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Entries by Albin Grataloup

Agentic AI: When the Language Models are Given Tools to Act

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Agentic AI extends language models with tools, memory, and the ability to act. Instead of relying on one giant model, many smaller agents can specialize, cooperate, and reuse skills. This makes AI systems more modular and practical, while also raising new questions about transparency, coordination, and responsibility. Large language models (LLMs) such as ChatGPT and […]

Transfer Learning: Making use of what is already there

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As the number of AI models grows, it becomes clear that many new applications share similarities with existing ones. Transfer learning and domain adaptation harness this overlap by repurposing previously trained models. This approach accelerates training, reduces data requirements, and improves model performance, making it a valuable tool. The traditional approach to deep learning involves […]