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Microsoft will likely soon follow Sony and stop the production of physical discs for Xbox games. But instead of leaving physical discs behind entirely, sources familiar with Microsoft's plans tell me the company has quietly been working on a disc-to-digital feature that will allow Xbox owners to digitize their existing physical game collections. Xbox employees […]

This continues from Part ① . In Part ②, we'll configure the common settings and the internal-processing Power Automate flows. Common Settings Setting Up Connections Open Power Automate ( https://make.powerautomate.com ) Go to "Data" → "Connections" → "New connection" and create a Microsoft Dataverse connection Do the same to create an Office 365 Outlook connection Basic Flow Creation Steps Click "Create" → select "Automated cloud flow" (event-triggered) or "Scheduled cloud flow" (recurring) Name flows in the format [Zone]-[Number] [Description] (e.g., "A-1 Opportunity Stage Stall Alert") Always run a test after creating a flow to verify it works 2. Internal-Processing PA Flows — 4 Flows (Write-back portions of A-4, C-5, C-6, D-3) Once the common settings are done, it's time to build. A-4: Write Back Stage Changed Date Without this flow, the stall-day calculations in A-1 and B-1 will not work. Implement this first. In Microsoft Dynamics 365 (D365), a "stage" refers to a major milestone in a process — such as a sales deal or customer engagement — that guides the responsible person through what needs to happen next. It's how a series of activities is visualized and managed. From here, all work is done in Power Automate. Step Task Details 1 Create the flow "Automated cloud flow" → select trigger "When a row is added, modified or deleted (Dataverse)" 2 Configure trigger Table: Opportunities / Change type: Modified 3 Add condition Add a "Condition" action: "When Status Reason (statuscode) has changed" 4 Write-back action "Update a row (Dataverse)" → set cr917_stage_changed_date to utcNow() C-5: Auto-Set Renewal Date + Auto-Create Renewal Opportunity (on Won) On Won close, two things happen: ① auto-set the renewal date to close date + 365 days, and ② auto-create a new Opportunity for the renewal cycle and add it to the pipeline. Step Task Details 1 Create the flow "Automated cloud flow" → trigger "When a row is added, modified or deleted (Dataverse)" 2 Configure trigger Ta

INTRODUCTION When I started using Power BI, I only thought of visuals like charts and graphs. However, as I progressed, I discovered a great data dashboard is built on great data models. Data Modelling is the process of organizing your data tables and defining how they relate to each other so Power BI can combine them into meaningful reports and dashboards. Good, designed data makes it easier and faster to maintain. Why is data Modelling Important Well-organized data makes it easier to manage data. Reduction of the duplicates. Ensures data consistency. Understanding Relationships Relationships allow the data table to give communication using fields. For example, Customer Table stores all information about a customer. Product Table store product details Sales Table stores all information about the transactions. Power BI connects the information between the customer’s name and Customer Id rather than repeating them it connects the information using joins. Going through relationships I discovered schemes. Scheme is the way tables are organized in databases. There are different types of schemes e.g. Star Schema, snowflake schema and Flat table. Star Schema A star schema is a data model with one central fact table and dimension table surrounding it. Fact table A table that stores events, transactions of what happened. • Total sales • average sales • quantity sold Dimension table A dimension table describes the items in the fact table. The table contains descriptive information. • The customer table describes the customer • How much sales were made The fact table sits in the center, while the dimension tables surround it—forming a star. Dashboard designs A good dashboard has to fit one page. A dashboard should show critical information. Update automatically when data changes. Focus on data understanding and decision making. Conclusion Power BI taught me that a great report are built from a a great dashboard which is achieved by having great models. Structuring a data into

Microsoft is set to announce a wave of layoffs for its Xbox studios and employees next week. Sources familiar with Microsoft's plans tell The Verge that the layoffs will lead to studio closures or spinoffs, potential mergers of studios, and canceled games. I understand Microsoft is currently weighing closing at least five studios, including the […]

To this day, we have yet to see a quantum computer conclusively perform a single useful task. Existing machines are simply too small and error-ridden to solve commercially relevant problems. That hasn't stopped Donald Trump's science adviser from promising a "quantum computer powerful enough for scientific discovery by 2028" and Trump from issuing a new […]

Microsoft has announced the limited public preview of Copilot Autofix for GitHub Advanced Security for Azure DevOps, extending AI-powered vulnerability remediation to teams using Azure Repos. By Craig Risi

Xbox union members argue for transparency and good-faith bargaining.

