<div id="readability-page-1"><div><div>First, let me clarify that I'm not trying to incite conflict between Windows and Mac. This article will only present facts and logic. Data is data, and trends are trends. Let's start with a fact—Microsoft is OpenAI's largest shareholder, having invested over $13 billion, and CEO Satya Nadella talks about AI to everyone he meets. However, if you ask a developer today who actually uses AI tools to write code and improve productivity, they most likely aren't using Windows. Where do programming tools like Claude Code and Codex CLI run? In the Terminal. That's right, before last winter, I didn't even know a terminal existed on a Mac. But today I can skillfully use Claude Code in the terminal to write a mapping software for a piece of hardware. I've used Windows longer than Mac (I used a Surface for a long time), and I don't have any prejudice against Microsoft products. But I spent a long time trying to get all of these operations done on Windows without success. Yes, the fact is—for AI coding, macOS and Linux are first-class citizens, while Windows is a second-class citizen that requires extra effort. Let's explain the logic in detail below— First, let's look at a logic: why development tools in the AI ​​era naturally favor Unix-based systems. These tools work by starting an agent in your terminal. This agent reads your entire code repository, then plans modifications to multiple files, writes code, and runs tests. Throughout the process, it needs to execute shell commands, manipulate git, invoke Docker, and install dependencies. This entire workflow is native to macOS and Linux, both of which are Unix-based. However, on Windows... The path separator is a backslash, the reverse of the forward slashes used in all URLs and Unix paths worldwide, resulting in syntax significantly different from Bash. Many open-source tools' READMEs default to Bash commands, implicitly assuming you're in a Unix environment. `npm install` on the Windows native file system is extremely slow. This isn't my opinion; Microsoft itself, in its March 2026 WSL improvement announcement, used this pain point as the starting point to justify the need for WSL improvements. So the question is—what is Microsoft's solution? WSL—Windows Subsystem for Linux. It's essentially running a Linux virtual kernel inside Windows. You bought a Windows computer, and to use AI development tools, you need to install Linux on Windows. Can it run? Yes. Is it outrageous? Outrageous. Two. Some might say WSL is already very mature. The WSL of 2026 is vastly different from what it was back then; startup takes less than two seconds, resources are dynamically allocated, and file systems are interoperable. Technically, this statement is correct. But the devil is in the details. Let's consider a specific scenario: cross-file system operations. In a development team of four or five people, some are editing on the Windows side using VS Code, some are running an agent in WSL, and some are doing code review on native Windows using GitHub Desktop. Synchronizing the state between these two file systems becomes a persistent nightmare. BaristaLabs' March 2026 test report pointed out that teams running AI programming agents in WSL environments spend 15% to 20% of their agent-assisted development time debugging bugs caused by environment differences. Microsoft's boomerang from years ago is now hitting them where it hurts. OpenAI's official Codex CLI installation guide clearly states that this tool is built for Unix-first environments. Until March 4, 2026, OpenAI finally released a native Windows version of Codex, running with PowerShell and a native Windows sandbox. BaristaLabs published a blog post titled: &#34;The WSL Tax Is Gone.&#34; The word &#34;tax&#34; says it all. Previously, AI development on Windows required paying taxes. On macOS and Linux, this tax has never existed. Let's look at the Unix genes of the open-source AI ecosystem. The most important open-source infrastructure projects in the AI ​​field in 2026—PyTorch, Hugging Face Transformers, llama.cpp, vLLM, Ollama, MLX, DeepSpeed, Ray. Almost without exception, these technologies were born in the Unix environment and are maintained by the Unix/Linux developer community. Opening the installation documentation for these projects, the example commands are uniformly in Bash syntax. Windows users who want to run these technologies must either install WSL or Anaconda in an attempt to bridge the gap. The entire technology stack for AI development, from model training frameworks to inference engines to deployment tools, has grown from Unix soil. macOS, due to its Unix lineage, is naturally part of this ecosystem. Windows, on the other hand, is an outsider and requires a translation layer (WSL) to integrate. Moreover, this 格局 (structure/structure) is unlikely to change in the foreseeable future. IV. Having discussed software, let's move on to hardware. In the AI ​​era, Apple's Apple Silicon chips offer a near-monopoly on local inference capabilities. The core principle here