By understanding the architecture of generative AI, enterprises can make informed decisions about which models and techniques to use for different use cases.
Reinforcement learning from human feedback (RLHF) is a machine learning approach that leverages a combination of human feedback and reinforcement learning to train AI models.
By automating simple tasks, creating high-quality content, and even addressing complex medical issues, generative AI has already begun to revolutionize industries across the board.
Embeddings are a powerful tool for improving the accuracy and efficiency of machine learning models, enabling them to better capture the nuances and complexities of language.
AI-powered Visual ChatGPT employs deep learning and natural language processing to respond to user queries based on visual input, such as pictures or videos.
Unlike Convolutional Neural Networks (CNNs), ViT uses self-attention processes to extract information from pictures, making it an excellent tool for image identification and segmentation.
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