
Google is expanding Gemini’s personalized AI image generation to eligible free users in the U.S., allowing the chatbot to create images based on your interests and data from connected Google apps.
Google has made its personalized image generation feature in the Gemini app free for all eligible U.S. users, expanding access beyond paid subscription tiers. The feature uses data from a user's Google account connections like email, photos, and search history to generate images based on their interests and preferences without requiring explicit prompts. Personal Intelligence is an opt-in feature that users can toggle on or off through the Tools menu. This expansion reflects Google's broader effort to make advanced Gemini capabilities more widely available after the service reached 750 million monthly active users earlier this year.

OpenClaw just released native companion apps for iOS and Android. The iOS app is listed as ‘OpenClaw – AI that does things.’ Both apps are free to download. They are not standalone chatbots. Each phone becomes a node in a self-hosted agent network. The assistant itself runs on a separate Gateway. That separation is the whole design. TL;DR OpenClaw’s iOS and Android apps are companion nodes, not standalone assistants. The Gateway runs the agent; phones add came

In this tutorial, we build an advanced, Colab-ready workflow around PyGraphistry for interactive graph analytics and visualization. We start by creating a realistic enterprise-style access dataset, transforming it into nodes and edges, and enriching the graph with risk scores, anomaly indicators, centrality metrics, community detection, and layout embeddings. We then use PyGraphistry to bind graph structure, visual encodings, labels, tooltips, and filtered subgraphs, and to generate local inter

AI scientists are becoming a new interface for scientific computing. These agents read papers, write code, generate hypotheses, call APIs, and inspect files. But science is not software engineering. No test suite turns green when a hypothesis is correct. Discovery stays iterative, uncertain, and grounded in the physical world. That gap is what NVIDIA is targeting. NVIDIA published a hands-on walkthrough for its BioNeMo Agent Toolkit. The argument is direct. A general coding agent pointed at
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