The post AI21 Labs Unveils Jamba 1.5 LLMs with Hybrid Architecture for Enhanced Reasoning appeared on BitcoinEthereumNews.com.

Jessie A Ellis Aug 23, 2024 01:33 AI21 Labs introduces Jamba 1.5, a new family of large language models leveraging hybrid architecture for superior reasoning and long context handling. AI21 Labs has introduced the Jamba 1.5 model family, a state-of-the-art collection of large language models (LLMs) engineered to excel in a variety of generative AI tasks, according to the NVIDIA Technical Blog. Hybrid Architecture Delivers Superior Performance The Jamba 1.5 family employs a hybrid approach combining Mamba and transformer architectures, complemented by a mixture of experts (MoE) module. This architecture excels in managing long contexts with minimal computational overhead while ensuring high accuracy in reasoning tasks. The MoE module increases the model’s capacity without escalating computational requirements by utilizing only a subset of available parameters during token generation. Each Jamba block, configured with eight layers and an attention-to-Mamba ratio of 1:7, fits into a single NVIDIA H100 80 GB GPU. The model’s architecture balances memory usage and computational efficiency, making it suitable for various enterprise applications. The Jamba 1.5 models also boast an extensive 256K token context window, enabling the processing of approximately 800 pages of text. This capability improves the accuracy of responses by retaining more relevant information over longer contexts. Enhancing AI Interactivity with Function Calling and JSON Support One of the standout features of the Jamba 1.5 models is their robust function calling capability with JSON data interchange support. This functionality allows the models to execute complex actions and handle sophisticated queries, enhancing the interactivity and relevance of AI applications. For instance, businesses can deploy these models for real-time, high-precision tasks such as generating loan term sheets for financial services or acting as shopping assistants in retail environments. Maximizing Accuracy with Retrieval-Augmented Generation The Jamba 1.5 models are optimized for retrieval-augmented generation (RAG), which improves their ability…

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Filed under: News - @ August 23, 2024 2:23 am