Comma openpilot – Open source driver-assistance

Comma.ai provides the comma four hardware and openpilot software, an open-source autonomy stack that adds advanced driver assistance features to over 325 vehicle models. The system utilizes 360° vision and OTA updates to enable lane centering and adaptive cruise control, supported by a dataset of over 300 million miles. With 50k GitHub stars, the project represents a major community-driven effort in real-world AI deployment for consumer vehicles.

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AI can 10x developers in creating tech debt

Michael Parker of TurinTech discusses the rise of AI-generated tech debt and the limitations of current LLM tools in enterprise environments with legacy codebases. He advocates for a shift from simple chat interfaces toward multi-agent systems that prioritize upfront planning, automated maintenance, and refactoring. The future of AI in software engineering involves proactive agents with organizational memory that function as collaborative team members rather than just individual assistants.

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JSON-render: LLM-based JSON-to-UI tool

json-render is a framework for building AI-generated interfaces by constraining LLM output to a predefined component catalog validated with Zod. It supports progressive streaming for real-time rendering, data binding via JSON Pointer, and the ability to export generated UI as standalone React code without runtime dependencies. This approach provides strict guardrails for generative UI while maintaining native performance and type safety.

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You can't pay me to prompt

The author has implemented a formal "NO-AI" policy for both professional and personal work, rejecting the use of LLM and generative tools in favor of human-centric creative processes. This stance is marked by a new "NO-AI" badge on their website and a formal policy document that prioritizes the journey of creation over automated output. While the author remains skeptical of the current tech trajectory, the policy allows for future revisions should the industry undergo a radical shift.

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We posted a job. Then came the AI slop, impersonator and recruiter scam

The Markup details the challenges of hiring for technical roles amidst a surge of LLM-generated "slop" and fraudulent applications. Key issues include automated resume tailoring, identity impersonation during video interviews, and sophisticated phishing scams that leverage AI to scale recruitment fraud. The report highlights specific red flags like templated response patterns and inconsistent metadata, necessitating a shift away from public job boards toward manual outreach.

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David Patterson: Challenges and Research Directions for LLM Inference Hardware

LLM inference is primarily constrained by memory and interconnect bottlenecks rather than compute, driven by the autoregressive Decode phase. Key research opportunities to address these challenges include High Bandwidth Flash, Processing-Near-Memory, 3D memory-logic stacking, and low-latency interconnects for both datacenter and mobile applications.

ArXiv

GPT OSS Beat Humans in TriMul Competition via TTT

TTT-Discover is a novel method that applies reinforcement learning at test time, allowing an LLM to continue training with problem-specific experience to discover a single state-of-the-art solution rather than generalize. This approach, which contrasts with prior work using frozen LLMs, achieves new SOTA across diverse domains including mathematics, GPU kernel engineering, algorithm design, and biology. TTT-Discover utilizes an open model (gpt-oss-120b) and provides reproducible results at a low computational cost.

ArXiv

Hallucination Stations: Limitations of Transformer-Based Language Models (2025)

This paper analyzes LLM hallucinations and limitations from a computational complexity perspective, concluding that LLMs are unable to perform or verify the accuracy of computational and agentic tasks beyond a certain complexity threshold.

ArXiv

AI agent generates rebuttals for papers

RebuttalAgent is a multi-agent framework that reframes rebuttal generation as an evidence-centric planning task to mitigate hallucinations and improve grounding. The system decomposes reviewer feedback into atomic concerns, utilizes hybrid contexts and autonomous external search, and generates an inspectable response plan before drafting. Evaluated on the new RebuttalBench, it outperforms baselines in coverage, faithfulness, and strategic coherence.

ArXiv

Surfaces with Klein bottle topology occur in fusion reactor fields

While magnetic confinement fusion typically assumes toroidal magnetic surfaces, this paper demonstrates that immersed Klein bottle topologies can also occur around reflection-hyperbolic fixed points of the Poincaré map. These genus-1 surfaces are present in the QUASR stellarator database and are associated with abnormal sawtooth crashes, challenging the standard assumption of strictly toroidal field configurations.

ArXiv

Open-source Figma design to code

VibeFigma is a CLI tool and REST API that automates the conversion of Figma designs into production-ready React and TypeScript components using Tailwind CSS. It leverages the official Figma API for design extraction and features optional AI-powered code optimization and cleanup via Google's Generative AI. The tool supports interactive modes, custom asset mapping, and component-level optimization for streamlined frontend development workflows.

Repo

Nvidia Presents the First AI Framework 100% Generated by AI [pdf]

VibeTensor is a research deep learning system fully generated by AI agents, spanning from Python and Node.js bindings down to a C++20 core and CUDA assembly. The stack includes a custom dispatcher, autograd engine, and stream-ordered caching allocator, capable of executing end-to-end training for computer vision and language models. While currently prioritizing correctness over performance, it serves as a milestone for agentic software engineering by demonstrating that LLM-powered agents can autonomously implement and validate complex system software.

Repo

Ask CLI – A simple tool to get help with commands from the terminal

Ask CLI is a lightweight terminal assistant designed for rapid command-line help and code debugging. It supports integration with major LLM providers and local inference via OpenAI-compatible APIs like Ollama or llama.cpp. The tool features context-aware analysis of command outputs through the -c flag while maintaining a security-first architecture that restricts unauthorized file access and execution.

Repo

Entelgia: A consciousness-inspired multi-agent AI system with persistent memory

Entelgia is a multi-agent AI architecture designed to model persistent identity, emotional regulation, and internal conflict through a "CoreMind" framework. It utilizes a unified persistent memory store and six interacting cores—including conscious, emotion, and meta-cognitive layers—to facilitate emergent moral reasoning rather than hard-coded safety constraints. Currently a research prototype, the system supports local LLM integration and focuses on identity continuity and reflective dialogue between specialized agents.

Repo

Local AI Manifesto

ACF is an AI-powered, 7-stage code generation pipeline emphasizing secure, private development, supporting local (Ollama, LM Studio) and cloud (OpenAI, Anthropic) LLM backends. It incorporates multi-model routing, local Git versioning, and a comprehensive CLI for managing development workflows with features like API contract generation, test coverage enforcement, and code reviews. The platform also includes an Extension Marketplace for custom agents, profiles, and RAG kits, enabling users to extend functionality and monetize specialized AI development tools.

Repo