Yash Patil(@ypatil125):Ever since we started serving inference for customers a few months ago, our business has taken off. We are clearly seeing that training wins (and keeps) inference workloads. Inference isn’t a commodity when you can help customers improve the model - not just serve it. Models should get better the more you use them. When you have evals or metrics that you want to optimize for, you can use online training techniques like On-Policy Self Distillation or frontier grade RL post-training to systematically target and improve specific behaviors in your model for your use case. Towards inference that enables continuously improving models! More to come soon!

2026.09.23 03:40

Ever since we started serving inference for customers a few months ago, our business has taken off. We are clearly seeing that training wins (and keeps) inference workloads. Inference isn’t a commodity when you can help customers improve the model - not just serve it. Models should get better the more you use them. When you have evals or metrics that you want to optimize for, you can use online training techniques like On-Policy Self Distillation or frontier grade RL post-training to systematically target and improve specific behaviors in your model for your use case. Towards inference that enables continuously improving models! More to come soon!

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