MBMACHINE BRIEF
AnalysisOriginalsModelsResearchStartupsTools
Newsletter

Navigate

  • Home
  • About Us
  • Newsletter
  • Search
  • Sitemap

Content

  • Original Analysis
  • Blog
  • Glossary
  • Best Lists
  • AI Tools

Categories

  • Models
  • Research
  • Startups
  • Robotics
  • Policy
  • Business
  • Analysis
  • Originals

Legal

  • Privacy Policy
  • Terms of Service
Machine Brief|

2026 Machine Brief. All rights reserved.

  1. Home
  2. /Glossary
  3. /In-Context Learning
Back to Glossary
ai

In-Context Learning

A model's ability to learn new tasks simply from examples provided in the prompt, without any weight updates.

Definition

A model's ability to learn new tasks simply from examples provided in the prompt, without any weight updates. You show the model a few examples of input-output pairs, and it figures out the pattern. One of the most surprising emergent abilities of large language models.

Share this term

Related Terms

Few-Shot Learning

The ability of a model to learn a new task from just a handful of examples, often provided in the prompt itself.

Prompting

The text input you give to an AI model to direct its behavior.

Emergent Behavior

Capabilities that appear in AI models at scale without being explicitly trained for.

Activation Function

A mathematical function applied to a neuron's output that introduces non-linearity into the network.

Adam Optimizer

An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.

AGI

Artificial General Intelligence.

Explore More

Latest NewsAI NewsMarketsAnalysisFull Glossary

Want to learn more about AI?

Browse our complete glossary or subscribe to our newsletter for the latest AI news and insights.

Browse GlossarySubscribe to Newsletter