PyGraphistry Implementation Workflow for Interactive Graph Intelligence Pipelines in Security Analytics and Risk Investigation
We build a Colab-ready PyGraphistry workflow for interactive graph analytics on enterprise access data. We generate a synthetic dataset of users, devices, IPs, services, roles, and geos, then convert it into nodes and edges. We enrich the graph with risk scores, centrality metrics, community detecti...
Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity
AI agents can't remember past conversations. They must constantly reload or retrieve context, which grows less efficient as tasks get longer and more complex. Memora solves this with a scalable memory system separating what’s stored from how it's retrieved.
The post Memora: A Harmonic Memory Represe...
Gemini’s personalized AI image generation is now free for US users
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.
NVIDIA BioNeMo Agent Toolkit Turns Biomolecular Models Into Callable Skills for AI Agents in Drug Discovery
NVIDIA's open-source BioNeMo Agent Toolkit turns biomolecular models like OpenFold3, DiffDock, and GenMol into documented, callable skills for AI agents. Each skill describes a model's purpose, inputs, artifacts, and failure modes, so an agent can select, run, and interpret it. In NVIDIA's benchmark...
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Imagine coming in to work to learn that a new underling will report to you. The worker is not a person but an AI tool—one that your company nonetheless calls Alex...
Claude Meets Blackwell Ultra: Anthropic’s Models Now Run on NVIDIA GB300 in Azure
Anthropic’s Claude models in Microsoft Foundry — hosted on Microsoft Azure and running on NVIDIA GB300 Blackwell Ultra GPUs — are now generally available, giving Azure-native enterprises a powerful new way to build autonomous and domain-specific AI agents. As agentic AI continues to drive enterprise...
Harper Carroll came to AI education through a CS background at Stanford, machine learning engineering at Meta, and a brief stint at a small GPU compute startup in late 2023, where she noticed that almost no one understood how to fine-tune open source models. She started writing and teaching to help ...
Enterprise investment in AI is booming. Gartner is calling 2026 an “inflection year” for organizations to align their AI projects with strategic business objectives. As the pressure to prove ROI mounts, executives and technology leaders are looking to agentic AI to drive the measurable financial out...
I Completed Five Years in Analytics Consulting: 5 Lessons That Changed How I Work
The tools I use for analytics and reporting have changed more than I expected, yet my questions for any analytics project haven't moved much.
The post I Completed Five Years in Analytics Consulting: 5 Lessons That Changed How I Work appeared first on Towards Data Science.
GenPage: Towards End-to-End Generative Homepage Construction at Netflix
Authors: Lequn Wang, Jiangwei Pan, and Linas BaltrunasFigure 1. Autoregressive homepage generation. GenPage builds a Netflix homepage one row or entity at a time, each one conditioned on what’s already on the page and the user’s context.IntroductionThe Netflix homepage is the first thing users see w...
Open Models, Closed Environments: Palantir Brings Secure AI to US Agencies With NVIDIA Nemotron
Showcasing the importance of open source innovation in American AI, Palantir’s new intelligent engine — introduced today — uses NVIDIA Nemotron open models to serve the needs of U.S. government agencies. Open source software has long been a pillar of U.S. technology leadership. In 1969, DARPA conne...
The following article originally appeared on Angie Jones’s LinkedIn page and is being republished here with the author’s permission. I’m fascinated by the concept of agent memory. LLMs are stateless by design, meaning they have no memory or awareness of past interactions. Each prompt you send to an ...
Meet EverOS: An Open Source Markdown-First Agent Memory Runtime With Hybrid BM25 + Vector Retrieval and Self-Evolving Skills
EverMind has open-sourced EverOS, a local-first memory runtime that stores AI agent memory as plain Markdown indexed by SQLite and LanceDB. It combines hybrid BM25 + vector retrieval, multimodal ingestion, and self-evolving Skills under an Apache 2.0 license. Here's what it is, how the architecture ...
arXiv:2606.27385v1 Announce Type: new
Abstract: The most widely used RANSAC variants score candidate models by counting inliers or summing per-point scores that saturate beyond a residual threshold. Every such score requires a user-supplied parameter that is a function of the inlier scale, which mu...
Unified Zero-Shot Time Series Forecasting: A Darts Foundation
arXiv:2606.27438v1 Announce Type: new
Abstract: Since its initial release in 2020, Darts has become a widely used open-source Python library for time series analysis. A series of foundation models have recently claimed accuracy improvements in zero-shot forecasting, promising a paradigm shift from ...
PairSAE: Mechanistic Interpretability from Pair Representations in Protein Co-Folding
arXiv:2606.27440v1 Announce Type: new
Abstract: Foundation models for structural biology have achieved remarkable performance in predicting biomolecular structure and show promise for the design of proteins and small molecules. Yet understanding which internal features drive their outputs remains c...
AI-Model Network: Concept, Current State and Future
arXiv:2606.27382v1 Announce Type: new
Abstract: While the primary function of computers lies in computation and processing, the core value of the Internet is rooted in sharing and collaboration. Computers create the Internet, and the Internet empowers the value of computers. The rapid development o...
When Does Personality Composition Matter for Multi-Agent LLM Teams?
arXiv:2606.27443v1 Announce Type: new
Abstract: Personality prompting shapes how large language models communicate, yet whether these behavioral shifts affect objective task outcomes remains under-explored. Prior work shows that agents prompted with low agreeableness produce adversarial language, w...
Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning
arXiv:2606.27483v1 Announce Type: new
Abstract: Large language model (LLM) agents have demonstrated strong capability in sequential decision-making, yet they remains fundamentally reactive in long-horizon tasks. Unlike humans who employ "what-if" reasoning to evaluate potential plans before commitm...
Odyssey: Constructing Verifiable Local Truth-Preserving Foundation Models
arXiv:2606.27593v1 Announce Type: new
Abstract: We introduce a categorical framework called ODYSSEY for constructing verifiable, local truth-preserving foundation models as compositions of foundries: building-block architectural components that specify a cover of local contexts, local representatio...