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What you'd expect: AWS, GCP, Azure
There is a lot of energy right now around sandboxing untrusted code. AI agents generating and executing code, multi-tenant platforms running customer scripts, RL training pipelines evaluating model outputs—basically, you have code you did not write, and you need to run it without letting it compromise the host, other tenants, or itself in unexpected ways.
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圖像來源，US House Oversight Committee，这一点在爱思助手下载最新版本中也有详细论述
The converse is also worth asking — whether simulating artificial environments (for instance a 3d representation of a Youtube video) might have unintended negative consequences. Fei-Fei Li’s startup World Labs, which aims to make the leading “world model” — an alternative to language models based on tokenizing physical space rather than words — recently raised a substantial amount of money. As consumer-facing robots become more plausible, the business case for such a model is obvious. But what physical spaces are “world” models actually being trained on? The contemporary physical environment, sound-proofed, plastic-coated, and artificially-colored, is radically different from the environment that Homo sapiens evolved to excel in.