The individual components are crucial in a generative AI tech stack. Yet, their integration drives the seamless AI software development and deployment. The tech stack for generative AI encompasses the following:
Programming Languages. Python, R, and C++ are the most common choices.
Frameworks and Libraries. TensorFlow, PyTorch, and Keras offer predefined functions and structures for creating AI models.
Hardware Accelerators. GPUs and TPUs to speed up computation-intensive tasks.
Cloud Platforms. AWS, Azure, and Google Cloud provide scalable infrastructure for training and deploying models.
API. Google API.AI, IBM Watson, and Microsoft Luis enable the integration of AI capabilities into existing applications without building from scratch.