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Pathway's BDH, a post-transformer architecture, reportedly matches GPT-2 scaling from 10M to 1B parameters while training from scratch on standard GPUs.
An overview of the current state and future outlook of continual learning in mid-2026, covering memory approaches including external memory, in-state memory, and weight updates, with analysis of various models like TTT, Titans, and Dragon Hatchling.
A co-author of the seminal 'Attention is All You Need' paper has argued that the field should move beyond transformers, and a debate hosted by Pathway explores this topic.