# Oct 20, 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.

- Implementing neural networks on the "3 cent" 8-bit microcontroller

- **Neural networks can achieve over 90% accuracy on MNIST inference using the ultra-low-cost PMS150C microcontroller**, demonstrating that effective machine learning can be implemented even in constrained environments with minimal resources.

- The Languages of English, Math, and Programming

- The **Triplets.ipynb** notebook explores how different AI models perform in solving the problem of listing distinct positive integer triplets that multiply to 108, revealing that **7 out of 9 models** succeeded when prompted to write a program, compared to only **2 out of 9** for a direct listing request.

- Sabotage Evaluations for Frontier Models

- **Anthropic's new evaluations** assess AI models for potential **sabotage capabilities**, including misleading human decisions and inserting bugs into code, to prepare for future risks as AI systems become more advanced.

- [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.

- All-optical switch device paves way for faster fiber-optic communication

- **An ultrafast all-optical switch** developed by a University of Michigan team utilizes **circularly polarized light** to control light signals without electrical conversion, enhancing speed and energy efficiency in fiber-optic communication.

- [P] NHiTs: Deep Learning + Signal Processing for Time-Series Forecasting

- **NHiTs** is a **state-of-the-art deep learning model** for time-series forecasting, effectively integrating past observations, future known inputs, and static exogenous variables to enhance predictive accuracy.

- [D] Last Week in Medical AI: Top LLM Research Papers/Models (October 12 - October 19)

- **MedLFQA** introduces a benchmark dataset for evaluating the **factuality** of long-form answers from **medical LLMs**, enhancing the reliability of AI-generated medical information.