If you're interested in BunsenLabs Carbon, download an ISO image, burn it to a USB drive, boot it up on a spare machine, and have fun. One thing to keep in mind is that, when you boot the ISO image, you'll want to select the Installer option from the menu.
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Since the initial release, community contributions have pushed data efficiency from ~2.4x to 5.5x against modded-nanogpt, more than doubling in a few days. The key changes are: shuffling at the start of each epoch, which had outsized impact on multi-epoch training; learned projections for value embeddings instead of separate embedding tables; swapping squared ReLU for SwiGLU activation; and ensembling multiple models. 10x data efficiency seems reachable in the short term. 100x might be feasible by the end of the year, given how many directions remain unexplored, but it will require serious exploration on the algorithms side.
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Why fork Zed? 2026-03-01