is unified memory. Traditional PC architecture separates the CPU from the GPU, with the CPU having its own system memory and the GPU its own video memory. These two memory pools are physically isolated and do not communicate with each other. When you want to run an AI model locally, the model's weights must be fully loaded into the GPU's video memory to achieve GPU-accelerated inference. Apple's M-series chips, under the Unified Memory Architecture (UMA), share the same physical memory pool for the CPU and GPU. With 64GB of RAM, the GPU can fully utilize all 64GB. A MacBook Pro M4 Max with 64GB of RAM can natively load and run a 70B parameter model (approximately 42GB). On a Windows PC, you would need a professional graphics card costing over $6000 to achieve this, and such a configuration is difficult to find in the consumer market. A March 2026 review from Compute Market provides some very telling data: A Mac Mini M4 Pro costs $1399. To build a desktop PC with equivalent AI inference capabilities using an RTX 4090, you would need a GPU, CPU, motherboard, RAM, power supply, case, cooler, and storage, totaling between $2800 and $3500. This difference is very real.<h2>V</h2>Some people say I'm not a developer, I'm just an ordinary AI user, so the difference between these two platforms isn't that big, right?Wrong!Let's look at some facts—On May 13, 2024, OpenAI released the ChatGPT desktop client—only available for macOS. Windows version? It won't be available until the end of the year. Claude's desktop application, Computer Use, launched on March 24, 2026, first for macOS, with the Windows version arriving on April 3, 10 days later. Google's Gemini native desktop application launched on April 15th this year—first on macOS. Windows version? As of May, not yet available. Perplexity's killer product this year, the Personal Computer, is a macOS exclusive. A Windows version? No timeline. Ollam's desktop application, launching in mid-2025, will also be macOS-first. Not to mention, a terminal-first programming agent is naturally Unix-centric. This list could be expanded further, but the meaning is already quite clear. This Mac-first approach isn't essentially about Apple winning market share over Windows (which will be discussed later), but rather about Apple winning the cold start environment for AI products. Windows remains the mainstream in the office world, but many of the first seed users of AI agents are on Macs: programmers, creators, independent developers, heavy AI users, and Silicon Valley startups. This group may not be the largest, but they are the most enthusiastic about tinkering, the most capable of hyping up products, and the most likely to get a new agent featured on Product Hunt, X, and Hacker News. In other words, the value of the Mac in the AI ​​agent era is not its number of installations, but rather its efficiency in dissemination. Let's discuss another obvious reason behind this: Who created the most important tools of the AI ​​era, such as Claude Code, ChatGPT, Cursor, Codex CLI, Ollama, and various libraries from Hugging Face? The vast majority were teams from the San Francisco Bay Area and Silicon Valley. And the developer community in San Francisco and Silicon Valley has the highest Mac penetration rate in the world, bar none. The creators of these AI tools use Macs every day. This means their primary development and testing environment is macOS. The command-line tools they wrote for their Macs naturally run best on macOS. Windows support? That's for next quarter's OKRs. This is actually a simple logic in product development—you should first ensure the product works well on the platform you're developing for. Some people say that macOS itself has very little AI support, while Windows has made significant efforts in system-level AI functionality. This statement is largely correct. However, if you carefully use the AI ​​features in Windows, you'll find that it actually has many flaws. Microsoft has crammed the Copilot button into every corner of Windows 11—Notepad, Paint, Photos, Screenshot tool, File Explorer, Settings—nothing is spared. The colorful Copilot logo in the upper right corner of Notepad has become a laughing stock in the Windows community. Clearly, this approach will cause user backlash. On March 20, 2026, TechCrunch reported that Microsoft began to roll back the feature expansion of Copilot. The &#34;Ask Copilot&#34; button in the Screenshot tool and Photos app has been removed. The AI ​​feature in Notepad has been renamed the more understated Writing Tools. Windows Central sources say that Microsoft has paused plans to add the Copilot button to more system apps. Microsoft has even removed Copilot from Xbox. Microsoft chose one path: to make AI a facade on the system interface. Apple chose another path: to make AI the substance on the underlying hardware and framework. Which one do you choose? Eight. Let's discuss a structural contradiction that most industry observers might overlook. Microsoft plays two roles simultaneously: the world's largest cloud computing