Artificial
Continual learning in mid-2026. A map of everyone trying to crack it: memory layers, "dreaming" agents, and the Post-Transformer models that learn inside the network
Llion Jones said “2026 is the continual learning year” in the recent Post-Transformer debate. Sutton/Silver call the next phase the "era of experience”. What’s continual learning? Simply put, it’s a model’s ability to continuously improve as it gains experience – without exhibiting catastrophic forgetting. Essentially the stability-plasticity tradeoff for a reasoning model. Essentially it comes down to: where does the memory live? Outside the model. Memory files, vector dbs, graphs. ...
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