An efficient library for implementing Machine Learning and Artificial Intelligence algorithms in C++ is TensorFlow. TensorFlow is an open-source library that provides a comprehensive ecosystem of tools, libraries, and community resources for deep learning. It offers both high-level APIs to build and train models and low-level APIs for fine-grained control. Another popular option is OpenCV, which is primarily known for computer vision tasks but also provides machine learning algorithms. Lastly, you may consider the Intel® oneAPI AI Analytics Toolkit, which offers optimized C++ libraries and frameworks for machine learning and AI development.

Some other libraries you could consider for implementing ML and AI algorithms in C++ are mlpack, which provides a collection of machine learning algorithms and tools, and Dlib, which offers various machine learning algorithms and tools alongside computer vision functions. Additionally, Scikit-learn is a popular ML library in Python, but it also has bindings for C++ called scikit-learn-cpp, which you can utilize within your C++ projects for ML implementations. Remember to explore these options and choose the one that aligns with your specific project requirements.