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Winsage

February 22, 2025

Announcing Windows 11 Insider Preview Build 26120.3291 (Dev and Beta Channels)

Windows 11 Insider Preview Build 26120.3291 (KB5052080) has been released for the Dev and Beta Channels, introducing enhancements for Snapdragon-powered Copilot+ PCs. Key updates include an improved Windows Search feature that allows users to find cloud-stored files directly from the taskbar search box and a refined Recall (Preview) experience, which will delete previous snapshots but continue saving new ones if enabled in Settings. For Beta Channel users, the same updates are available as optional upgrades, with plans to make them recommended later this year. Insiders can switch from the Dev to the Beta Channel while both channels share identical build numbers, but this option will close once the Dev Channel progresses to higher build numbers. The improved Windows Search feature supports finding cloud-stored photos by describing them, available for users signed into OneDrive with a personal Microsoft account. Support for third-party cloud providers is expected soon. The update also includes fixes for live captions, File Explorer reliability, and issues with Remote Desktop. Known issues include inaccuracies in build version display after a PC reset and problems with Recall not saving snapshots automatically. An update to the Snipping Tool introduces a new trim feature for screen recordings, allowing users to adjust start and end times.

Winsage

February 22, 2025

4 Windows 11 features that make me regret upgrading

Windows 11 has become popular among users, but some experience frustrations with its features. The Copilot feature is heavily integrated, prompting users to engage with it frequently, which many find intrusive. The redesigned Start Menu is seen as cluttered and less user-friendly compared to Windows 10, requiring customization for better usability. The Widgets button on the taskbar has become a distraction, leading many to disable it for improved focus. Windows 11 frequently upsells Microsoft services, requiring a Microsoft account and inundating users with promotional notifications. Overall, users feel that navigating Windows 11 has become adversarial, prioritizing notifications over user experience and complicating basic usability.

Winsage

February 22, 2025

Windows upgrades to Start, Search, and Share might arrive sooner than you expect

A new Drag Tray feature allows users to share files by dragging them to a tray at the top of the screen, simplifying the sharing process. The Start menu can now be customized with a Grid view or a Category view for easier navigation. Windows Search has been updated to allow users to find images by typing a description instead of the file name, including images stored in the cloud. This search enhancement is currently available on Snapdragon-powered Copilot+ PCs, with support for AMD and Intel models expected soon.

Winsage

February 21, 2025

Windows tests long-awaited changes to Start, Share, and Search

Microsoft has released two test builds of Windows 11: Insider Preview Build 22635.4950 (KB5052078) in the Beta Channel and Insider Preview Build 26120.3291 (KB5052080) as an optional release in both Beta and Dev Channels. Build 26120.3291 introduces a semantic search capability, allowing searches by descriptive terms, but is limited to Qualcomm-powered Snapdragon PCs. Users of the Recall feature will lose all saved snapshots during the upgrade process. Build 22635.4950 tests a new Share interface that simplifies file sharing through a drag-and-drop mechanism. The Start menu will receive new configuration options, including a grid view and a "categories" view for app organization. These updates will be available to Windows Insiders receiving updates for Windows 11, version 24H2.

Tech Optimizer

February 21, 2025

Self-managed multi-tenant vector search with Amazon Aurora PostgreSQL

Organizations are using generative AI and machine learning tools to extract value from unstructured data, employing specialized machine learning models to convert data into vectors for efficient searching and retrieval. Amazon Aurora PostgreSQL-Compatible Edition, with the pgvector extension, allows developers to create a vector store for generative AI applications. Multi-tenant architectures in software-as-a-service (SaaS) applications ensure tenant data isolation to maintain security and privacy. In a multi-tenant scenario, home survey requests are processed, and survey reports are stored in Amazon S3. Embedding models convert these documents into vector embeddings, which are stored in a vector store. There are two approaches to building a vector-based application: a self-managed approach, where developers handle data processing and queries, and a fully-managed option using Amazon Bedrock Knowledge Bases. The self-managed approach involves coding to process data, generate vector embeddings, and store them in Aurora. The architecture includes data ingestion via AWS Lambda, embedding conversion, SQL queries for data retrieval, and response enhancement using a large language model (LLM). Key terminologies include vector embeddings, embedding models, chunking, pgvector, HNSW index, and IVFFlat index. The process of creating a vector store involves configuring the Aurora PostgreSQL database, enabling the pgvector extension, and establishing a schema for the vector store. The vector table includes fields for UUID, vector embeddings, text chunks, metadata, and tenant identification. Data ingestion requires coding to convert data into embeddings and insert them into the database. Retrieval of vector data is crucial for enhancing prompts sent to LLMs, with various distance functions supported for identifying similar vectors. Multi-tenancy is enforced using row-level security in PostgreSQL, ensuring tenant data isolation. The process includes updating query functions to support tenant isolation and setting the current tenant ID for queries.

