AI web crawlers are destroying websites in their never-ending content hunger

Here is a 2-sentence summary of the text: AI web crawlers are overwhelming websites with traffic, causing performance degradation and increased operational costs, as they aggressively scrape content to feed into Large Language Models (LLMs). The problem is exacerbated by the fact that these crawlers often disregard website guidelines and ignore traditional methods of blocking, such as robots.txt files, leaving website owners to seek new ways to mitigate the issue and protect their sites.

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'World Models,' an old idea in AI, mount a comeback

Artificial intelligence researchers are pursuing the development of "world models," which are internal representations of the environment that an AI system can use to evaluate predictions and decisions, with the goal of creating more intelligent, scientific, and safe AI systems. However, despite the concept's promise, there is currently no consensus on the details of world models, and current AI systems often rely on "bags of heuristics" rather than coherent world models, which can lead to a lack of robustness in their performance.

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Parallel AI agents are a game changer

The development of AI-assisted coding has evolved significantly, from initial tools like GitHub Copilot that provided autocomplete suggestions, to more advanced "vibe coding" tools that can generate complete functions and implementations from natural language descriptions. The latest innovation, parallel agents, allows multiple AI agents to work on different problems simultaneously, transforming the way software is developed and enabling engineers to manage multiple streams of development, review code, and provide feedback in a more efficient and collaborative manner.

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Show HN: Amber – better Beeper, a modern all-in-one messenger

This app allows users to manage iMessage, Whatsapp, and Telegram conversations in one place, with features like AI assistance, scheduling, and end-to-end encryption, to help them stay organized and respond to messages on time. The app aims to help users become "superconnectors" by providing a system and tools to maintain and deepen their relationships, similar to how successful individuals like John D. Rockefeller and Marlon Brando used personal CRMs and assistants to manage their networks.

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Apertus 70B: Truly Open - Swiss LLM by ETH, EPFL and CSCS

Apertus is a 70B and 8B parameter language model designed to be fully open, multilingual, and transparent, supporting over 1000 languages and long context, with comparable performance to models trained behind closed doors. The model is a decoder-only transformer pretrained on 15T tokens and can be used for various tasks, including text generation, with code and usage examples provided, but it may produce biased or inaccurate content and should be used as an assistive tool rather than a definitive source of information.

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The Memorization Problem: Can We Trust LLMs' Economic Forecasts?

Large language models (LLMs) can perfectly recall economic and financial data from before their knowledge cutoff dates, making it impossible to distinguish between genuine forecasting and memorization when testing their forecasting capabilities. This memorization ability raises concerns about using LLMs for forecasting historical data or backtesting trading strategies, as their apparent success may be due to recall rather than actual economic insight.

ArXiv

Factors of Convergence Between Brains and Computer Vision Models

Researchers trained a series of AI models with varying factors such as model size, training amount, and image type, and compared their representations to those of the human brain, finding that all three factors impact brain-model similarity. The largest models trained with human-centric images achieved the highest brain-similarity, with brain-like representations emerging in a specific chronology during training that mirrors the developmental trajectory of the human cortex.

ArXiv

Show HN: MCP Secrets Vault – Local MCP proxy to keep API keys out of LLM context

MCP Secrets Vault is a secure server that enables AI assistants to use secrets like API keys and tokens without exposing them, featuring policy-based access control, rate limiting, and audit logging. The server is built with TypeScript and provides a range of tools and configurations to manage secrets, including discover, describe, use, and query functions, as well as comprehensive logging and security guarantees.

Repo

Show HN: I built a deep research tool for local file system

DeepDoc is a tool that performs deep research on local resources, such as documents and images, to uncover insights and generate a clear markdown report without requiring manual digging through files. The tool works by uploading local resources, extracting text, and using a research-style workflow to explore, organize, and generate a report, with the ability to refine the structure and content through user feedback and various agents.

Repo

Show HN: Klavis AI open source Docker images for 50+ high quality MCP servers

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Repo

Show HN: Agent PromptTrain – Manage Claude Code Conversations for Teams

Agent Prompt Train is a management server for teams that provides comprehensive monitoring, conversation tracking, and dashboard visualizations for Claude Code, allowing teams to understand, manage, and improve their Claude Code usage. It offers features such as real-time conversation tracking, historical analytics, and AI-powered insights, and is designed to help teams maximize their Claude AI usage while complying with Anthropic's Terms of Service.

Repo

There's a gap between AI coding demos and daily reality

Many developers are not using AI coding tools to their full potential, and there are specific techniques that can help achieve transformative results, such as using memory files, test-and-regenerate loops, and parallel agent workflows. A collection of these techniques has been compiled into an "AI Coding Playbook" to help developers fill in the gaps and get the most out of their AI coding tools.

Repo