Eric Boyd, the Microsoft executive responsible for the company’s AI platform, recently stated in an exclusive video interview with VentureBeat that Microsoft’s AI service will soon offer more language and learning models (LLMs) beyond OpenAI. Boyd acknowledged that customers want to have choices when it comes to AI models.

Boyd’s statement comes after Amazon AWS CEO Adam Selipsky criticized Microsoft’s reliance on OpenAI as a single model provider. Selipsky stated that companies want cloud providers that offer more options and partnerships with multiple model providers.

When asked about the possibility of offering more models outside of OpenAI, Boyd responded, “I mean, there’s always things coming. I would stay tuned to this space. There’s definitely…we’ve got some things cooking, that’s for sure.”

Microsoft has already deployed OpenAI’s models across various consumer and enterprise products, such as Bing, GitHub Copilot, and Office coPilots. Additionally, Microsoft provides options for customers to use other models through its Azure Machine Learning platform, including open source models provided by Hugging Face.

While closed-source models like OpenAI are often the preferred choice for enterprise companies due to their extensive support and services, Microsoft recognizes the importance of offering more choices to customers. Amazon has been actively emphasizing its expanded partnerships with various model providers, including Anthropic, Stability AI, Cohere, and AI21, to offer more options to customers.

Enterprise Adoption of AI and Core Use Cases

Boyd discussed the readiness of enterprise companies to adopt AI and highlighted the importance of focusing on core use cases where AI models excel. He stated, “We see the most success with companies that have a clear vision for, hey, here’s a problem that’s going to get solved. But particularly when it’s in one of the key categories…that’s what the models work really well at.”

Boyd further emphasized that companies should avoid having grandiose ideas of how AI will solve complex problems and instead focus on specific applications where AI models can provide value. He mentioned that models are particularly effective at content creation, summarization, code generation, and semantic search.

Microsoft aims to stay competitive by offering a range of generative AI applications and the LLMs that power them. Boyd believes that companies that focus on these core application areas can benefit the most from AI technology.

Microsoft’s Approach to Partnerships and Responsible AI

In terms of partnerships, Boyd emphasized Microsoft’s commitment to collaboration with OpenAI and other companies in the AI space. He stated, “We’re not single-minded in this. We know customers are going to want to have choice and we want to make sure we provide it to them.”

Furthermore, Microsoft is dedicated to ensuring responsible AI practices. The company has published responsible AI principles and has implemented a responsible AI standard. Microsoft works closely with its partners, including OpenAI, to prioritize safety, transparency, and interoperability.

In terms of model governance, Microsoft offers customers a confidence-inspiring framework. Azure provides robust privacy and security measures, supporting the strictest industry regulations. Microsoft partners with various companies to offer a range of models and aims to give customers the flexibility to choose the ones that best suit their needs.

Microsoft acknowledges the research and development taking place in open source AI and actively contributes to the open source community. The company understands the value of both closed and open source models and aims to provide a balanced offering to its customers.

In conclusion, Microsoft’s expansion of AI offerings and emphasis on choice reflect the company’s commitment to meeting customer demands while upholding responsible AI practices. By providing a range of models and partnering with various companies, Microsoft aims to empower enterprises to adopt AI solutions that align with their specific needs and use cases.