DISRUPTIVE TECH
We need observability in AI because this technology is starting to show limitations while becoming indispensable , and for enterprises , these limitations are unacceptable . Observability helps companies evaluate and monitor , quality of inputs , outputs , results of LLMbased applications and can flag hallucinations , bias , toxicity , performance and cost issues , says Anupam Datta at Snowflake .
Why enterprise AI also needs observability tools
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