The authors emphasize the role of computing infrastructure and data in the development of generative AI models. They note that building a new generative AI model requires specialized computing infrastructure, which is often provided by major cloud vendors. They also point out that generative AI models are trained on massive internet-scale data, including publicly available repositories of web crawl data, Wikipedia, online books, and other sources. The article concludes by noting that while AI model developers release information on how the model was trained, they do not provide detailed information about the provenance of their training data sources.
Key takeaways:
- The generative AI market is rapidly expanding, with significant investments being made in AI startups and corporations increasing spending on the technology.
- Generative AI can deliver significant increases in productivity, either by augmenting human effort or substituting for it.
- Specialized computing infrastructure powered by high-performance GPUs is essential for training and running generative AI models. Major cloud vendors like AWS, Google Cloud, and Microsoft Azure commonly provide this infrastructure.
- Generative AI models are trained on massive internet-scale data, which can include publicly available data, domain-specific data crawled from the web, or data purchased from marketplaces.