Demo-to-deployment gap
The distance between the conditions under which a vendor's demo was produced (curated inputs, a favorable environment, sometimes a different model version) and the conditions your production deployment will actually face. Closing this gap is the purpose of pre-signature testing on your own hardest inputs.
Defined in 2 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in AI Governance: Applied Mastery.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
The distance between the conditions under which a vendor's demo was produced (curated inputs, a favorable environment, sometimes a different model version) and the conditions your production deployment will actually face. Closing this gap is the purpose of pre-signature testing on your own hardest inputs.
The well-documented pattern in which a robotic system's performance in a favorable, curated demonstration does not reliably predict its performance under the full variability of a real deployment environment. Treated as its own topic later in this program. (see Topic 7.4)
The difference between a system's performance under favorable, curated demonstration conditions and its performance under the real variability, scale, and failure costs of a production deployment.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- The vendor interrogation: questions that expose what the sales deck hides · Shipping AI and Surviving the Incident, AI Governance: Applied Mastery
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.