Evaluation
Brendon.BOT has curated 14 items on evaluation across 6 shelves (blog, books, insights, papers, podcasts, videos), with available analysis and source links. Historical and pinned items may not have a current quality assessment.
Papers (1)
-
Just Ask Jev: Reinforcement Learning for Calibrated Decisions as a Zero-Shot Detector of AI Alignment Failures
arXiv
Jev turns a single LLM call into a calibrated, zero-shot detector for ten common alignment failures.
Podcasts (1)
-
Simulation: the new Scaling Law — Joon Sung Park, Simile AI
Latent Space
The SimGym hype and Simile AI's $2B Series B funding are a stark reminder that the summer of simulative AI never truly went away. Joon Sung Park's discussion on the new scaling law for simulation will likely resonate…
Videos (1)
-
Continual Learning: How AI Agents Get Better With Every Use | Arjun Karanam, Trajectory
Sequoia Capital
In Sequoia’s written conversation, Arjun Karanam describes an experience gap and four goals: traceable decisions, evaluation from real traffic, an enabling harness and room to experiment with open weights. He presents…
Books (2)
-
AI Engineering: Building Applications with Foundation Models
Chip Huyen
A practitioner's guide to foundation-model applications, covering evaluation, RAG, fine-tuning, and AI system architecture.
-
Machine Learning with Pytorch and Scikit-Learn
Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili
A broad Python ML textbook covering classical methods, deep learning, transformers, graph networks and reinforcement learning.
Insights (8)
- Embodied Domains Are Becoming Alignment Stress Tests
- From Benchmarks to Real-World Dialogues: Evaluation Is Getting Human-in-the-Loop
- The Long-Tail Knowledge Paradox
- The Evaluation-Feedback Gap Is Quietly Widening
- The Dilemma of Divergent Knowledge
- The Benchmark Mirage: Why Your Model Score Might Be Meaningless Tomorrow
- When AI Evaluation Metrics Become Legal Documents
- Trace Integrity Redefines Agent Reliability Metrics