Question: How can I optimize the usage and costs of my AI models, is there a platform that can help?

If you want to squeeze the most out of your AI models in terms of usage and cost, Anyscale is worth a serious look. The platform is geared for developing, deploying and scaling AI workloads and comes with features like workload scheduling, cloud choice, intelligent instance selection and GPU and CPU partitioning for better utilization. It supports a variety of AI models and can cut costs by up to 50% for spot instances, making it a good option for enterprises.

Another top pick is Together, which is geared for fast and efficient development and deployment of generative AI models. It comes with new optimizations like Cocktail SGD, FlashAttention 2 and Sub-quadratic model architectures to speed up AI model training and inference. Together supports multiple models and promises big cost savings, including 117x compared to AWS and 4x compared to other suppliers.

Last, Predibase is a cost-efficient option for fine-tuning and serving large language models (LLMs) in particular. It offers state-of-the-art techniques like quantization and low-rank adaptation, along with a cost-effective serving infrastructure and enterprise-grade security. That makes it a good option for developers who want to fine-tune LLMs for different tasks without a lot of overhead.