Summary
We saw that PaLM 2 could match and perhaps surpass other models in some fields. Google AI assistants, cloud tools, and APIs provide general-purpose functionalities. They resemble Microsoft Azure and OpenAI offers. However, the technology is quite different, as we saw with the architecture that led to PaLM 2. Also, many factors will influence the decision, and the outputs might vary from one task to another.
Before making a choice, extensive evaluations must be made with the right questions before working with Microsoft Azure, Google Cloud, and IBM Cloud, among others.
The chapter was divided into the four parts we will probably encounter when we explore new transformer models: architecture improvements, large language generative mainstream assistants, API implementation, and customization (fine-tuning or other methods).
We began the chapter by reviewing the many improvements in the architecture of LLM Generative AI models. Pathways opens the door to increased optimization...
