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Nvidia & Microsoft push local AI agents on Windows
Winsage
September 5, 2026

Nvidia & Microsoft push local AI agents on Windows

NVIDIA has enhanced the capability to run AI agents locally on its hardware in collaboration with Microsoft and software partners, coinciding with the launch of new RTX Spark Windows PCs. The installation process for local agent software has been simplified, with improved inference speeds and the introduction of NVIDIA PAIR, which distributes inference tasks across multiple PCs on a local network. Three applications benefiting from these enhancements are Hermes Agent, OpenClaw, and Perplexity Portable Computer, all designed to minimize manual configuration. Hermes Agent offers a one-click local setup for RTX and DGX systems, automatically detecting the GPU and optimizing model selection. OpenClaw simplifies local model setups for RTX GPUs with at least 24GB of VRAM, backed by an open-source community. Perplexity Portable Computer, already available on Linux, is extending support to NVIDIA RTX GPUs and Windows. NVIDIA is also improving performance in the open-source inference stack, achieving throughput increases of up to 1.9 times on GeForce RTX 5090 and up to 1.4 times on DGX Spark clusters. The PAIR software identifies compatible PCs on the same network to optimize computing resources, supporting various hardware configurations. The upcoming RTX Spark Windows PCs, set to launch in October, will include compact desktop and laptop designs featuring Blackwell GPU and Grace CPU architecture. Game publishers like Electronic Arts and Ubisoft are developing titles for these systems. Additionally, CyberLink's PhotoDirector AI PC Mode will integrate local AI processing for creative tasks, emphasizing the trend of migrating generative AI workloads from cloud to local devices. NVIDIA notes that over half of U.S. households have two or more PCs, indicating potential for maximizing computing power.
Microsoft PowerToys will soon take full advantage of the same AI that powers Copilot+ PCs
Winsage
August 11, 2026

Microsoft PowerToys will soon take full advantage of the same AI that powers Copilot+ PCs

Microsoft PowerToys has introduced on-device support for Phi Silica, a small language model, in its latest preview version, enhancing the Advanced Paste feature for clipboard management. Advanced Paste can format clipboard content in various formats, extract text from images using OCR, and transcode audio and video files. It now supports multiple AI models, including local options like Foundry Local and Ollama. The latest version, PowerToys v0.101.2211.0, includes improvements such as enhanced AI customization for Advanced Paste, better dialog handling in the Command Palette, and improved window management features. Mouse Jump has transitioned to the newer WinUI app architecture, and new settings have been added for update channel selection and bug reporting.
Google Cloud boosts AlloyDB search for CJK text with Gemini
Tech Optimizer
July 16, 2026

Google Cloud boosts AlloyDB search for CJK text with Gemini

Google Cloud has enhanced AlloyDB by integrating AlloyDB AI Functions with Gemini models to improve search indexing for logographic languages like Chinese, Japanese, and Korean. This update addresses challenges in database search functionality, particularly for languages written in continuous scripts, where traditional PostgreSQL text parsing struggles. Developers can now invoke Gemini models directly from SQL to facilitate word segmentation and stop-word removal before creating full-text indexes, offering a more efficient alternative to traditional methods. The architecture maintains raw text, segmented text, search vectors, and embeddings in a single table, with generated columns ensuring automatic updates to search vectors and embeddings. A batching process using a PL/pgSQL stored procedure allows for efficient processing of extensive document collections by aggregating rows into arrays for model requests, thus reducing row-locking issues. Google Cloud provides tailored text search configurations for different datasets, suggesting a simple configuration for solely Chinese text and an English configuration for bilingual datasets. This preprocessing logic can also be applied during query execution, allowing user searches to be directed to Gemini for text segmentation and stop-word elimination. AlloyDB supports RUM indexes on search vectors, which store lexeme positions for computing relevance and word distance, enabling rapid query responses. Additionally, a hybrid search methodology combines full-text and vector search using a ScaNN index on embeddings, merging results through Reciprocal Rank Fusion. This development allows for robust multilingual search and vector retrieval solutions within the database environment, eliminating the need for external microservices.
silver Android smartphone
Tech Optimizer
July 2, 2026

EDB Named a Leader in Multimodel Data Platforms Evaluation

EDB has been recognized as a Leader in The Forrester Wave: Multimodel Data Platforms, Q2 2026, with EDB Postgres AI (EDB PG AI) achieving the highest scores in Vision, Innovation, Roadmap, and Partner Ecosystem criteria. EDB PG AI integrates transactional, analytical, and AI workloads into a unified platform, supporting open-source frameworks and enabling various deployment options. The platform features governance at the data layer and is designed for operational efficiency, allowing organizations to implement sovereign AI quickly. EDB PG AI can be deployed on-premises, in hybrid environments, or across cloud infrastructures, backed by partnerships with companies like Dell, IBM, and NVIDIA.
EDB launches agentic Postgres AI with governance tools
Tech Optimizer
June 26, 2026