AI infrastructure provider (Azure + OpenAI) and the world's largest desktop operating system manufacturer (Windows). At first glance, these two seem synergistic, but upon closer inspection, a hidden conflict of interest emerges. Azure's business logic is: the more things you can't do locally, the more you rely on my cloud. Need to train large models? Go to Azure. Need to deploy AI applications? Go to Azure. Microsoft's capital expenditure on AI-related infrastructure in fiscal year 2026 is approaching $80 billion. This bet is on the continued concentration of computing power in the cloud. So here's the question—if Microsoft really makes Windows an excellent native AI platform, wouldn't it be stabbing its own cloud business in the knee? Microsoft cannot achieve self-consistency. Having discussed so many structural disadvantages, a natural question arises: are these disadvantages actually reflected in market share? Let's look at the overall market first. According to StatCounter data from April 2026, the global desktop operating system market share is as follows: Windows 63.6%, macOS plus older versions of OS X combined approximately 12.6%, Linux 3%, and ChromeOS 1.5%. Windows remains the undisputed leader. But trends are far more important than existing data. IDC's shipment data shows that in the third quarter of 2025, shipments of devices pre-installed with macOS increased by 14.9% year-over-year, while global PC shipments grew by only 8.1% during the same period. Going back further, in the second quarter of 2025, Mac shipments grew by 21.4%, while global PC shipments grew by 6.5%. In the first quarter, Mac sales grew by 7%, while global PC sales grew by 4.8%. For three consecutive quarters, Mac's growth rate has been two to three times that of the overall market. More importantly, there's the geographic distribution: In the US market, macOS's market share is far higher than the global average: it reached 28.5% by early 2025, almost double the global share. And the US is precisely the heart of the global AI industry, a hub for AI tool creators and early adopters. So here's the question—if these trends are already happening, is Apple actively accelerating them? Yes. And quite aggressively. On March 4, 2026, Apple released the MacBook Neo. This is Apple's most aggressive attack on the entry-level laptop market ever. The MacBook Neo starts at $599, and with domestic education subsidies and government subsidies, it comes down to 3399 yuan. Previously, the cheapest Mac laptop was the $999 MacBook Air. Apple slashed the price by 40%. In my opinion, this is Cook's final and most ruthless move as CEO, a true &#34;inventory killer.&#34; The MacBook Neo is not a cheaply made, low-spec machine: it features an A18 Pro chip, TSMC's N3E process, 20 billion transistors, and up to 16 hours of battery life. More importantly, it runs the full macOS, an AI-friendly operating system. At 3399, what more could you ask for? What the MacBook Neo is doing is bringing tens of millions of students and entry-level users, previously excluded from the Mac ecosystem by price, into Apple's inner circle. Once these people get involved, they'll definitely find that the AI ​​tool ecosystem on macOS is far superior to that on Windows. Therefore, if you want to use AI effectively, you absolutely must try an entry-level MacBook Neo! You deserve this machine! It must be stated that—I'm not saying Windows is finished, nor am I going to discuss the age-old differences in user interface and aesthetics between Windows and Mac. Yes, in enterprise IT management, the .NET ecosystem, and Azure, Windows remains dominant. Globally, Windows holds over 60% of the desktop operating system market share, a position that no one can shake in the short term. But the definition of productivity has changed. Today, AI agents have become the new unit of productivity, terminals have replaced graphical interfaces as the mode of human-computer collaboration, and local inference capability has become a key indicator for hardware selection. Windows is not the optimal solution in any of these three dimensions. Currently, there is no short-term inflection point in sight. WSL improvements remain at the promise stage with no timetable, and Copilot's consumer strategy has begun to shrink. It's self-evident which side time is on. Back in the day, Internet Explorer was the absolute king, with a market share exceeding 95% at one point; we all know what happened after that. The world of operating systems is far more complex than that of browsers; Windows won't disappear like IE. However, in the new battlefield of AI, the first-mover advantage is rapidly shifting towards Unix-based competitors. How will Microsoft retaliate? Let's wait and see.</div></div></div>

MSFO

2 倍做多 AAPL ETF - GraniteShares

蘋果每日 2 倍做多 ETF - Direxion

微軟每日 2 倍做多 ETF - Direxion

2 倍做多 MSFT ETF - GraniteShares

MSFX

在 AI 時代，Windows 被認為過時的原因在於，儘管微軟是 OpenAI 的最大股東並積極推廣 AI，但許多開發者在使用 AI 工具時並不使用 Windows，而是更傾向於在 Mac 的終端上運行編程工具，如 Claude Code 和 Codex CLI。

Why is Windows considered outdated in the AI era?