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Scaling LLMs to Larger Codebases

You Don't Need to Spend $100/Mo on Claude Code:Your Guide to Local Coding Models

Well Being in Times of Algorithms

How I protect my Forgejo instance from AI web crawlers

Decompiling the Synergy: Human–LLM Teaming in Reverse Engineering [pdf]

Show HN: Books mentioned on Hacker News in 2025

Disney Imagineering Debuts Next-Generation Robotic Character, Olaf

ONNX Runtime and CoreML May Silently Convert Your Model to FP16

Origin of Hallucination in LLMs, The physical source of hallucinations has found

Target Improves Add to Cart Interactions by 11 Percent with Generative AI Recommendations

Target has deployed GRAM, a GenAI-powered accessory recommendation system for the Home category, using large language models to prioritize product attributes and capture aesthetic cohesion. The system helps shoppers find compatible accessories, integrates human-in-the-loop curation, and achieved measurable improvements in engagement and conversion. By Leela Kumili

Toad: A Unified CLI Tool for All Your LLMs That Promises Improved UX From Existing Ones

During his sabbatical, Will McGugan, maker of Rich and Textual( frameworks for making Textual User Interfaces (TUI)), put his UI skills to work to build Toad. The newly publicly released tool aims to provide a unified, “beautiful” GUI for multiple coding agents in your terminal, accessible via the same tool via the Agent Communication Protocol (ACP). By Olimpiu Pop

Neptune Combines AI‑Assisted Infrastructure as Code and Cloud Deployments

Now available in beta, Neptune is a conversational AI agent designed to act like an AI platform engineer, handling the provisioning, wiring, and configuration of the cloud services needed to run a containerized app. Neptune is both language and cloud-agnostic, with support for AWS, GCP, and Azure. By Sergio De Simone

Meta Details GEM Ads Model Using LLM-Scale Training, Hybrid Parallelism, and Knowledge Transfer

Meta released details about its Generative Ads Model (GEM), a foundation model designed to improve ads recommendation across its platforms. The model addresses core challenges in recommendation systems (RecSys) by processing billions of daily user-ad interactions where meaningful signals such as clicks and conversions are very sparse. By Vinod Goje

IBM Research Introduces CUGA, an Open-Source Configurable Agent Framework on Hugging Face

IBM Research has released CUGA (Configurable Generalist Agent) on Hugging Face Spaces, making its enterprise-oriented agent framework easier to evaluate with open models and real workflows. The move positions CUGA as a practical alternative to brittle, tightly coupled agent frameworks that often struggle with tool misuse, long-horizon reasoning, and recovery from failure. By Robert Krzaczyński

QConAI NY 2025 - Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery

Aaron Erickson at QCon AI NYC 2025 emphasized treating agentic AI as an engineering challenge, focusing on reliability through the blend of probabilistic and deterministic systems. He argued for clear operational structures to minimize risks and optimize performance, highlighting the importance of specialized agents and deterministic paths to enhance accuracy and control in AI workflows. By Andrew Hoblitzell

Google Metrax Brings Predefined Model Evaluation Metrics to JAX

Recently open-sourced by Google, Metrax is a JAX library providing standardized, performant metrics implementations for classification, regression, NLP, vision, and audio models. By Sergio De Simone

AWS Expands Well-Architected Framework with Responsible AI and Updated ML and Generative AI Lenses

At AWS re:Invent 2025, AWS expanded its Well-Architected Framework with a new Responsible AI Lens and updated Machine Learning and Generative AI Lenses. The updates provide guidance on governance, bias mitigation, scalable ML workflows, and trustworthy AI system design across the full AI lifecycle. By Leela Kumili

QCon AI New York 2025: AI Platform Scaling at LinkedIn

At QCon AI NY 2025, LinkedIn's Prince Valluri and Karthik Ramgopal unveiled an internal platform for AI agents, prioritizing execution over intelligence. By using structured specifications within a robust orchestration layer, they enhance agent observability and interoperability while ensuring human accountability. By Andrew Hoblitzell

I don't understand the point of AI based web browsers.

Schools across the U.S. are rolling out AI-powered surveillance technology, including drones, facial recognition and even bathroom listening devices

[R] No causal inference workshops at ICLR 2026?

Leaf-scan tells farmers when fruit is ripe – without destroying it

Predictions for agentic AI in 2026

We asked four AI coding agents to rebuild Minesweeper, and the results were explosive...

Extremists are using AI voice cloning to supercharge propaganda. Experts say it’s helping them grow

Scientists find a way to 'reboot' vision in adults with lazy eye

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