# Nov 3, 2025

### Tiny electric motor outperforms record holder by 40%
- **YASA's new electric motor** delivers **750 kilowatts (1,005 horsepower)** while weighing only **28 pounds**, outperforming its predecessor by **40%** in power density.

### Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
- **Tongyi DeepResearch** emerges as the first fully open-source Web Agent, achieving **state-of-the-art performance** with scores of 32.9 on Humanity’s Last Exam and 75 on xbench-DeepSearch, surpassing all existing agents.

### Is Your Bluetooth Chip Leaking Secrets via RF Signals?
- **Bluetooth chips are vulnerable** to machine learning-assisted side-channel attacks, allowing attackers to recover full encryption keys from **90,000 traces** captured at a distance of one meter, affecting millions of devices globally, including wearables and IoT products.

### New Prompt Injection Papers: Agents Rule of Two and the Attacker Moves Second
- The **Agents Rule of Two** proposes that AI agents should only satisfy **two** of three critical properties—processing untrustworthy inputs, accessing sensitive data, or changing state—to mitigate prompt injection risks, emphasizing the need for robust security measures in LLM applications.

### Skyfall-GS – Synthesizing Immersive 3D Urban Scenes from Satellite Imagery
- **Skyfall-GS** synthesizes **immersive 3D urban scenes** from satellite imagery, leveraging open-domain diffusion models to create high-quality textures without the need for expensive 3D annotations.

### \[R\] We were wrong about SNNs. The bo.ttleneck isn't binary/sparsity, it's frequency.
- The **performance gap** between Spiking Neural Networks (SNNs) and Artificial Neural Networks (ANNs) is primarily due to **low-pass filtering** effects of spiking neurons, rather than binary activation losses, as shown in recent research.

### The Continual Learning Problem
- **Memory layers** enable continual learning by allowing models to update parameters selectively, achieving only **11% forgetting** compared to **89%** with full finetuning and **71%** with LoRA when learning new facts from TriviaQA.

### Collatz-Weyl Generators: Pseudorandom Number Generators (2023)
- The **Collatz-Weyl Generators** are a novel class of **pseudorandom number generators (PRNGs)** that leverage generalized Collatz mappings, demonstrating exceptional **statistical quality** by passing rigorous randomness tests recognized by the research community. [Link to article](https://arxiv.org/abs/2312.17043)

### Terahertz Tech Sets Stage for "Wireless Wired" Chips
- **Room-temperature terahertz technology** is advancing with a **70-nanometer thick film** that generates terahertz signals, promising to miniaturize bulky data links for telecommunications.

### \[P\] Explanation of Gated DeltaNet (Qwen3-Next and Kimi Linear)
- **Gated DeltaNet** is a linear attention mechanism inspired by recurrent neural networks, utilizing a gating mechanism to enhance memory control and improve long-context reasoning, as seen in the architectures of [Qwen3-Next](https://qwen.ai/blog?id=4074cca80393150c248e508aa62983f9cb7d27cd&from=research.latest-advancements-list) and [Kimi Linear](https://arxiv.org/abs/2510.26692).

### Continuous Autoregressive Language Models
- **Continuous Autoregressive Language Models (CALM)** shift from discrete next-token prediction to **continuous next-vector prediction**, enhancing efficiency by compressing K tokens into a single vector, allowing for reconstruction with over **99.9% accuracy**.

### \[D\]\[P\] PKBoost v2 is out! An entropy-guided boosting library with a focus on drift adaptation and multiclass/regression support.
- **PKBoost v2** introduces **Shannon Entropy Guidance** and **Hierarchical Adaptive Boosting**, enhancing feature selection and drift adaptation, crucial for handling imbalanced datasets effectively.

### Geonum – geometric number library for unlimited dimensions with O(1) complexity
- **Geonum** revolutionizes mathematical computation by integrating **geometric numbers**, which retain essential geometric information, allowing for efficient operations without the complexity of traditional scalar systems.

### \[R\] TempoPFN: Synthetic Pretraining of Linear RNNs for Zero-Shot Timeseries Forecasting
- **TempoPFN** is a **univariate time series foundation model** that excels in **zero-shot forecasting** by leveraging synthetic data, utilizing a **GatedDeltaProduct architecture** for enhanced performance and efficiency.

### Higher-order Linear Attention
- **Higher-order Linear Attention (HLA)** introduces a **causal, streaming mechanism** that enables higher interactions in attention models while maintaining linear time complexity and a constant-size state, avoiding the quadratic costs of traditional methods.