Meta Permits Its A.I. Models to Be Used for U.S. Military Purposes

Meta has announced a shift in policy, allowing US government agencies and contractors working on national security to use its artificial intelligence models, called Llama, for military purposes. This move is an exception to Meta's previous policy, which prohibited the use of its technology for military efforts, and is intended to promote "responsible and ethical" innovations that support the US and its allies.

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DeepMind debuts watermarks for AI-generated text

Google DeepMind has developed a system called SynthID-Text that adds a watermark to AI-generated text, allowing it to be identified as such, without compromising the quality or accuracy of the text. The system has been integrated into Google's Gemini chatbot and made available to developers, but experts acknowledge that it is not foolproof and that tackling the full problem of identifying AI-generated text will require a broader effort.

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What Shapes Do Matrix Multiplications Like?

The performance of matrix multiplication on GPUs can be significantly affected by the shape of the matrices, with certain shapes resulting in faster execution times despite doing more work. This is due to three main factors: compute intensity and parallelization, tiling, and wave quantization, with tiling being the primary cause of performance variations due to its impact on memory layout.

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How a Mumbai Drugmaker Is Helping Putin Get Nvidia AI Chips

An Indian pharmaceutical company, Shreya Life Sciences, is selling top-end Dell servers optimized for artificial intelligence to Russia, which contain Nvidia AI chips. This trade has raised concerns among the US and its European allies, as it appears to be a way for Russia to circumvent sanctions and obtain advanced technology.

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A ChatGPT-like assistant but private for developers

This AI tool offers total privacy with no account, login, or tracking, and all conversations are kept on the user's device. It's free and unlimited to use, powered by state-of-the-art AI technology including Llama 3.1, 3.2, and FLUX.1.

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WebRL: Training LLM Web Agents via Self-Evolving Online Reinforcement Learning

WebRL, a self-evolving online curriculum reinforcement learning framework, trains high-performance web agents using open large language models (LLMs), addressing challenges such as scarce training tasks and sparse feedback signals. WebRL significantly improves the performance of open LLMs, surpassing proprietary models and previous state-of-the-art web agents, and bridging the gap between open and proprietary LLM-based web agents.

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Image-Goal Representations Atomic Control Units for Foundation Model Embodied AI

IGOR (Image-GOal Representations) is a system that learns a unified action space across humans and robots, enabling knowledge transfer among large-scale activity data. IGOR achieves this by compressing visual changes into latent actions, allowing for the training of foundation policies and world models that can be applied to various tasks and even enable human-to-robot knowledge transfer and control.

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PatternBoost: Constructions in Mathematics with a Little Help from AI

PatternBoost is a method that combines classical search algorithms with a transformer neural network to find interesting constructions in mathematics. The technique has been applied to problems in extremal combinatorics, yielding impressive results and even finding the best known solutions to several long-standing problems.

ArXiv

Accuracy-Performance Trade-Offs in LLM Quantization

Researchers conducted a comprehensive study on the accuracy and performance of large language models using various quantization formats, including FP8, INT8, and INT4. The study found that certain formats, such as FP8 and INT8, can achieve high accuracy with minimal degradation, while others, like INT4, offer competitive performance and cost-efficiency in specific deployment environments.

ArXiv

TextLap: Customizing Language Models for Text-to-Layout Planning

Researchers developed TextLap, a method that uses large language models to generate graphical layouts from text instructions, and demonstrated its effectiveness in outperforming strong baselines in image generation and graphical design benchmarks. TextLap uses a curated dataset called InsLap to customize large language models for layout planning, allowing users to create compelling graphical layouts with just text instructions.

ArXiv

Show HN: I wrote an open-source browser alternative for Computer Use for any LLM

Browser-Use is an open-source web automation tool that allows large language models (LLMs) to interact with websites through a simple interface. It supports various LLM models, including those from LangChain, and features interactive element detection, multi-tab management, and customizable actions.

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PiML: Python Interpretable Machine Learning Toolbox

PiML is a Python toolbox for interpretable machine learning model development and validation, offering a range of inherently interpretable models and supporting arbitrary supervised ML models under regression and binary classification settings. It provides various tools for model explainability, fairness, and diagnostics, and can be installed via pip install PiML.

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Dstack: An alternative to k8s for AI/ML tasks

Dstack is a streamlined alternative to Kubernetes and Slurm, designed for AI workloads, simplifying container orchestration in the cloud and on-premises. It supports NVIDIA GPU, AMD GPU, and Google Cloud TPU out of the box and is easy to use with any cloud provider or on-premises servers.

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Show HN: Firecrawl-Simple – Stable fork of Firecrawl optimized for self-hosting

Firecrawl Simple is a stripped-down and stable version of Firecrawl, optimized for self-hosting and ease of contribution, with features like billing logic and AI removed. It can be self-hosted using Docker Compose and supports crawling, scraping, and checking crawl job status through API endpoints.

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The Bunny B1: Demoing a Natrual Language to App Call Interface with SmolLM2

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