Question: How can I speed up my AI model training without breaking the bank?

If you need to speed up your AI model training without going broke, Together provides a cloud foundation for fast and efficient generative AI model development and deployment. It's got heavy-duty optimizations like Cocktail SGD, FlashAttention 2 and Sub-quadratic model architectures and supports a variety of models for different AI tasks. The company promises big cost savings, up to 117x compared to AWS, so it's a good option for companies that want to build private AI models into their products.

Another good option is Tromero, which helps you move from using GPT-4 to training and deploying your own AI models. It has a three-step process for model fine-tuning and deployment, including a Tailor tool for quick training and a Playground for fiddling with models. Tromero says it offers up to 50% cost savings and full data control, making it a secure and economical option for AI/ML engineers.

Anyscale is another contender, a platform for building, deploying and scaling AI applications. It's based on the open-source Ray framework, supports a variety of AI models, and comes with features like workload scheduling, cloud flexibility and heterogeneous node control. Anyscale says it offers up to 50% cost savings on spot instances and has a free tier with flexible pricing, so it's good for small and large businesses.

Last, Salad offers a cloud foundation for deploying and managing AI/ML production models at scale. It's a relatively cheap option with features like scalability, a global edge network, on-demand elasticity and multi-cloud support. Salad supports a range of GPU-hungry workloads and charges $0.02/hour for GTX 1650 GPUs, with deeper discounts for large-scale usage. That makes it a good option if you need to train a lot of AI models.