Data Annotation: Types, tools, techniques, and use cases
Data annotation is adding labels or tags to a training dataset to provide context and meaning to the data.
Reinforcement Learning from Human Feedback (RLHF): Working, applications, benefits and RLAIF
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.
What role do embeddings play in a ChatGPT-like model?
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.
How is a Vision Transformer model (ViT) built and implemented?
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.
The future of AI: How multimodal models are leading the way
The emergence of multimodal AI and the release of GPT-4 mark a significant turning point in the field of AI, enabling us to process and integrate inputs from multiple modalities.
Generative Adversarial Networks (GANs): Architecture and training process
Although the architecture and training process of Generative Adversarial Networks are complex, it is essential to understand them to optimize their performance for specific applications.
