模型即产品

There were a lot of speculation over the past years about what the next cycle of AI development could be. Agents? Reasoners? Actual multimodality?

过去几年对下一轮AI发展的猜测有很多。代理？推理者？真正的多模态？

I think it's time to call it: the model is the product.

我认为是时候说出来了：模型就是产品。

All current factors in research and market development push in this direction.

所有当前的研究和市场发展因素都在推动这个方向。

• Generalist scaling is stalling. This was the whole message behind the release of GPT-4.5: capacities are growing linearly while compute costs are on a geometric curve. Even with all the efficiency gains in training and infrastructure of the past two years, OpenAI can't deploy this giant model with a remotely affordable pricing.
• 通用模型的扩展正在停滞。这就是GPT-4.5发布背后的整个信息：能力在以线性方式增长，而计算成本则呈几何曲线增长。即使在过去两年中培训和基础设施的所有效率提升下，OpenAI也无法以远程可承受的价格部署这个巨型模型。
• Opinionated training is working much better than expected. The combination of reinforcement learning and reasoning means that models are suddenly learning tasks. It's not machine learning, it's not base model either, it's a secret third thing. It's even tiny models getting suddenly scary good at math. It's coding model no longer just generating code but managing an entire code base by themselves. It's Claude playing Pokemon with very poor contextual information and no dedicated training.
• 有观点认为，意见导向的训练效果远超出预期。强化学习和推理的结合意味着模型突然学会了任务。这不是机器学习，也不是基础模型，而是一种秘密的第三种东西。甚至是小模型突然在数学上变得令人惊讶地优秀。编码模型不再只是生成代码，而是能够独立管理整个代码库。Claude在没有专门训练和非常有限的上下文信息的情况下玩Pokemon。
• Inference cost are in free fall. The recent optimizations from DeepSeek means that all the available GPUs could cover a demand of 10k tokens per day from a frontier model for… the entire earth population. There is nowhere this level of demand. The economics of selling tokens does not work anymore for model providers: they have to move higher up in the value chain.
• 推理成本正在自由落体。DeepSeek最近的优化意味着所有可用的GPU可以满足来自前沿模型的每天10k个token的需求，覆盖……整个地球人口。没有任何地方有这种水平的需求。出售token的经济学对模型提供者来说不再有效：他们必须在价值链上向更高层次移动。

This is also an uncomfortable direction. All investors have been betting on the application layer. In ...