Build Long-Context AI Apps with Jamba: Powering the Future of AI Agents

AI21 Labs and DeepLearning.AI have launched a course on building long-context AI applications with the Jamba model. Traditional transformer architectures are computationally expensive for long contexts, while Mamba architectures can compromise output quality. Jamba presents a hybrid architecture, combining the precision of transformers with the efficiency of Mamba, allowing AI agents to process large documents without fragmentation. The course focuses on using tools like the AI21SDK and LangChain to build and optimize enterprise-grade AI agents capable of handling extensive operational memory and complex reasoning.