336 summarised stories about AI Cost & Economics, each linking back to the original source. Browse all topics →
OpenAI 2 years ago 34
OpenAI now allows users to fine-tune smaller, cheaper models using outputs generated by larger frontier models through its API. The process runs entirely on OpenAI's platform, eliminating the need for external infrastructure. This enables developers to create cost-efficient models that replicate the capabilities of expensive large models without paying for repeated calls to those frontier models.
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TLDRocket
21 October 2026
The day’s biggest throughline wasn’t new model announcements—it was the messy, expensive reality of getting AI to run at scale, profitably, and reliably. Google Cloud shipped llm-d 1.0, a Kubernetes-native distributed inference layer that routes requests to pooled vLLM or SGLang servers, while Google also unveiled TorchTPU, a PyTorch-focused path for developers trying to move off Nvidia GPUs (notably, the pitch leans on PyTorch’s dominance, cited as 85% of AI apps). Off the hardware side, Dutch startup Photon Bridge raised €10 million to build laser tech for optical links in large AI clusters, targeting first samples in 2027 and volume manufacturing in 2028, and framing the bottleneck as a manufacturing-scale problem: millions of lasers per year, delivered via multiplexing designed for higher yield.
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