You export a CSV from a UK system and double-click it in US Excel — 28/05/2026 suddenly looks like May 28, or something even stranger. The file isn't corrupt. Excel is guessing your date format based on your computer's locale. This short guide covers why that happens, how to import CSV correctly, and how to batch-fix dates that are already wrong. For the full walkthrough with examples, see the official guide: How to Fix Excel CSV Date Import Problems . Why Excel breaks CSV dates A CSV is plain text. It does not store whether a value is a date or a string. When you double-click to open, Excel parses using your regional settings: US Excel: MM/DD/YYYY UK / Europe: DD/MM/YYYY Dates like 03/04/2025 are the most dangerous — both parts are ≤ 12. US Excel may read April 3; UK Excel reads March 4. Excel won't warn you. Other common traps: Dates exported as serial numbers (e.g. 44927 ) Two-digit years triggering century guesses Re-saving as CSV destroys formats a second time The right way: don't double-click the CSV Open Excel first — don't double-click the .csv file Data → Get Data from Text/CSV (older Excel: Data → From Text) Set date columns to Text if you need to preserve the original string Confirm the source region (US / UK), then convert to a single format For team data exchange, agree on ISO 8601: YYYY-MM-DD in your schema — unambiguous, sorts correctly as text, and works in JSON APIs and databases. Ambiguous value US reads as UK reads as Safe format (ISO) 03/04/2025 2025-04-03 2025-03-04 Confirm source region 28/05/2026 — 2026-05-28 2026-05-28 05/28/2026 2026-05-28 — 2026-05-28 Already broken? Fix dates in the browser (no server upload) I built a free tool cluster on FormatList — everything runs locally in your browser : 1. Date Format Fixer — bulk repair Paste a date column or upload .csv / .txt Ambiguous rows highlighted; optional US / UK preference Export ISO / US / UK or download a fixed CSV Best for: normalizing a whole column to ISO before a database or API imp

Nine jurors. Two hours of deliberation. Twenty-six claims at the original federal complaint's peak. Three surviving claims at trial. Zero claims surviving the verdict. One hundred fifty billion dollars of maximum disgorgement exposure if the verdict had gone the other way. One hundred thirty billion dollars of OpenAI Foundation equity stake under the October 28, 2025 recapitalization. Thirty-eight million dollars of total Musk contributions per his sworn trial testimony. Forty-four million per the legal complaint. Eight years from the January 2, 2016 Sutskever-Musk "less open / Yup" email exchange to the August 2024 federal filing date. Three years of statute-of-limitations runway on the breach-of-charitable-trust claim; two years on the unjust-enrichment claim. The verdict in Musk v. Altman came in this morning at the federal courthouse on Clay Street in Oakland, before Judge Yvonne Gonzalez Rogers in the Northern District of California. The companion piece, The Calendar Technicality , makes the doctrinal argument that the procedural dismissal is the substantive determination California charitable-trust law would have produced on the merits as well. This piece takes the same conclusion through the numbers. The dollar-and-time math closed the merits door before the doctrinal door even came into view. Two hours, in context Federal-court civil-trial deliberations on complex commercial cases typically run between one and five days. The Administrative Office of the U.S. Courts' annual judicial-business reports show median civil-jury deliberation in the multi-day range for cases with three or more issues to resolve and dollar exposure above one billion. The two-hour deliberation in Musk v. Altman is roughly one to two standard deviations below the median for cases of this complexity. The brevity is not a function of jury inattention. The trial ran three weeks. Roughly four hours of testimony came from Altman alone on May 12, with cross-examination opening with Musk's lea

About a quarter of PCs are still running Microsoft's previous operating system.

