checkpoint
A checkpoint is a saved state of an AI model used to resume training or evaluate an intermediate version.
In machine learning, a checkpoint is a snapshot of a model's state saved at a particular point during training. It contains the learned weights and may also store information needed to resume training, such as the optimizer state. Unlike a final released model, checkpoints are created at multiple points during training so they can be compared or used to roll back.
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Articles covering this entry
…s less about clever prompts and more about three things: the context you give the agent, the plugins it can draw on, and the checkpoints where a human steps in.
Pick a model size that fits the device's memory, and use QAT checkpoints when memory is tight.
…ls and data sources into an AI model), Claude identified the four highest-impact journeys, which expanded into 13 measurable checkpoints across web and desktop.
Handing an agent anything that touches money still calls for a clear order of operations and a few checkpoints where a person signs off.
▲ Connected tasks with an approval checkpoint
That checkpoint can reveal missing updates or coverage tilted toward a tool you rarely use.
Set progress checkpoints—and check the interface
…tinction is not simply between automation and manual browsing; it is between actions that can proceed in the background and decisions that deserve a checkpoint.
That classification makes restricted access and explicit approval checkpoints especially important when the system works in business software.
AI can shorten production and revision cycles; the standard for a useful website still depends on human decisions at each checkpoint.