Author: Carter

Posted on June 1, 2026 by Joe Heck, Swift Documentation Workgroup Member, Apple CNCF projects highlighted in this post Today’s Swift services often operate on the same cloud-native platforms that power much of the modern Kubernetes ecosystem—including ConfigMaps, containerized applications, declarative deployments, and service lifecycle management. Projects like Prometheus and OpenTelemetry have established common standards for observability and operations across distributed systems, yet configuration handling in Swift services has remained largely informal. Swift is increasingly used to build production-grade services on Linux, leveraging its modern concurrency model, memory and data-safety guarantees, and high performance. Yet in practice, developers often build…

Every connected device a business operates is a workload someone must keep healthy, secure, and up to date. With 21.1 billion connected IoT devices online by the end of 2025 and a trajectory toward 39 billion by 2030, the spreadsheet-and-script method that sufficed for a handful of laptops is no longer practical. Gartner now projects that over half of organizations will embrace autonomous endpoint management by 2029. This shift is not merely a tooling upgrade. It represents a fundamental change in how IT teams manage the entire estate, from corporate laptops to industrial sensors.Key TakeawaysAutonomous endpoint management leverages AI and…

# Introduction You shouldn’t jump on Python for data science simply because it’s the trendy choice. Python’s stronghold in the data world didn’t happen by chance. At its core, the language offers highly expressive, human-readable syntax that removes the burden of manual memory management. But this convenience has a trade-off standard Python execution is dynamically typed and interpreted, making basic loops and iterations painfully slow. To build high-performance data solutions, you need to move away from ordinary procedural code and embrace vectorized, memory-conscious techniques. Let’s explore five essential Python concepts that will help you evolve from messy, sloppy code to…

Since 2017, the Transformer’s attention mechanism has remained largely unchanged. Most attempts to improve efficiency have aimed to completely swap out softmax attention. A new study takes an alternative approach: it preserves softmax attention and attaches an auxiliary correction module. Researchers from Northwestern University, Tilde Research, and the University of Washington present a parameterized Local Linear Attention architecture named ‘Parallax.’ It is designed to scale to large language model pretrained and co-designed with the Muon optimizer. Parallax does not pursue efficiency by reducing computation. Instead, it intentionally adds extra computation, then optimizes that computation to run more cheaply on contemporary…

Between May 28 and June 28, 2026, users who carry out specified contract trading activities can gain access to exclusive hospitality experiences for selected group-stage, semi-final, and final matches, while also competing for a share of the $300,000 total prize pool. Rewards span USDT bonuses, travel allowances, trial funds, BTC position-opening vouchers, and additional perks . With the global excitement for 2026’s football events still building, worldwide digital asset trading platform ZOOMEX has rolled out its “Win a Trip to the World Cup!” campaign. Built around a $300,000 prize pool and high-end World Cup hospitality packages, the campaign welcomes users…

Watch the complete conversation here. In June, it will be seven years since the Office of Management and Budget released the initial federal data strategy. Just this past March, it marked two years since the launch of the first government-wide policy on artificial intelligence. Both milestones signaled a change in how federal agencies utilized data to enhance their core missions. Establishing a modern data strategy was a foundational step for agencies before they could explore and deploy AI solutions. Organizations needed to establish frameworks for data governance and data management before venturing into AI experimentation. Dealing with massive amounts of…

pros and cons Pros Exceptional performanceEasy to upgradeStrong speakers Follow ZDNET: Add us as a preferred source on Google.Whenever I start testing a new gaming laptop, I tend to get completely absorbed in the experience. Gaming is a huge passion of mine, and there have been plenty of occasions where I’ve booted up one of these devices after hours just for the sheer enjoyment of playing my favorite games on them. My budget desktop simply can’t keep up. That’s exactly what happened over the last few weeks as I put the MSI Raider 16 Max HX through its paces —…

Artie Beaty/ZDNETFollow ZDNET: Add us as a preferred source on Google.ZDNET’s key takeawaysAndroid Auto can cause your phone to overheat due to its intensive data usage.There are several tricks you can use to keep your phone cool.Closing apps, running your car’s AC, and using a new cable can all help.Android Auto can be an incredibly useful tool, but it’s pretty taxing on your phone. When your device is navigating, streaming music, charging, sending data, and more at the same time, it’s no surprise it might start to run hot — especially if you live in a warm climate. I’ve seen high…

In my piece on Taming Entity and Relationship Sprawl in Knowledge Graphs, I covered how the Proxy-Pointer design helps pinpoint the right entities and relationships quickly. Still, that tackles just the second half of a major hurdle in loading data into a graph. The trickier—and costlier—task is actually spotting those entities (NER) and relationships to begin with. Knowledge Graphs are designed to handle layered queries and aggregation across entities and relationships found in similar documents—contracts, compliance guides, credit terms, global policies, and more. These files often stretch beyond 100 pages, with text that easily surpasses 500,000 characters. Companies routinely upload…

The Office of Personnel Management is still dealing with a spike in retirement applications, a result of the large number of federal workers who took the Voluntary Early Retirement Authority (VERA) offer and the deferred resignation program (DRP). In February 2026, OPM issued a justification for a new contract aimed at modernizing its HR systems. In that statement, OPM warned of an “expected doubling of the retirement application backlog.” As of May 2026, OPM’s average processing time for federal retirement cases sits at 76 days (50 days for applications filed digitally and 100 days for those submitted on paper). Regardless…