EDB launches agentic Postgres AI with governance tools

EDB has introduced new features for its Postgres AI platform, including an agentic database and converged analytics capabilities, allowing enterprises to run AI agents alongside transactional workloads on a unified PostgreSQL foundation. The platform includes governance tools that position control mechanisms at the data layer and integrates AI processing with operational data, enabling businesses to connect live records with AI systems without transferring sensitive information. The agentic database can monitor over 200 metrics, identify issues, suggest changes, and apply fixes automatically based on user-defined policies. It consolidates various data types through a single SQL interface, significantly accelerating database tuning processes and enhancing application performance. EDB has also expanded its analytics capabilities with a zero-ETL architecture for real-time analysis and large-scale warehousing. EDB PG AI for ClickHouse targets real-time analysis, while EDB PG AI for WarehousePG focuses on historical analysis at petabyte scale. The platform claims up to 30 times faster query performance compared to legacy systems and improved scaling efficiency. EDB's platform integrates vector search and retrieval for AI agents, demonstrating lower query latency and higher retrieval accuracy than competitors. NTT East is using EDB PG AI for AI-driven network operations, while the governance feature manages agent access at the data querying point using native Postgres roles and row-level security. The platform can be deployed on-premises, in hybrid environments, or across cloud infrastructures, with partnerships including Dell, IBM, Nvidia, Red Hat, and Supermicro.
Pixel Screenshots just moved away from using on-device AI only, but is it less private?
AppWizard
June 19, 2026

Pixel Screenshots just moved away from using on-device AI only, but is it less private?

The Pixel Screenshots app has transitioned from relying solely on on-device AI to a hybrid model that incorporates cloud processing. The latest update, version 1.26.134.11, reflects this change by revising the app's settings to indicate that AI processing may occur on-device or in the cloud. Google emphasizes that user privacy will be prioritized, utilizing a “secure, isolated environment” for processing. The update is currently rolling out and may not yet be available to all users in the Play Store.
Microsoft tests Windows AI features on RTX GPUs, not just NPUs
Winsage
June 12, 2026

Microsoft tests Windows AI features on RTX GPUs, not just NPUs

Microsoft is expanding the availability of its Copilot+ features to users with Nvidia RTX GPUs, allowing older PCs to utilize advanced AI tools such as text summarization, image upscaling, and code generation. This change is facilitated by the experimental release of the Windows App SDK 2.2, which enables AI functionalities to run on dedicated Nvidia RTX GPUs. Features include text rewriting, editing, and advanced capabilities in the Microsoft Photos app. Users must download the experimental version of WinAppSDK 2.2, have an Nvidia GeForce RTX 30 series GPU with at least 6GB of VRAM, and enable Developer Mode on their PC. This shift reflects a broader strategy to leverage local AI models while still using cloud resources, aiming to democratize access to AI capabilities across a wider range of devices.
This is how RTX Spark and Windows will finally make AI agents practical for your PC
Winsage
June 6, 2026

This is how RTX Spark and Windows will finally make AI agents practical for your PC

Nvidia is developing the RTX Spark, a powerful chip that integrates AI agents into consumer PCs, in collaboration with Microsoft. This chip features a CPU and an RTX 5070-class GPU, providing 1 petaflop of computing power and up to 128GB of unified memory, enabling sophisticated AI agents to operate directly on devices without the need for dedicated AI PCs or cloud services. Windows will introduce new security frameworks to facilitate the use of AI agents, addressing previous limitations that hindered their effectiveness on PCs. Users will be able to delegate complex tasks to AI agents, which can learn from interactions and adapt to individual workflows, enhancing the computing experience. However, challenges such as market demand, compatibility issues, and competition from other companies may impact the success of the RTX Spark.
Nvidia unveils DGX Station for Windows AI workstations
Winsage
June 2, 2026

Nvidia unveils DGX Station for Windows AI workstations

NVIDIA has launched the DGX Station for Windows, a deskside system designed for extensive AI workloads on Windows machines, marking a shift from traditional Linux-based systems. It features the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip, capable of executing AI models with up to 1 trillion parameters. The system supports model training, fine-tuning, inference, data science, and multi-agent development, allowing hundreds of agents to run concurrently. A key feature is the NVIDIA OpenShell on Windows, which provides a secure runtime environment for autonomous agents. The DGX Station integrates with existing enterprise management frameworks and extends Windows security and compliance tools. Its hardware architecture includes a Blackwell Ultra GPU, a 72-core Grace CPU, up to 748GB of coherent memory, and networking capabilities of up to 800Gb/s. It is designed for individual specialists or collaborative teams and can be paired with an NVIDIA RTX PRO 6000 Blackwell Workstation GPU. The DGX Station will be available through vendors like ASUS, Dell Technologies, GIGABYTE, HP, MSI, and Supermicro.
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