AI simplified #ai #deeplearning #trending #aiengineering

Latency + How fast the model responds (Because users leave if responses are slow)

Accuracy + Are answers actually correct?

Track hallucinations, precision, and relevance.

Token Usage → Monitor input/output token costs

LLM bills can explode silently.

Retrieval Quality → In RAG systems, check:

Context relevance

Retrieval precision

Missed documents

Failure Rate → API failures, timeouts, crashes, retries

User Feedback + Thumbs up/down, session ratings, edits

Drift Detection → Has model performance degraded over time?

GPU / Infrastructure Usage + CPU, memory, GPU utilization

Security Metrics → Prompt injection attempts, unsafe outputs, data leaks

Business Metrics → Retention, conversions, engagement, task completion

The Interview One-Liner:

"In production Al systems, I track latency, hallucination rate, retrieval quality, token cost, system reliability, and user feedback to ensure both model performance and business impact."

Save this for your next Al interview

Видео AI simplified #ai #deeplearning #trending #aiengineering канала Nisha Singh