This 'College Protester' Isn't Real. It's an AI-Powered Undercover Bot for Cops

American police departments near the US-Mexico border are spending hundreds of thousands of dollars on a secretive AI technology called Overwatch, which uses online personas to interact with and gather intelligence on suspected criminals, including "college protesters" and "radicalized" activists. The technology, sold by New York-based company Massive Blue, has not led to any known arrests and has raised concerns about social media monitoring and undercover tools, with critics arguing it could be used to violate individuals' First Amendment rights.

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Building an AI that watches rugby

The Gainline rugby app aims to provide a richer experience for fans by adding context to the game, but is limited by the data available, which only covers major events and not the nuances of the game. To address this, the developers experimented with using AI to watch and analyze rugby games, extracting data such as the score and game clock from video footage, and even transcribing referee and commentary audio using Whisper.

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AI is turning us into glue

The author, a software developer, is feeling bleak about the rise of Artificial General Intelligence (AGI) and its potential to replace human workers, as they enjoy the puzzle-solving aspects of their job and worry that AGI will leave them with only "glue-like" tasks. The author is skeptical that the promised future of "vibe coding" and human-AI collaboration will be fulfilling, and instead sees a future where humans are relegated to menial tasks or acting as a link between AI and the physical world.

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Russian Propaganda Campaign Targets France with AI-Fabricated Scandals

A Russian propaganda campaign, known as Storm-1516, has targeted France with AI-fabricated scandals, generating 55.8 million views on social media through 38,877 posts. The campaign, which uses AI to create and spread false claims, has significantly increased its activity in recent months, with leading generative AI chatbots also repeating the false narratives, posing a new disinformation threat.

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Show HN: HN Watercooler – listen to HN threads as an audio conversation

The text appears to be a status update from a process generating audio, currently at 0/0 comments processed. It mentions an ElevenLabs API key and a Hacker News thread URL, suggesting that the process is related to generating audio from comments on a specific Hacker News thread.

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PIM-LLM: A High-Throughput Hybrid PIM Architecture for 1-Bit LLMs

PIM-LLM is a hybrid architecture that combines analog processing-in-memory and digital systolic arrays to accelerate 1-bit large language models, achieving significant improvements in performance and efficiency. The design results in up to 80x faster processing and 70% higher energy efficiency compared to conventional hardware accelerators, setting a new benchmark for PIM-based LLM accelerators.

ArXiv

No Free Lunch with Guardrails: Evaluating LLM Safety Tradeoffs

The adoption of large language models and generative AI has led to the development of guardrails to ensure their safe use, but these measures often involve tradeoffs between security and usability. Researchers have evaluated various industry guardrails and language models, confirming that strengthening security can come at the cost of usability, and proposing a blueprint for designing better guardrails that balance risk and usability.

ArXiv

What Should We Engineer in Prompts:Training Humans in Requirement-Driven LLM Use

The Requirement-Oriented Prompt Engineering (ROPE) paradigm is introduced to improve the process of prompting large language models (LLMs) by focusing on generating clear and complete requirements. ROPE has been shown to be effective, outperforming conventional prompt engineering training in an experiment and demonstrating a direct correlation between the quality of input requirements and LLM outputs.

ArXiv

BitNet b1.58 2B4T Technical Report

BitNet b1.58 2B4T is a 2-billion parameter, open-source Large Language Model that achieves performance comparable to leading models while offering significant advantages in computational efficiency. The model, trained on 4 trillion tokens, is available for research and adoption through Hugging Face, along with open-source inference implementations for GPU and CPU architectures.

ArXiv

A cute proof that makes e natural

The number $e$ has numerous mathematical properties, but many students lack a clear understanding of how these properties are connected. This article presents a concise and intuitive proof that links the continuously-compounded-interest limit to the fact that $e^x$ is its own derivative, and derives other key properties of $e$ in a way that is accessible to pre-calculus students.

ArXiv

Recursive LLM prompts

The concept of recursive LLM prompts involves using English as a programming language and a large language model (LLM) as the runtime, where a prompt is designed to return an updated prompt, allowing for recursive generation of text. This approach can be used to break down problems into sub-steps, leveraging the knowledge encoded in the LLM, but it also raises challenges, such as handling cases where the model generates incorrect facts or answers.

Repo

Bibliography of Recent BFT Algorithms

The literature on consensus is vast and explores various aspects of Byzantine agreement, including foundational concepts, communication complexity, and network models. Recent research has focused on optimizing communication cost, achieving optimal quadratic worst-case communication complexity, and developing protocols that adapt to different network conditions and fault scenarios.

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RubyLLM 1.2.0: Universal OpenAI Compatibility & Custom Models

RubyLLM is a Ruby library that provides a simple and unified API for working with various AI providers, including OpenAI, Anthropic, and Google Gemini, allowing developers to easily integrate AI capabilities into their applications. The library offers features such as chat, vision and audio understanding, PDF analysis, image generation, and embeddings, and is designed to be easy to use and minimize dependencies.

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Show HN: Gin-MCP- All Gin APIs are now MCP-compatible without rewriting

Gin-MCP is a zero-configuration library that enables Gin APIs to be used with Model Context Protocol (MCP) clients, allowing for effortless integration and automatic discovery of routes and schema inference. With Gin-MCP, developers can expose their existing Gin endpoints as MCP tools with minimal setup, making it easy to integrate with MCP-compatible clients like Cursor.

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Matrix Calculus for Machine Learning and Beyond

The 18.063 Matrix Calculus course at MIT, taught by Professors Alan Edelman and Steven G. Johnson, covers a coherent approach to matrix calculus, including techniques for thinking of a matrix holistically and generalizing derivatives of important matrix factorizations. The course will cover topics such as derivatives as linear operators, derivatives of functions with matrix inputs and outputs, and applications in engineering, scientific optimization, and machine learning, with a focus on reverse/adjoint/backpropagation differentiation and automatic differentiation.

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