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Why Windows 95 left a handy power saving feature on the cutting-room floor

2 months ago
Microsoft feared too many machines would end up bricked

Microsoft vet Raymond Chen first told the story of HLT and Windows 95 more than 20 years ago. The instruction tells the CPU to effectively shut itself down until the next hardware interrupt – ideal for laptops, since power consumption would be hugely reduced.…

Richard Speed

US Created 911,000 Fewer Jobs Than Previously Thought in the 12 Months Through March

2 months ago
U.S. jobs growth was much slower than previously reported, according to revised data released on Tuesday. From a report: The number of jobs created in the United States from April 2024 to March 2025 was revised down by 911,000 by the Bureau of Labor Statistics. That would roughly amount to 76,000 fewer jobs created each month of the year up until March. The revision draws fresh attention to the weakening U.S. labor market, which added an average of only 29,000 jobs in each of the three most recent months. The August jobs report showed that the U.S. added only 22,000 jobs that month and also revised June's job growth down to a loss of 13,000 jobs. Those datapoints have led economists and some policymakers to conclude that the U.S. labor market is now at a standstill. "The jobs engine that has been integral to U.S. economic growth defying expectations for the past four years is stalling," Sarah House, a senior economist at Wells Fargo, said in a note on Friday.

Read more of this story at Slashdot.

msmash

Windows 11 Powers Up WSL: How GPU Acceleration & Kernel Upgrades Change the Game

2 months ago
by George Whittaker Introduction

Windows Subsystem for Linux (WSL) has gradually become one of Microsoft’s key bridges for developers, data scientists, and power users who need Linux compatibility without leaving the Windows environment. Over recent versions, WSL2 brought major improvements: a real Linux kernel running in a lightweight virtualized environment, much better filesystem behavior, nearly full system-call compatibility, etc. However, until recently, certain high-performance workloads, GPU computing, video encoding/decoding, and very up-to-date kernel features, were either limited, inefficient, or unavailable.

In Windows 11, Microsoft has taken bold strides to remove many of these bottlenecks. Two of the most significant enhancements are:

  1. The ability for WSL to tap into the GPU for acceleration (compute, video hardware offload, etc.), reducing reliance on CPU where the GPU is much more suited.

  2. More seamless Linux kernel upgrades, allowing users to run newer kernel versions inside WSL2, bringing performance, driver, and feature improvements faster.

This article walks through each thing in detail: what has changed, why it matters, how to use it, what limitations still exist, and how these developments shift what’s possible with WSL on Windows 11.

What WSL Was, and Where It Needed Improvement

Before diving into recent changes, it helps to understand what WSL (especially WSL2) already provided, and where it lagged.

  • WSL1: Early versions translated Linux system calls to Windows equivalents. Good for basic command-line tools, scripts, but limited in compatibility with certain networking, kernel module, filesystem, and performance-sensitive tasks.

  • WSL2: Introduced a real Linux kernel inside a lightweight VM (Hyper-V or a similar backend), better system-call compatibility, better performance especially for Linux tools, and much improved behavior for things like Docker, compiling, etc. Still, heavy workloads (e.g. ML training, video encoding, hardware-accelerated graphics) were constrained by CPU support, lack of passthrough of GPU features, older kernels, etc.

So developers were pushing Microsoft to allow more direct access to GPU functionality (CUDA, DirectML, video decoding), and to speed up how kernel updates reach users.

GPU Acceleration in WSL on Windows 11: What It Means

GPU acceleration here refers to WSL’s ability to offload certain computation or video tasks from the CPU to the GPU, enabling faster, more efficient execution. This includes:

  • Compute workloads - frameworks like CUDA (for NVIDIA), DirectML, etc., so that things like deep learning, scientific computing, data-parallel tasks run much faster. Microsoft now supports running NVIDIA CUDA inside WSL to accelerate ML libraries like PyTorch, TensorFlow.

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George Whittaker