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If you are of the opinion that the transformer architecture cannot scale to AGI and a more brain inspired approach is needed, then the sooner that everyone realizes that scaling LLM/Tx is not sufficient, the sooner the search begins in earnest. At present the majority of experimental compute and researcher effort is probably on such LLM/Tx systems, however if that changes to exploring new approaches then we can expect a speedup on finding such better architectures. For existing companies, https://thinkingmachines.ai/ and https://ssi.inc/ are probably already doing a lot of this, and Deepmind is not just transformers, but there is a lot of scope for effort/compute to shift from LLM to other ideas in the wider industry.