The company says the increases are being driven by rising memory and console storage prices, with costs more than 2.5x higher than previous levels.

Microsoft just added a cheaper 12-inch Surface Pro and 13-inch Surface Laptop to its lineup. Both models come equipped with 8GB of RAM instead of 16GB, costing $849 for the specced-down Surface Pro and $949 for the Surface Laptop, as spotted earlier by Windows Central. When the 12-inch Surface Pro and 13-inch Surface Laptop launched […]

A critique published in Nature Wednesday calls the basic technology behind Microsoft's "breakthrough" quantum computing chip the Majorana 1 into question. Microsoft unveiled the chip in February 2025 and said it featured a brand-new technology known as a topological qubit. Topological qubits, they said, would be the "building blocks" for their future quantum computer. Microsoft […]

The RAM, storage, and component crunch has come for new laptop prices. Plenty of models have gone up in price after being on the market for months, and so have those that’ve been on shelves for over a year. Plus, many new models are releasing at higher prices than the previous generation. So, it really […]

At this year's Microsoft Build 2026, Microsoft unveiled a broad set of enhancements to Azure Kubernetes Service (AKS) aimed at making Kubernetes a first-class platform for AI training, inference, and large-scale cloud-native applications. By Craig Risi

Microsoft inked a 20-year power purchase agreement with Chevron, locking in decades of carbon emissions from a new natural gas power plant.

Azure Functions shipped a serverless agents runtime in public preview at Build 2026. Agents are defined in .agent.md markdown files with YAML triggers, MCP server access, 1,400+ connectors, and sandboxed execution. The Functions team confirmed to InfoQ that the runtime adds no cold start overhead and no billing premium beyond standard Flex Consumption. By Steef-Jan Wiggers

Everyone is talking about AI Agents. But before you build an AI Agent, there is one concept you absolutely need to understand: Generative AI. Generative AI is the technology that transformed software from systems that simply follow rules into systems that can understand language, generate responses, reason through instructions, and assist users in a natural way. As part of my new course: Develop Your First AI Agent with Microsoft Foundry I published the first lesson where we explore the journey from traditional software to Generative AI and understand why modern AI Agents became possible. 🎥 Watch the video here: Why This Topic Matters Many developers jump directly into AI Agents, prompts, tools, and frameworks. However, without understanding the evolution of AI, it becomes difficult to understand: Why AI Agents exist Why Large Language Models are important Why prompts work Why tools are needed How modern AI systems actually operate In this lesson, we start from first principles and build the foundation required for the rest of the course. What You'll Learn Traditional Software For decades, software followed a simple pattern: Input → Rules → Output Developers explicitly defined every behavior. This worked well until humans started interacting with software using natural language. Why Rule-Based Systems Break Imagine building a dietician chatbot. Users might ask: What should I eat? Suggest a healthy breakfast. What foods contain protein? Can I eat oats daily? All of these questions are similar. Yet they are phrased differently. Supporting thousands of variations quickly becomes impossible with manually written rules. Predictive AI Machine Learning introduced a new approach. Instead of writing rules, we train models using data. Examples include: Spam Detection Fraud Detection Recommendation Systems Predictive AI can make decisions. But it still cannot create content. Prediction vs Creation A predictive model can answer: Fraud probability: 87% But can it explain why? Ca

Microsoft recently introduced at Build 2026 Microsoft Scout, an always-on agent. Scout belongs to a new category of agents Microsoft called Autopilots: always-on agents that work autonomously on a user’s behalf with their own identity, without needing to be prompted each time. Microsoft Scout integrates with Work IQ and is based on the open-source agent framework OpenClaw. By Bruno Couriol

Microsoft has finally refreshed its premium Surface Laptop and Surface Pro with new chips, but the update comes with a steep price hike.