The article also discusses the cost of acquiring and developing GenAI solutions, which can range from nothing to millions of dollars depending on the specific use case. It suggests that small and medium-sized businesses might find openly hosted applications like ChatGPT a cost-effective solution, while organizations with complex and expensive data might prefer to partner with a maker. Large organizations involved in foundational model research would want to be shakers.
Key takeaways:
- The article proposes three categories to help CxOs evaluate potential partners and solutions in the field of generative AI (GenAI): shakers, makers, and takers.
- Shakers are organizations doing primary research and development around deep neural net foundational models, such as Google AI, OpenAI, and Nvidia.
- Makers are organizations that use domain-specific large language models (LLMs) to improve their products and services in a niche and contextual AI framework, such as Amazon and Salesforce.
- Takers are organizations that consume public LLM services through APIs or chat interfaces without customization, like Adobe Firefly.