the messy, context-rich language of how people actually work.

Google acquires Spirit Airlines customer data trove for $10 million

Google's $10 million purchase of 100+ million emails and 30 million phone calls from bankrupt Spirit Airlines reflects an emerging market for operational exhaust as AI training material—specifically, unstructured conversational and transactional data that large language models need to improve customer service and dialogue systems. LLM development is increasingly a hunt for authentic human communication at scale, with companies willing to pay nine-figure sums for data that would have been worthless to previous software generations. A failed airline's customer complaint logs and support calls now command higher value as training data than as operational records.