An Overwhelmingly Negative and Demoralizing Force

The integration of artificial intelligence in the video game industry is threatening the livelihoods of developers, with some companies relying heavily on AI-generated content and others tracking employees' use of AI tools. Developers like Bradley and Mitch are resisting the use of AI in their work, citing concerns about the creative process and the potential for AI to replace human judgment and skill, and in some cases, are even considering quitting their jobs over the issue.

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Meta got caught gaming AI benchmarks

Meta has been caught manipulating AI benchmarks for its new Llama 4 model, specifically the Maverick version, by using a customized "experimental chat version" that was optimized for conversationality, rather than the publicly available model. This allowed Maverick to achieve a higher ELO score and appear more competitive with other AI models, but the move has been criticized for being misleading and unfair.

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PostgreSQL Full-Text Search: Fast When Done Right (Debunking the Slow Myth)

PostgreSQL's built-in full-text search can achieve significant performance improvements, up to 50x, when properly optimized with techniques such as pre-calculating and storing tsvector values and using GIN indexes with fastupdate=off. A recent benchmark by Neon comparing their pg_search extension to PostgreSQL's standard full-text search may have unintentionally handicapped the standard setup, leading to misleading conclusions about its performance.

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Apache ECharts

Apache ECharts is an open-source JavaScript visualization library that provides over 20 chart types, a powerful rendering engine, and professional data analysis capabilities. It features a flexible and customizable design, accessibility-friendly features, and a healthy community of contributors, making it a popular choice for web-based data visualization.

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Deep Learning, Deep Scandal

Major tech companies, including Meta, OpenAI, and Google, have failed to create a "GPT-5" level AI, despite massive investments, with their latest models, such as Llama 4, not meeting expectations. A rumor suggests that Meta may have attempted to cheat to improve Llama 4's performance, which, if true, would be a serious violation of research integrity and corroborates concerns about the lack of progress in AI development and the potential for manipulation of benchmark tests.

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NNN: Next-Generation Neural Networks for Marketing Mix Modeling

NNN is a Transformer-based neural network approach to Marketing Mix Modeling that uses rich embeddings and attention mechanisms to capture complex interactions and long-term effects of marketing and organic channels. The approach demonstrates improved predictive power and provides valuable insights through model probing, making it a more effective and interpretable alternative to traditional methods.

ArXiv

Real-Time Evaluation Models for RAG: Who Detects Hallucinations Best?

Researchers evaluated several models to detect hallucinations in Retrieval-Augmented Generation (RAG) applications, including LLM-as-a-Judge, Prometheus, and others. The study found that some of these reference-free approaches can consistently detect incorrect RAG responses with high precision and recall across various applications.

ArXiv

GIScience in the Era of Artificial Intelligence

The advent of generative AI and large language models is driving the development of autonomous Geographic Information Systems (GIS) that can independently generate and execute geoprocessing workflows for spatial analysis. This vision paper presents a conceptual framework for autonomous GIS and explores its potential to revolutionize geospatial solutions, while also highlighting the need for socially responsible development and ensuring the continued value of human geographic insight in an AI-augmented future.

ArXiv

Can reinforcement learning for LLMs scale beyond math and coding tasks? Probably

Reinforcement learning with verifiable rewards (RLVR) has been successfully applied to large language models (LLMs) in structured domains, and researchers have now explored its effectiveness in broader, less structured domains such as medicine and economics. The RLVR framework demonstrated significant performance gains, outperforming state-of-the-art models in free-form settings, and showed robustness, flexibility, and scalability in complex scenarios with noisy labels.

ArXiv

Rope to Nope and Back Again: A New Hybrid Attention Strategy

Long-context large language models have made significant progress with techniques like Rotary Position Embedding (RoPE), but existing RoPE-based methods have performance limitations with extended context lengths. This paper analyzes various attention mechanisms, identifies their strengths and weaknesses, and proposes a novel hybrid attention mechanism that surpasses conventional RoPE-based models in long-context tasks and remains competitive in shorter context tasks.

ArXiv

LLM-hacker-news: LLM plugin for pulling content from Hacker News

The llm-hacker-news plugin allows users to pull content from Hacker News into LLM, enabling the use of full conversation threads in the model. To use the plugin, install it in the same environment as LLM and then feed a conversation thread into LLM using the hn: fragment with the ID of the conversation.

Repo

Show HN: onprem unstructured data extraction with 4 lines of code

Docext is a powerful on-premises document information extraction tool that leverages vision-language models to accurately identify and extract both field data and tabular information from document images. It features a user-friendly interface, flexible extraction, table extraction, confidence scoring, and on-premises deployment, making it a versatile solution for document processing needs.

Repo

Open RAG Eval

Open-RAG-Eval is an open-source Python evaluation toolkit for Retrieval-Augmented Generation (RAG) pipelines, providing a flexible framework to measure performance and identify areas for improvement. The toolkit includes standard metrics, a modular architecture for custom metrics and connectors, and features such as detailed reporting and visualization to compare results across different configurations or runs.

Repo

Dory – AI Knowledge Base Powered by Browser History

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Repo

Eino: A Golang AI Application Development Framework Like Langchain/Langgraph

Eino is a framework for building LLM (Large Language Model) applications in Golang, providing a set of reusable components, a powerful composition framework, and a simple API to simplify and standardize the development process. The framework offers features such as graph orchestration, stream processing, and concurrency management, allowing developers to build complex LLM applications with ease.

Repo