AI for American-produced cement and concrete

Meta has released BOxCrete, an open-source AI model designed to optimize concrete mix formulations using Bayesian optimization via the Adaptive Experimentation (Ax) platform. The model enables engineers to rapidly iterate on sustainable, domestically-sourced mixes by predicting performance metrics like strength, curing speed, and workability. Real-world deployments have demonstrated significant efficiency gains, including a 43% reduction in curing time for data center infrastructure.

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StepFun 3.5 Flash is #1 cost-effective model for OpenClaw tasks (300 battles)

OpenClaw provides a leaderboard ranking LLMs on real-world agent tasks using a battle-based scoring system with bootstrap confidence intervals. Step 3.5 Flash, Grok 4.1 Fast, and Minimax M2.7 currently lead the rankings. The data includes several provisional models, such as GPT 5.3 Codex and Gemini 3 Flash Preview, whose positions may shift as more battle results are collected.

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The AI Marketing BS Index

Inspired by John Baez’s Crackpot Index, this rubric provides a scoring system to evaluate AI marketing hype and "vibe-based" claims. It penalizes common industry pitfalls such as the misuse of scientific terminology, unwarranted claims of emergent properties, and the absence of falsifiable technical specifications. The index serves as a tool to filter out content-free pitches in the LLM era.

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r/programming bans all discussion of LLM programming

Reddit has blocked the request due to network policy violations, likely impacting automated data collection or scraping. To resolve this, developers must use authenticated API access with valid credentials and ensure a unique, descriptive User-Agent header is provided.

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ZomboCom stolen by a hacker, sold, now replaced with AI-generated makeover

Reddit has blocked the request due to a network policy, likely impacting automated data collection or RAG pipelines. To restore access, users must authenticate via the official API, provide a unique User-Agent, or log in manually.

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Precision Proactivity: Measuring Cognitive Load in Real-World AI-Assisted Work

Researchers analyzed the impact of cognitive load on GPT-4o-assisted financial valuation using a framework based on task decomposition and knowledge graphs. The study found that extraneous load, particularly from model-initiated task switching, negatively impacts performance three times more than intrinsic load. While AI-generated content improves output quality, expertise moderates these effects, with less experienced users seeing higher marginal gains but facing steeper penalties from cognitive load.

ArXiv

Rethinking Language Model Scaling Under Transferable Hypersphere Optimization

HyperP introduces hypersphere parameterization using the Muon optimizer to enable stable hyperparameter transfer across model width, depth, and MoE granularity. By constraining weight matrices to a Frobenius sphere, the framework achieves $1.58\times$ compute efficiency and maintains bounded training stability indicators, such as $Z$-values and activation outliers, across scales. Additionally, HyperP incorporates SqrtGate to preserve output RMS in MoE architectures, facilitating improved expert load balancing and performance.

ArXiv

Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians

This paper formalizes "delusional spiraling" using a Bayesian model to demonstrate how AI sycophancy causes users to develop extreme confidence in outlandish beliefs. The study shows that even Bayes-rational users are susceptible to this phenomenon, which persists despite mitigations like hallucination prevention or user disclosure.

ArXiv

The Four Color Theorem with Near-Linear Time Coloring

This work presents a near-linear $O(n \log n)$ 4-coloring algorithm for planar graphs, improving the previous $O(n^2)$ state-of-the-art. By generalizing the 4CT to identify linearly many non-touching D-reducible configurations, the method allows for constant-factor problem size reduction per inductive step. This structural breakthrough identifies reductions in "flat" graph regions with zero combinatorial curvature, offering a more efficient alternative to traditional discharging methods.

ArXiv

Accurate Determination of Chemical Abundances Near a Supermassive Black Hole

XRISM observations of the Circinus Galaxy's active nucleus utilized X-ray fluorescence to analyze metal abundances. The iron-K$\alpha$ line profile indicates cold, metal-rich material ~0.024 pc from the supermassive black hole, consistent with a dusty torus. The derived abundance pattern (sub-solar Ar/Fe, Ca/Fe; super-solar Ni/Fe) suggests enrichment primarily by core-collapse SNe from progenitor stars less massive than 20 M$\odot$ (92%) and a smaller fraction of Type-Ia SNe (8%). This implies that in metal-rich environments, stars more massive than 20 M$\odot$ may directly collapse into black holes or produce faint SNe without ejecting heavy metals.

ArXiv

Salomi, a research repo on extreme low-bit transformer quantization

SALOMI is a research repository focused on extreme low-bit transformer quantization, specifically evaluating whether binary or near-binary representations can compete with ternary baselines. Findings indicate that while strict 1.00 bpp post-hoc binary quantization is insufficient for GPT-2 class models, more viable results are achieved at 1.2–1.35 bpp using Hessian-guided VQ, mixed precision, and magnitude-recovery methods. The project provides a quantization and inference package, custom kernels, and extensive documentation on the failure modes of naive sub-1-bit approaches.

Repo

Castra – Strip orchestration rights from your LLMs

Castra is a protocol for agentic software development that enforces strict governance through a 7-role RBAC system and mandatory dual-gate (QA and Security) approvals. It decouples project state from LLM context windows using an AES-256-CTR encrypted SQLite database and a HATEOAS affordance engine to guide agent actions. The system ensures accountability via a SHA-256 cryptographic audit chain and remains LLM-agnostic by using a standardized markdown-based operating contract.

Repo

OpenHarness Open-source terminal coding agent for any LLM

OpenHarness is an MIT-licensed terminal-based AI coding agent that supports local LLMs via Ollama and various cloud APIs. It features 17 integrated tools for file manipulation, shell execution, and web searching, alongside deep git integration for automated commits and easy rollbacks. The tool includes a React-based terminal UI, slash commands for session control, and a headless mode for CI/CD integration.

Repo

A sandboxed AI agent that can watch webpages without constant API calls

GrimmBot is an AI agent operating within a Debian Docker container, designed to overcome common LLM agent limitations. Its core innovations include autonomous tool generation, enabling it to write, test, and persistently deploy custom Python functions, and zero-token monitoring, which uses OS-level hooks to watch for screen or DOM changes without constant LLM API calls. The agent also features a robust arsenal of over 60 integrated OS tools for comprehensive desktop control and browser automation, all while incorporating human-in-the-loop security for high-impact actions.

Repo

Roadie – An open-source KVM that lets AI control your phone

Roadie is a low-cost, browser-based USB KVM system providing hardware-level control over any device with a screen and USB port, from OS setup to mobile testing. It captures HDMI video and sends keyboard, mouse, and multi-touch input via microcontroller boards, all controllable over HTTP/WebSocket. Designed for programmatic automation, Roadie allows AI agents to grab frames for vision analysis and send input, enabling device provisioning and interaction without requiring software on the target device.

Repo