Annoyed Redditors tanking Google Search results shows perils of AI scrapers

Londoners on Reddit are intentionally posting false recommendations for restaurants to keep them off the radar of tourists and social media influencers, highlighting the flaws of Google's AI Overview feature, which relies on user-generated content. This trend shows how easily AI scrapers can be manipulated, and raises concerns about the accuracy and reliability of Google search results.

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ModelKit: Transforming AI/ML artifact sharing and management across lifecycles

ModelKit is a standardized packaging format for AI/ML artifacts that streamlines development, ensures broad compatibility, and optimizes resource usage. It enables seamless sharing and collaboration, efficient artifact management, and built-in versioning and tagging, making it a building block for innovation in AI/ML development and deployment.

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How a Mumbai Drugmaker Is Helping Putin Get Nvidia AI Chips

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A Mumbai-based pharmaceutical company, Shreya Life Sciences, is selling top-end Dell servers optimized for artificial intelligence to Russia, which are equipped with Nvidia AI chips. This has raised concerns among the US and its European allies about India's role as an intermediary in the sales of advanced technology to Russia, which is subject to international sanctions.

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Google to develop AI that takes over computers, The Information reports

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Combining Machine Learning and Homomorphic Encryption in the Apple Ecosystem

Apple prioritizes user privacy and uses homomorphic encryption (HE) to enable private server lookups while minimizing data sharing. The company has implemented HE in conjunction with other technologies to power features like private database lookups and machine learning, and has open-sourced an HE library to facilitate adoption in the developer community.

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LLM Agent Honeypot: Monitoring AI Hacking Agents in the Wild

Researchers introduced the LLM Honeypot, a system to detect and monitor autonomous AI hacking agents, by deploying a customized SSH honeypot and analyzing prompt injections. Over a few weeks, they collected 800,000 hacking attempts and identified 6 potential AI agents, aiming to improve awareness and preparedness for AI hacking risks.

ArXiv

Decomposing the Dark Matter of Sparse Autoencoders

Researchers investigated the "dark matter" in sparse autoencoders (SAEs), which refers to unexplained variance in language model activations. They found that about half of the SAE error can be linearly predicted from the initial activation vector, and propose a new type of "introduced error" to explain the remaining, nonlinear error.

ArXiv

Easy real-time collision detection

The article presents a distance field-based collision detection scheme that uses the graphics pipeline to detect collisions between an object and its environment, offering precision and ease of implementation. The scheme can handle various scenarios, including particle systems, but has limitations on the shape of the considered objects.

ArXiv

Improving Pinterest Search Relevance Using LLMs

Pinterest integrates Large Language Models into its search relevance model to effectively predict the relevance of Pins, using a semi-supervised learning approach to scale up training data. This approach leverages various text representations, including captions, link-based text data, and user-curated boards, to improve search relevance across multiple languages and domains.

ArXiv

Solving Global Lyapunov functions: open problem in mathematics with transformers

Language models struggle with complex reasoning tasks, such as advanced mathematics, particularly in finding a Lyapunov function for global stability in dynamical systems. A proposed method for generating synthetic training samples allows sequence-to-sequence transformers to outperform algorithmic solvers and humans in solving polynomial systems and discovering new Lyapunov functions for non-polynomial systems.

ArXiv

Show HN: AI agents working together in a virtual podcast studio. NotebookLM alt

NeuralNoise is an AI-powered podcast studio that uses multiple AI agents to analyze content, write scripts, and generate high-quality audio with minimal human input. It utilizes OpenAI, ElevenLabs, and Streamlit to simplify the process of generating AI podcasts.

Repo

Watch six different LLMs play Texas Hold'em against each other

The AI Poker Arena is a simulated game of poker that uses GitHub Models to compare the performance of multiple small AI models in a competitive environment. The project aims to evaluate AI models in a more nuanced way than traditional benchmarks or human voting, by pitting them against each other in a purely adversarial setting.

Repo

Show HN: CogniSim – Interaction utilites for crossplatform LLM agents

Revyl AI's Mobileadapt is a library that enables cross-platform interaction with mobile devices using Large Language Models (LLMs). It combines the accessibility tree with mark prompting to provide a readable state for the LLM, allowing for more accurate interactions.

Repo

Chain Large Language Model Actions and Workflows Using YAML

COMandA is a command-line tool that enables the composition of Large Language Model (LLM) operations using a YAML-based Domain Specific Language (DSL). It simplifies the process of creating and managing chains of LLM activities that operate on files and information. COMandA supports multiple LLM providers, file-based operations, image analysis, and direct URL input for web content analysis.

Repo

Show HN: Zephyr: New [WIP] NN Jax Framework; Short, Simple, Declarative

The zephyr library is a work-in-progress project that aims to simplify the process of creating neural networks using the JAX library. It focuses on two key aspects: parameter creation and simplicity. Zephyr treats neural networks as pure functions, eliminating the need for special methods or transforms, and allows for maximum control over all parameters.

Repo