Recent progress in LLMs has shown their potential in performing complex reasoning tasks and effectively using external tools like search engines. Despite this, teaching models to make smart decisions about when to rely on internal knowledge versus search remains a…
Language models trained on vast internet-scale datasets have become prominent language understanding and generation tools. Their potential extends beyond language tasks to functioning as decision-making agents in interactive environments. When applied to environments requiring action choices, these models are expected…
Recent advancements in LM agents have shown promising potential for automating intricate real-world tasks. These agents typically operate by proposing and executing actions through APIs, supporting applications such as software engineering, robotics, and scientific experimentation. As these tasks become more…
In this tutorial, we demonstrate how to build a powerful and intelligent question-answering system by combining the strengths of Tavily Search API, Chroma, Google Gemini LLMs, and the LangChain framework. The pipeline leverages real-time web search using Tavily, semantic document…
Manipulating lighting conditions in images post-capture is challenging. Traditional approaches rely on 3D graphics methods that reconstruct scene geometry and properties from multiple captures before simulating new lighting using physical illumination models. Though these techniques provide explicit control over light…
Amazon Web Services (AWS) has open-sourced its Strands Agents SDK, aiming to make the development of AI agents more accessible and adaptable across various domains. By following a model-driven approach, the Strands Agents SDK abstracts much of the complexity behind…
