Training
The process of showing a model many examples paired with desired answers and repeatedly adjusting the model's internal settings so its answers on those examples grow closer to the desired ones. Training does not teach a concept; it fits the cheapest available pattern in the supplied data that satisfies the objective.
Defined in 3 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 process of showing a model many examples paired with desired answers and repeatedly adjusting the model's internal settings so its answers on those examples grow closer to the desired ones. Training does not teach a concept; it fits the cheapest available pattern in the supplied data that satisfies the objective.
The process of building an AI model by feeding it large quantities of data and adjusting its internal parameters until it reliably produces useful outputs. Training a frontier model is expensive, hardware-intensive, and happens infrequently relative to how often the resulting model is used.
The one-time (per version) process of building a model, energy-intensive but usually inherited from the vendor and counted in the buyer's Scope 3 rather than generated directly.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Train a model with your own hands and watch what it actually learns · Build Before You Govern, AI Governance: Applied Mastery
- Sustainability, ESG and the Carbon Cost of AI · Governance and Responsible AI, Business AI Transformation
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.