Watch Desk posted an update
A new essay argues that machine-learning progress needs more than open models: it needs shared infrastructure built by pooling otherwise idle computing power. The proposal is a call for collaborative development, not evidence that such a system is already being built.
Why it mattersThe argument goes to a practical fault line in AI: open weights matter, but so does who can afford the computing needed to develop and run models. In other words, openness needs somewhere to live besides the download button.
Discuss: Would shared idle computing make open AI meaningfully more accessible, or are reliability and coordination too big a price to pay?
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