Cheap Inference Squeezes Frontier AI Economics
Frontier labs must keep funding expensive model advances even as older capabilities become cheaper and harder to distinguish from the latest release.
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AI Models & Infrastructure
Model capabilities, compute, deployment, economics and the infrastructure used to operate AI.
Ideas in AI Models & Infrastructure
Compression Cuts AI Agent Context Costs
Filtering repetitive tool output before it reaches an AI agent can cut token use while preserving the context that matters.
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Local AI Agents Put Existing Computers to Work
Bringing intelligence onto a user’s device lets agents work with local software, files and processing power instead of recreating the whole environment in the cloud.
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Lower Baselines Magnify AI Model Breakthroughs
A new AI model can combine genuine improvement with a flattering comparison against an older model that seemed to deteriorate over time.
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Mathematical AI Must Separate Discovery From Retrieval
A model can find an unexpected link between mathematical fields, but novelty depends on proving it hasn't merely recovered an overlooked result.
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Near-Free Decision Models Cut Workflow Costs
Fast, specialised models can make sorting, routing and checking cheap enough to place throughout automated workflows.
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Smaller AI Models Work Better on Narrow Tasks
Dividing software work into bounded jobs can make cheaper models a practical alternative to a single request sent to the largest available model.
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The bandwidth limit on local AI
A model may fit in a local AI machine yet still respond slowly if its memory cannot supply data quickly enough.
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Why AI accuracy isn’t business reliability
A polished AI answer can create more risk than value when a business needs work it can safely rely on.
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Why consumers reach for hosted AI
Local models can handle everyday personal tasks, but hardware costs and limited awareness leave hosted frontier AI as the easier consumer choice.
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