3 ms·
" With only 7M parameters, TRM obtains 45% test-accuracy on ARC-AGI- 1 and 8% on ARC-AGI-2, higher than most LLMs (e.g., Deepseek R1, o3-mini, Gemini 2.5 Pro) w
by briandw 1y ago
" With only 7M parameters,
TRM obtains 45% test-accuracy on ARC-AGI-
1 and 8% on ARC-AGI-2, higher than most
LLMs (e.g., Deepseek R1, o3-mini, Gemini 2.5
Pro) with less than 0.01% of the parameters"
That is very impressive.
Side note:
Superficially reminds me of Hierarchical Temporal Memory from Jeff Hawkins "On Intelligence".
Although this doesn't have the sparsity aspect, its hierarchical and temporal aspects are related.
https://en.wikipedia.org/wiki/Hierarchical_temporal_memory https://en.wikipedia.org/wiki/Hierarchical_temporal_memory
https://www.numenta.com https://www.numenta.com
- java-man 1y agoI suspect the lack of sparsity is an Achilles' heel of the current LLM approach.