Buffer of Thoughts (BoT) is a thought-augmented reasoning framework that enhances LLMs by incorporating a meta-buffer of problem-solving strategies and a buffer manager to dynamically select and adapt these strategies for improved performance on complex tasks.

Explore AI Alignment: its importance, challenges, and methodologies. Learn how to create AI systems that benefit humanity and align with human values and goals.

This guide provides a robust pathway for professionals to validate their expertise in cloud technology, enhance career prospects, and gain industry credibility. It will help beginners and intermediate learners understand the certification paths, their benefits, and the steps to achieving these valuable credentials.

Choose Excel for versatile data processing and comprehensive analysis, and Tableau for advanced visuals and seamless integration with various data sources.

Explore the best Apache Spark certifications to boost your data career. Learn about top programs, exam details, and tips for success.

Maximize your earning potential as a Python developer with proven strategies, continuous learning tips, and comprehensive career growth insights.

Faiss is an open-source library designed for efficient similarity search and clustering of dense vectors, enabling applications like recommendation systems and image search.

PostgreSQL is an open-source object-relational database management system that combines the power of relational databases with the flexibility of object-oriented programming.

DSPy is an open-source Python framework that allows developers to build language model applications using modular and declarative programming instead of relying on one-off prompting techniques.

Learn how business leaders can implement AI effectively and responsibly, gaining strategic advantage and staying competitive.

Prepare to excel in your next data architect interview with this comprehensive guide, which includes top questions and answers to help you demonstrate your expertise and secure the role.

SAMBA is a hybrid language model architecture that combines state space models (SSMs) and sliding window attention (SWA) to efficiently process long sequences of text with improved memory recall.