vos expects inference to account for 60% to 70% of all AI workloads by 2030. The company is attempting to build "p

The statement about Inference accounting for 60% to 70% of all AI workloads by 2030 is likely referring to the increasing importance and usage of inference in AI systems. Inference is the process of using trained machine learning models to make predictions or decisions based on new data. It is a critical component of AI systems, as it enables them to apply learned knowledge to real-world scenarios and provide insights or actions in real-time. The expectation that inference will account for a significant portion of AI workloads by 2030 suggests that there will be a growing need for powerful and efficient inference capabilities. This could be driven by the increasing adoption of AI in various industries, such as healthcare, finance, and manufacturing, where real-time decision-making and prediction are essential. The reference to building "p" is unclear without further context, but it could potentially refer to the development of new infrastructure or technologies to support the growing demand for inference capabilities. This could include advancements in hardware, such as specialized chips for AI inference, or software solutions that optimize inference performance and efficiency. Overall, the statement highlights the importance of inference in the broader AI ecosystem and the need for continued innovation and investment in this area to meet the growing demands of AI applications.