AppWizard

February 21, 2025

Minecraft sees release of “Dungeons & Dragons: A New Quest” DLC today

Players can immerse themselves in Dungeons & Dragons: A New Quest, where they join heroes Katra and Vaer on a journey to reclaim Vaer’s soul from dark forces. The adventure begins in Candlekeep, where they must find the powerful "Deck of Many Things." Players can choose from four classes: Barbarian, Rogue, Wizard, and Paladin, and customize their stats. The quest explores iconic locations like Candlekeep, Sword Coast, Icewind Dale, and Caer Dineval, featuring formidable foes such as owlbears and Mind Flayers. A complimentary Dragon Mask is also available in the Dressing Room. Dungeons & Dragons: A New Quest is available at the Minecraft Marketplace.

Tech Optimizer

February 21, 2025

Multi-tenant vector search with Amazon Aurora PostgreSQL and Amazon Bedrock Knowledge Bases

The article discusses the implementation of a multi-tenant vector store using Amazon Aurora PostgreSQL-Compatible Edition and Amazon Bedrock Knowledge Bases. It outlines a scenario where users request home surveys, and surveyors update findings stored in an Amazon S3 bucket. The process involves converting documents into vector embeddings for enhanced natural language queries through the Retrieval Augmented Generation (RAG) technique. Key steps include: 1. Ingesting data from S3 into Amazon Bedrock Knowledge Bases. 2. Using an embeddings model to convert documents into vector embeddings. 3. Storing vector embeddings, data chunks, and metadata in Aurora with pgvector. 4. Submitting natural language queries that are transformed into embeddings for retrieval from the vector store. 5. Forwarding relevant documents to a large language model for response generation. To set up the vector store, prerequisites include access to an Amazon Aurora PostgreSQL-compatible database, Amazon S3 for document storage, and Amazon Bedrock for managing knowledge bases. The article provides SQL commands for creating the necessary schema, vector table, and index in Aurora, as well as instructions for ingesting data and ensuring multi-tenant data isolation through metadata filtering. Best practices for deploying a multi-tenant vector store include optimizing chunk size, evaluating embedding models, and monitoring query performance. The article emphasizes the benefits of fully managed solutions to reduce operational complexity.

Winsage

February 21, 2025

How to Fix the “Windows Could Not Find a Driver for Your Network Adapter” Error

The "Windows Could Not Find a Driver for Your Network Adapter" error occurs when Windows cannot communicate with the network adapter due to outdated, corrupted, or missing drivers. To resolve this issue, users can reinstall network adapter drivers by opening "Device Manager," locating the network adapter under "Network Adapters," right-clicking it to select "Uninstall Device," confirming the uninstallation, and then scanning for hardware changes to prompt Windows to reinstall the adapter and its drivers. Alternatively, users can perform a network reset, which removes all network adapters and restores settings to their original defaults. This involves opening the Settings app, selecting "Network & Internet," clicking on "Network reset," and then clicking "Reset now" to initiate the process.

Winsage

February 20, 2025

This Is the Ultimate Tool for Setting Up a New Windows Computer

WinUtil is a free utility developed by Chris Titus that simplifies the setup process for new computers running Windows. It allows users to install multiple applications with a few clicks, featuring a user-friendly interface divided into five tabs: Software Installation, Tweaks, Config, Updates, and Microwin. Users can select desired software, make system adjustments, configure Windows preferences, manage update installations, and create customized Windows installers. The tool supports exporting application collections and tweaks for easy replication on other computers, and comprehensive documentation is available for further exploration of its features.

AppWizard

February 20, 2025

The least used app on my Android phone is… the Google app?!

The Google app, launched over 15 years ago, enhances mobile search capabilities on Android devices and serves multiple essential functions, including powering the search widget, the Discover feed, Circle to Search, Google Lens, the Saved tab, and ad personalization options. A poll indicates that 34% of users utilize the app daily, 9% use it often, 16% rarely, and 41% never use it. Despite its perceived redundancy, the app is an uninstallable system app, crucial for maintaining various Android features and functionalities.