37Design a fully on-premise diarization and summarization pipeline for sensitive meeting recordings that provably does not retain transcripts▼hardPalantirAnthropicMicrosoft1 replies◆ premiumSensitive meeting audio in, speaker-attributed summary out, and a hard guarantee that the raw transcript never lands on disk. The strong answer keeps everything on-prem, processes transcripts in memory only, and proves non-retention with architecture and audit, not a policy promise.Open full answer →
38Reproduce-from-paper: design a production-safe Constitutional-AI-style fine-tuning pipeline that aligns a chatbot to a set of rules▼hardAnthropicOpenAICohere1 replies◆ premiumTurn a constitution of rules into a model that follows them, with no human labels on harmful examples. The strong answer walks the two phases (self-critique SFT, then RL from AI feedback), then spends real time on the part papers gloss: adversarially validating the aligned model holds under attack.Open full answer →
39Set up a red-teaming evaluation framework for a code-generation model that sometimes emits malicious scripts▼hardAnthropicOpenAIGitHub1 replies◆ premiumA code model that occasionally produces ransomware, reverse shells, or exfiltration scripts. The strong answer builds an automated loop: adversarial prompt generation, static and behavioral output scanning, layered mitigations, and attack-success-rate per category to prove the mitigations worked.Open full answer →
