Question: Is there a platform that can help reduce energy consumption while running AI workloads?

If you're looking for a foundation to lower energy usage when running AI jobs, Groq is a strong contender. It's a hardware and software foundation for high-performance, high-quality and energy-efficient AI compute. The LPU Inference Engine can run in the cloud or on premises, and it's optimized for energy efficiency, which can cut energy use dramatically.

Another strong contender is Anyscale, which offers the highest performance and efficiency for building, deploying and scaling AI applications. With features like workload scheduling, cloud flexibility, intelligent instance management and GPU and CPU fractioning, it supports a broad range of AI models and can cut costs by up to 50% for spot instances. Anyscale also integrates with popular IDEs and offers a free tier with flexible pricing for larger businesses.

Together also has a compelling option for companies that want to build private AI models into their products. It supports a broad range of generative AI models and offers scalable inference to handle high traffic. With optimizations like Cocktail SGD and FlashAttention 2, it can cut costs for AI model training and inference dramatically. Together says it offers significant cost advantages compared to other suppliers, so it's a good option for those who want to lower their costs to embrace enterprise AI.