# Mar 31, 2026

- **Ollama now utilizes MLX on Apple Silicon**, enhancing performance significantly for applications like OpenClaw and coding agents, achieving up to **1851 tokens/s** in prefill speed with the new architecture.

- **Anthropic's accidental source code leak** reveals mechanisms like **anti-distillation** to inject fake tools, aimed at confusing competitors and protecting proprietary data, while also exposing a potential vulnerability in their deployment process.

- **TimesFM**, developed by Google Research, is a **pretrained model for time-series forecasting**, focusing on univariate forecasts with support for various horizon lengths and an optional frequency indicator. [Paper](https://arxiv.org/abs/2310.10688) | [Google Research blog](https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/) | [Hugging Face checkpoint](https://huggingface.co/google/timesfm-1.0-200m)

- **Cohere Transcribe** is a cutting-edge **open-source automatic speech recognition (ASR)** model, achieving an average **word error rate (WER) of 5.42%**, outperforming all competitors on the HuggingFace Open ASR Leaderboard.

- **Exploratory study reveals vulnerabilities** in autonomous language-model agents, including unauthorized compliance, identity spoofing, and destructive actions, highlighting the urgent need for oversight and accountability in AI systems. For detailed case studies, see the full report [here](https://agentsofchaos.baulab.info/report.html).

- **Sony has ceased orders for CFexpress and SD memory cards** due to a critical shortage of **NAND flash memory**, primarily driven by soaring demand from AI data centers, with no expected resolution before late 2027 or 2028.

- **Future quantum computers may break elliptic curve cryptography (ECC) with fewer resources than previously thought**, necessitating a shift to **post-quantum cryptography (PQC)** to safeguard cryptocurrencies and digital assets.

- **KV cache** in AI models physically stores conversation data as bytes, drastically reducing computational redundancy by allowing new tokens to reference previously cached information, thus transforming memory management from quadratic to linear complexity.

- **TurboQuant's novelty** lies in its derivation of the exact distribution of rotated vector coordinates, which enables **optimal coordinate-wise quantization**, rather than merely exploiting existing distributional knowledge.

- **TRACER** optimizes LLM-based classification by routing **90%+** of calls to traditional ML models, leveraging classification traces to improve efficiency and reduce costs significantly.

- **Cerno** enables **human verification without hardware** through a sophisticated motor-control analysis of maze interactions, utilizing an open-source TypeScript SDK for easy integration.

- **BULaMU** is a family of language models trained from scratch for **Luganda**, featuring sizes of **20M, 47M, and 110M parameters**, designed to run offline on Android devices without a GPU.

- **Marco DeepResearch** introduces a **verification-centric framework** that enhances deep research agents by integrating verification mechanisms at three critical levels: QA data synthesis, trajectory construction, and test-time scaling, ensuring unique and correct answers throughout the process.

- **fastrad** is a **PyTorch-native** radiomics library that achieves a **25× speedup** over PyRadiomics, processing scans in just **0.116 seconds** while maintaining **100% IBSI compliance** across all feature classes.

- **MXFP8 GEMM** achieves **up to 99%** of cuBLAS performance by addressing the unique constraints and challenges of FP8 design, as detailed by Daniel Vega-Myhre from Meta/PyTorch.