A generative AI tech stack consists of various frameworks, tools, and infrastructure that enable the development and deployment of generative AI models. Key components include machine learning frameworks like TensorFlow and PyTorch, cloud computing platforms like AWS and Google Cloud, and specialized APIs for NLP and computer vision. A robust AI tech stack also integrates data processing tools, model training algorithms, and scalable deployment solutions. Businesses leveraging generative AI stacks can create applications for content generation, fraud detection, image synthesis, and personalized recommendations. Selecting the right generative AI tech stack is crucial for achieving high performance, efficiency, and adaptability in AI-driven projects.
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