Concept detail
Evaluation harness design
0 tagged videos · 7 connection videos · degree 0
Publication timeline
- 2020-011 video
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Source videos
Observed neighbors
Agent feedback
Replacing click signals with agent outcome signals implies evaluation must be built around task success of the consuming agent, not user-behavior proxies.
1 source videos
Parallel’s Parag Agrawal: Building a New Web for AI Agentsbusiness-leader co-ownership of AI programs
The business owner is the party that defines the value metric, which is what the evaluation harness ultimately encodes.
1 source videos
SoftBank CEO Masayoshi Son: Superintelligence, AI Investing, and the Future of RoboticsDifferential logprob oracle
A slow trusted reference path functions as a corruption detector where the fast path's own logs and confidence signals are blind.
1 source videos
Two Bugs That Hid in Plain Sight: A vLLM Debugging Detective Story — Asaf Gardin & Yuval Belfermachine behavior
Cost-incurring choice tests turn preference claims into quantitative, cost-controlled behavioral measurements.
1 source videos
AI Consciousness Research: What We Can Study Now | Noa Weiss (Atlas Computing)Non-repeatable agent output
Output variance for identical inputs forces a shift from exact-match assertions to statistical or rubric-based evaluation and makes escalation rate a proxy metric for rule-set drift.
1 source videos
AI Agents vs Business Rules: Which Should Make Decisions?Relational context
Implies eval boundaries must enclose environment and peers, not just the agent or model.
1 source videos
The Revolution of Systems Thinking: Why It Changes Everything We Know About Realityverifiability as an admission gate
Determines which specifications can be automatically checked, and therefore what an eval suite can enforce.
1 source videos
System Engineering Requirements - Aircraft System Development Process - EASA Rotorcraft & VTOL 2019