Quick introduction to Large Language Models for Android developers

Android has supported traditional machine learning models for years, enabling developers to implement tasks like image classification and object detection. Recently, generative AI and large language models have opened up new possibilities for language understanding and text generation. Machine learning differs from traditional programming in that it involves training models on large datasets to learn how to map inputs to outputs, rather than writing explicit algorithms. Generative AI models can understand inputs like text, images, and audio, and generate human-like responses, enabling applications like chatbots and language translation. Large language models are neural networks trained on massive amounts of text data, learning patterns, grammar, and semantic relationships between words and phrases. These models can be fine-tuned for specific tasks and datasets, and come in various sizes, with larger models requiring more compute power. Key concepts in generative AI include context windows, embeddings, and parameters like Top-K, Top-P, and Temperature, which control the creativity and randomness of model outputs. Fine-tuning models for specific use-cases can also be done using techniques like Low rank adaptation. The future of generative AI on Android looks promising, with ongoing research and optimization of LLMs for mobile devices expected to bring even more innovative features soon.