Oct 19, 2024

• AI engineers claim new algorithm reduces AI power consumption by 95%
  BitEnergy AI's new algorithm, Linear-Complexity Multiplication (L-Mul), replaces complex floating-point multiplication with integer addition, achieving a potential 95% reduction in AI power consumption while maintaining accuracy.

• Why do random forests work? They are self-regularizing adaptive smoothers
  Tree ensembles, viewed as adaptive and self-regularizing smoothers, enhance prediction smoothness beyond individual trees, adjusting their smoothness based on input dissimilarity at test-time, which offers a fresh perspective on their effectiveness.

• [Project] Tsetlin Machine for Deep Logical Learning and Reasoning With Graphs (finally, after six years!)
  The Graph Tsetlin Machine is a novel deep learning model that enables multimodal learning and reasoning across directed and labeled multigraphs, marking a significant advancement after six years of development.

• [D] multi-modal neural networks for time series?
  Multi-modal neural networks can be designed to forecast time series by integrating auxiliary data and property embeddings, enabling accurate predictions even with non-overlapping time series inputs.

• TwoMinutePapers - New AI Can Barely Move…And Somehow Learns To Walk!

• YannicKilcher - GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models