Research

数据驱动的行业、技术与商业研究 · 视频背后的证据、数据与视觉化报告

5 articles

Research Tracks

What dataset would let a model learn the decision from geometry, assembly, BOM and CFD context together — and does it exist anywhere yet?
How should 'automation' and 'AI' be separated in evaluation, so that a gain like 100 → 50 → 42 min is attributed to the right cause?
What would a convincing public vehicle-scale result have to contain — representation, data, benchmark, verification against CFD — to count as evidence rather than a demo?
Where exactly should the authority boundary sit — which actions may an autonomous system take before validation itself becomes untestable?
Can evaluation practice (shared trajectories, agent standards, TEVV) keep up as deployments move faster than measurement?
How much surrogate screening is safe in a real engineering loop before high-fidelity validation has to re-enter?
Will job transformation stay ahead of job displacement?
Does productivity follow capability — or lag it by years?
Who captures the economic value as intelligence becomes abundant?
How fast does AI adoption translate into measurable productivity?
Which industries will face the same "cheapness inflection" next?
Does the value-not-price pattern from autos hold for AI — or differ?