ReAct agents vs function calling agents Talk to our Consultant Twitter Facebook Linkedin Large Language Models (LLMs) are transforming how we interact with technology, enabling tasks like generating creative content, summarizing text, and answering questions. However, they have limitations. Their knowledge is frozen at the time of training, and they cannot directly interact with external systems like APIs or databases. This means they lack access to real-time information and cannot directly influence the physical world. To address these limitations, two frameworks have emerged: ReACT agents and function calling agents. These frameworks enable LLMs to reason, take action, and interact with external systems, expanding their capabilities significantly. This article explores both frameworks, comparing their approaches, benefits, and limitations to guide developers in choosing the best approach for their needs. What are ReACT agents? How do ReACT agents w
Composite AI: Benefits, applications, implementation strategies, best practices, and future prospects
Composite AI: Benefits, applications, implementation strategies, best practices, and future prospects Talk to our Consultant Twitter Facebook Linkedin Composite AI is rapidly gaining attention as a transformative approach that combines various artificial intelligence techniques to tackle complex challenges. Unlike traditional AI, which often relies on a single methodology, composite AI integrates multiple AI strategies—such as machine learning, natural language processing , and computer vision—into a cohesive system. This integrated approach enhances problem-solving capabilities, making it possible to address more intricate issues with greater precision. The market for composite AI is growing swiftly, with industry estimates projecting its value from USD 0.9 billion in 2023 to reach USD 4.4 billion by 2028, at a CAGR of 36.5% during the forecast period. This substantial growth highlights the increasing recognition of composite AI’s potential across se