# Jun 29, 2026

## Daily

## Weekly

- **GLM 5.2 beats Claude in our benchmarks**
    - **GLM 5.2**, an open-weight model from Zhipu AI, achieved a **39% F1 score** in IDOR detection, outperforming Claude Code (32%) at a cost of **$0.17 per vulnerability found**, showcasing its competitive edge in security tasks.

- **A way to exclude sensitive files issue still open for OpenAI Codex**
    - **A proposed feature** seeks to implement a mechanism for marking files and paths that should not be accessed or sent to the model, enhancing security and usability across repositories with a deterministic configuration.

- **Model Training as Code**
    - **Savanna transforms model training into a collaborative software project** by implementing the entire training pipeline in code, enabling one-click, hermetic training runs that enhance efficiency and reduce human error.

- **Ornith-1.0: Self-scaffolding LLMs for agentic coding**
    - **Ornith-1.0** introduces a **self-improving training framework** that enables models to generate their own scaffolds for coding tasks, enhancing solution quality through joint optimization.

- **TOP500 at ISC’26: We have a New Number 1 Supercomputer**
    - **LineShine Supercomputer** in Shenzhen, China, has claimed the **top spot** on the TOP500 list, marking the first Chinese entry in nine years with a **CPU-only system** that boasts **2.198 Exaflops** of sustained FP64 performance.

- **Knowledge Distillation of Black-Box Large Language Models**
    - **Proxy-KD** is a novel method that enables efficient knowledge transfer from **black-box large language models (LLMs)** to smaller models, enhancing their performance significantly.

- **Ornith-1.0: self-improving open-source models for agentic coding**
    - **Ornith-1.0** is a **self-improving open-source model** for agentic coding, featuring architectures like **9B-Dense**, **31B-Dense**, **35B-MoE**, and **397B-MoE**, which excel in coding benchmarks such as **Terminal-Bench 2.1** and **SWE-Bench**.

- **Cerebras OpenAI deal capacity has effectively killed the waitlist for everyone else**
    - **Cerebras' deal with OpenAI** has effectively monopolized its inference capacity, allocating **$20 billion** worth of chips to a single customer, leaving smaller startups in the lurch.

- **Apple Neural Engine: Architecture, Programming, and Performance**
    - The **Apple Neural Engine (ANE)** serves as a **fixed-function matrix accelerator** in Apple devices, with insights derived from reverse-engineering revealing its architecture and performance metrics across the A11 to A18 and M1 to M5 chip families, as detailed in the [arXiv article](https://arxiv.org/abs/2606.22283).

- **Micro-Agent: Beat Frontier Models with Collaboration Inside Model API**
    - **Micro-Agent** technology enhances AI model performance by enabling **collaboration** within the serving layer, allowing multiple models to work together without altering their individual identities.

- **US Grid Constraints: Towards 40GW+ of Behind-the-Meter Datacenter by 2028?**
    - **US datacenter demand is projected to surge from +21GW in 2026 to +84GW by 2030**, with Behind-The-Meter (BTM) solutions expected to power over **50% of new datacenters by 2028**, driven by the inability of the grid to keep pace with power needs.

- **Google's Agentic Peer-Reviewer Handled ~10K Papers at ICML/STOC — Formal Research Paper Now Out**
    - **Google's agentic AI peer-reviewer** efficiently reviewed **~10,000 papers** at ICML/STOC, demonstrating a **34% increase** in catching mathematical errors compared to traditional methods.

- **Claude Meets Blackwell Ultra: Anthropic’s Models Now Run on NVIDIA GB300 in Azure**
    - **Claude models** are now available on **NVIDIA GB300 Blackwell Ultra** in Microsoft Azure, enabling enterprises to create **autonomous AI agents** tailored to specific domains.

- **EML Trees are Universal Approximators**
    - **EML trees serve as universal approximators**, enabling the representation of all elementary functions through composition, thus allowing for the approximation of any function in a general space with controlled size and depth.

- **MultiHashFormer: Hash-based Generative Language Models**
    - **MultiHashFormer** introduces a novel framework for hash-based autoregression in language models, enabling efficient token representation through unique hash signatures generated by multiple independent hash functions.