Gemini 2.5 Flash Image

Google has introduced Gemini 2.5 Flash Image, a state-of-the-art image generation and editing model that enables users to blend multiple images, maintain character consistency, and make targeted transformations using natural language. The model is available via the Gemini API, Google AI Studio, and Vertex AI, with a pricing of $30.00 per 1 million output tokens, and offers features such as prompt-based image editing, native world knowledge, and multi-image fusion.

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Claude for Chrome

Anthropic is developing a Chrome extension for its AI assistant Claude, which will allow it to interact directly with users' browsers, but the company is first addressing safety and security challenges, such as prompt injection attacks, through controlled testing with 1,000 trusted users. The testing aims to identify vulnerabilities and improve Claude's defenses, which have already shown promising results in reducing attack success rates, before making the extension more widely available.

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Will Smith's concert crowds are real, but AI is blurring the lines

A video clip from a Will Smith concert has gone viral, with many accusing him of using AI to generate fake crowds, but it has been revealed that the crowds are actually real, composed of footage from multiple concerts on his European tour. The video's poor quality and AI-like artifacts are instead attributed to two levels of manipulation: Will Smith's team using AI image-to-video models to generate short clips from photos, and YouTube's post-processing experiment that unblurred and denoised the video, resulting in an unpleasant, smeary look.

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Why I'm declining your AI generated MR

The author, a senior computer scientist, outlines scenarios where a merge request (MR) doesn't deserve a code review due to misuse of AI, such as generating low-quality or unnecessary code, and provides guidelines for identifying and addressing these issues. The author emphasizes the importance of responsible AI use and code reviews in maintaining project quality and promoting learning and improvement among developers.

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Proposal: AI Content Disclosure Header

This document proposes a new HTTP response header field called AI-Disclosure to provide a machine-readable way to disclose the presence and degree of Artificial Intelligence (AI) generated or AI-assisted content in web responses. The header is designed to be compatible with HTTP structured field syntax and provides metadata for user agents, bots, and archiving systems, offering a simple and advisory signal for basic AI involvement awareness.

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LLM Speed Up Breakthrough?

Jet-Nemotron is a new family of hybrid-architecture language models that matches or exceeds the accuracy of leading full-attention models while significantly improving generation throughput. The Jet-Nemotron-2B model achieves comparable or superior accuracy to other models across various benchmarks, delivering up to 53.6x generation throughput speedup and 6.1x prefilling speedup, outperforming some larger-scale models despite its smaller size.

ArXiv

2-D Sparse Parallelism for Deep Learning Recommendation Model Training

The increasing complexity of deep learning recommendation models requires large-scale distributed systems to efficiently train vast amounts of data, particularly for managing sparse categorical features with trillions of parameters. A novel two-dimensional sparse parallelism approach has been proposed, which enables efficient training and achieves nearly linear training speed scaling up to 4K GPUs, setting a new state-of-the-art benchmark for recommendation model training.

ArXiv

AlphaX: An AI-Based Value Investing Strategy for the Brazilian Stock Market

Researchers have been exploring the use of artificial intelligence (AI) techniques, including neural networks and deep learning, to develop autonomous trading strategies, but many of these strategies perform poorly in real markets despite promising backtesting results. A new AI-based strategy, AlphaX, inspired by Value Investing, was developed and tested through simulations that controlled for biases, and it outperformed major Brazilian market benchmarks and technical indicators, showing statistically significant results.

ArXiv

No evidence ageing/declining populations compromise socio-economic performance

Concerns about declining or ageing populations leading to weaker economies and lower living standards are often based on oversimplified interpretations of economic models and driven by political agendas rather than evidence. In reality, data analysis shows that countries with low or negative population growth tend to perform better on various socio-economic indicators, suggesting that long-term prosperity depends more on investments in education, skills, and technology than on population size.

ArXiv

Audio-Visual Contact Classification for Tree Structures in Agriculture

Robots performing tasks like pruning and harvesting in agriculture need to identify whether they're contacting rigid or soft materials to ensure safe manipulation, but vision alone is often insufficient due to occlusion and limited viewpoints. A proposed multi-modal classification framework combines vibrotactile (audio) and visual inputs to identify contact classes, achieving an F1 score of 0.82 and demonstrating the potential of audio-visual learning for manipulation in unstructured environments.

ArXiv

Show HN: Sideko – Hybrid deterministic/LLM generator for API SDKs and docs

Sideko is a tool that automates API work and accelerates integrations, providing features such as SDKs, mock servers, API documentation, and CLI tools. It can be installed on various platforms, including macOS, Linux, and Windows, and offers a range of resources, including documentation, issue reporting, and licensing information, to support its use.

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Show HN: Pantheon-CLI – Open-Source Python Claude Code and Smart Notebook

Pantheon-CLI is an open-source, infinitely extensible scientific framework that enables humans to interact with data in a more intuitive and conversational way, using a combination of natural language and code. It provides a terminal-based interface and a notebook interface, allowing users to perform complex data analysis tasks, including single-cell and spatial genomics, with the help of an AI-powered assistant that can understand and generate code in multiple programming languages.

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Show HN: 70 Days → 800 GitHub Stars (Cold Start) – My Secret Was a Problem Map

The WFGY project is a semantic reasoning engine designed to solve core AI problems such as hallucination, context drift, and logic failure, with a goal of igniting a new civilization layer built on semantic reasoning. The project includes various modules, such as TXT OS, Blah Blah Blah, and Blur Blur Blur, which provide functionalities like semantic Q&A, image generation, and reasoning games, all running natively as .txt apps without installation or dependencies.

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Show HN: Ubon – a solution for the "You're absolutely right" debugging dread

Ubon is a fast static analysis tool designed to identify and fix issues in AI-generated "vibe-coded" apps, including secrets, insecure cookies, accessibility problems, and broken links. It provides a human-friendly triage system with colorized output, explanations, and confidence scores, and can be used with AI assistants to streamline the debugging process and reduce back-and-forth conversations.

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Show HN: Bagel – ChatGPT for Physical Data

Bagel is a tool for extracting, transforming, and analyzing robotics data, allowing users to cast topic messages to a pandas DataFrame or PyArrow Dataset in just a few lines of code. It supports various log formats, including ROS 1 and 2, and PX4, and can be run locally or in a Docker container, enabling efficient data processing and analysis without the need for cloud computing.

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