# Jul 26, 2025

- **Efficient Computer's Electron E1 CPU** – 100x more efficient than Arm?  
  The **Electron E1 CPU** from Efficient Computer claims to achieve **up to 100 times better energy efficiency** than leading ARM embedded cores by utilizing a **spatial data flow architecture** that minimizes data movement overhead, a significant energy drain in traditional CPUs.

- **Experimental surgery performed by AI-driven surgical robot**  
  **AI-driven surgical robots** have advanced to autonomously perform complex procedures, achieving a **100% success rate** in gallbladder surgeries on pig organs, showcasing significant improvements over previous models like STAR.

- **SRAM Has No Chill: Exploiting Power Domain Separation to Steal On-Chip Secrets**  
  **Volt Boot** is a novel attack that exploits **power domain separation** in modern SoCs to retain data in on-chip SRAM across power cycles, achieving **100% accuracy** in data retrieval without the need for low temperatures or complex post-processing.

- **[P] Sub-millisecond GPU Task Queue: Optimized CUDA Kernels for Small-Batch ML Inference on GTX 1650.**  
  **Achieved 93,563 ops/sec** and **0.011 ms median latency** on a GTX 1650 by optimizing CUDA kernels for small-batch ML inference, demonstrating significant performance gains over traditional frameworks like PyTorch and cuBLAS.

- **[D] - Scaling Inference To Billions of Users And Agents**  
  **Scaling LLM inference** to billions of users requires a comprehensive infrastructure, including the **GKE Inference Gateway**, which reduces tail latency by **60%** and increases throughput by **40%** through model-aware routing techniques like KV cache and LoRA.

- **Unifying Probabilistic Learning in Transformers [R]**  
  This work proposes a **unified theory** of probabilistic learning in transformers, suggesting that various learning processes occur along a single axis termed **'internal time'**, linking them to quantum systems.

- **[D] How to improve pretraining pipeline**  
  **Enhancements** to the pretraining pipeline include **Flash Attention**, **RMSNorm**, **SwiGLU**, and **RoPE**, which optimize model performance on an **11b token dataset** of web text and code.

- **[D] Do you think that Muon Optimizer can be viewed through the lens of explore-exploit?**  
  The **Muon optimizer** demonstrates the ability to achieve **comparable loss** with significantly less data, indicating a potential shift in optimization strategies after years dominated by Adam.