Ever wondered how AI models can perform tasks they weren’t explicitly trained for? This video explores in-context learning, a powerful technique in prompt engineering that allows models to "realize" their latent capabilities.

We’ll discuss:
1️⃣ What is In-Context Learning? – Discover how examples in prompts guide models to perform specific tasks without changing their parameters.
2️⃣ How It Works – Learn the key components of in-context learning: instructions, requirements, examples, and questions.
3️⃣ Zero-Shot vs. Few-Shot Learning – Understand the difference and when to use each.
4️⃣ Best Practices – Tips for choosing diverse and representative examples while managing context window limitations.
5️⃣ Comparison with Fine-Tuning – See how in-context learning contrasts with fine-tuning in terms of external vs. embedded knowledge.

🧠 Key Insight: In-context learning shows that models often have untapped potential. By simply providing the right examples, we can unlock their capabilities for a variety of tasks.

🔔 Subscribe for more deep dives into AI techniques and insights.
👉 Let’s explore the future of applied AI together.

#AI #MachineLearning #InContextLearning #PromptEngineering #AppliedAI

свернуть