Microsoft CEO Satya Nadella has weighed in on the debate around slowing AI development, agreeing with the need for deliberate pacing but also issuing a wake-up call to industry leaders including Dario Amodei and Sam Altman. In a post shared on social media platform X (formerly known as Twitter) Nadella stressed that any pursuit of superintelligence must be grounded in the principle that AI should hep humanity and also remain under human control. Nadella further added that the benefits of AI must be accelerated and spread broadly across countries, communities and companies. He also stressed on the importance of a frontier ecosystem where both closed and open-source models can thrive making sure that innovation is also not concentrated in the hands of a few entities.Highlighting the need for organizations to retain control over their unique knowledge, Nadella noted: “Every organization should be able to build its own continuous learning loop… without becoming dependent on any one model provider.” He argued that firms must have the ability to embed their own knowledge into models and weights they control. Nadella welcomed research and deliberate pacing to get alignment right as a design goal. He also supported ideas like “embedded evaluators” and broader mechanisms to ensure AI safety is more than just talk.He cautioned against AI being controlled by a handful of entities, calling for broad representation across countries, academia, and industries. Nadella said Microsoft’s approach is to provide broad access and choice at every layer of the AI stack, enterprise control of learning loops and models, and a “Code of Conduct” for its MAI models, which will be published for public consultation.
Read Microsoft CEO Satya Nadella’s complete post here
Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it’s not worth pursuing.We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive.And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control.So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like “embedded evaluators” and the broader efforts to develop the mechanisms to make this more than just talk.The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia.This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.
