Microsoft has announced that it will cease providing support for Microsoft 365 applications on the Windows 10 operating system after October 14, 2025. This means that after this date, users who continue to utilize Windows 10 will no longer receive security updates, bug fixes, or technical support for their Microsoft 365 apps, which include popular productivity software like Word, Excel, PowerPoint, Outlook, and Teams. This effectively ends the functional lifespan of Microsoft 365 on Windows 10, although the applications may continue to operate for a period afterward, albeit with increasing security risks and potential compatibility issues.
This decision aligns with Microsoft's broader strategy of encouraging users to migrate to Windows 11, the company's latest operating system. While Microsoft will continue to support Windows 10 with security updates until October 14, 2025, the lack of support for crucial productivity applications like Microsoft 365 effectively makes Windows 10 a less desirable platform for businesses and individuals who rely on these applications for their daily workflow. This move underscores the importance of staying up-to-date with software updates and operating system upgrades to ensure ongoing compatibility and security. Users who wish to continue using Microsoft 365 with full support after the October 2025 deadline will need to upgrade their systems to Windows 11. Failing to do so could expose users to potential security vulnerabilities and limit their access to the latest features and functionalities offered by Microsoft 365. This effectively deprecates Windows 10 as a viable platform for continued use of the Microsoft 365 suite, pushing users towards the newer Windows 11 ecosystem.
The website "WTF Happened In 1971?" presents a collection of graphs depicting various socio-economic indicators in the United States, primarily spanning from the post-World War II era to the present day. The overarching implication of the website is that a significant inflection point occurred around 1971, after which several key metrics seemingly diverged from their previously established trends. This divergence often manifests as a decoupling between productivity and compensation, a stagnation or decline in real wages, and a dramatic increase in metrics related to cost of living, such as housing prices and healthcare expenses.
The website does not explicitly propose a singular causative theory for this shift. Instead, it presents a compelling visual argument for the existence of a turning point in American economic history, inviting viewers to draw their own conclusions. The graphs showcase a variety of indicators, including, but not limited to:
Productivity and real hourly wages: These graphs illustrate a strong correlation between productivity and wages prior to 1971, with both rising in tandem. Post-1971, however, productivity continues to climb while real wages stagnate, creating a widening gap. This suggests that the benefits of increased productivity were no longer being equitably distributed to workers.
Housing prices and housing affordability: The website depicts a sharp escalation in housing costs relative to income after 1971. This is visualized through metrics like the house price-to-income ratio and the number of years of median income required to purchase a median-priced house. This indicates a growing difficulty for the average American to afford housing.
Healthcare costs: Similar to housing, the cost of healthcare exhibits a dramatic increase after 1971, becoming a progressively larger burden on household budgets.
Debt levels (both household and national): The website presents graphs showcasing a substantial rise in debt levels, particularly after 1971. This includes metrics like household debt as a percentage of disposable income and the national debt as a percentage of GDP, suggesting a growing reliance on borrowing to maintain living standards.
College costs and college tuition as a percentage of median income: The cost of higher education undergoes a significant increase post-1971, making college less accessible for many.
Income inequality: The website visually represents the growing disparity in income distribution, with the share of wealth held by the top 1% increasing significantly after 1971, further exacerbating the economic challenges faced by the majority of the population.
In essence, "WTF Happened In 1971?" visually argues that a fundamental change occurred in the American economy around that year, marked by decoupling of productivity and wages, exploding costs of essential goods and services like housing and healthcare, and a widening gap between the wealthy and the rest of the population. The website refrains from explicitly attributing this shift to any specific cause, leaving the interpretation and analysis to the observer.
The Hacker News post titled "WTF Happened in 1971?" generated a significant amount of discussion, with many commenters offering various perspectives on the claims made in the linked article. While some expressed skepticism about the presented correlations, others offered supporting arguments, additional historical context, and alternative interpretations.
A recurring theme in the comments was the acknowledgment that 1971 was a pivotal year with numerous significant global events. The end of the Bretton Woods system, where currencies were pegged to gold, was frequently cited as a key factor contributing to the economic shifts highlighted in the article. Commenters debated the long-term consequences of this change, with some arguing it led to increased financial instability and inequality.
Several commenters pointed out potential flaws in the article's methodology, suggesting that simply correlating various metrics with the year 1971 doesn't necessarily imply causation. They argued that other factors, such as the oil crisis of the 1970s, increasing globalization, and technological advancements, could have contributed to the observed trends. Some suggested that focusing solely on 1971 oversimplifies a complex historical period and that a more nuanced analysis is required.
Some commenters offered alternative explanations for the trends shown in the article. One commenter proposed that the post-World War II economic boom, driven by reconstruction and pent-up demand, was naturally slowing down by the early 1970s. Another suggested that the rise of neoliberal economic policies, beginning in the 1970s and 80s, played a significant role in the growing income inequality.
Other commenters focused on the social and cultural changes occurring around 1971. They mentioned the rise of counterculture movements, the changing role of women in society, and the increasing awareness of environmental issues as potential factors influencing the trends discussed. Some argued that these societal shifts were intertwined with the economic changes, creating a complex and multifaceted picture of the era.
A few commenters delved deeper into specific data points presented in the article, challenging their accuracy or offering alternative interpretations. For example, the discussion around productivity and wages prompted debate about how these metrics are measured and whether they accurately reflect the lived experiences of workers.
While the article itself presents a particular narrative, the comments on Hacker News offer a broader range of perspectives and interpretations. They highlight the complexities of historical analysis and the importance of considering multiple factors when examining societal shifts. The discussion serves as a valuable reminder that correlation does not equal causation and encourages a critical approach to understanding historical trends.
In a blog post titled "I deleted all of my email filters," author Cory Doctorow articulates his evolving perspective on email management and the unintended consequences of elaborate filtering systems. He begins by describing his previous reliance on an intricate network of filters, meticulously crafted over years, designed to automatically sort incoming emails into various folders based on sender, subject, content, and other criteria. This system, initially conceived as a means of achieving "Inbox Zero" and maintaining control over the deluge of electronic communication, ultimately transformed into a source of anxiety and a barrier to serendipitous discovery.
Doctorow explains how the increasing complexity of his filters led to a sense of unease regarding potentially missed messages languishing unseen in obscure folders. The cognitive overhead required to maintain and update the filters, combined with the nagging suspicion that important communications might be inadvertently filtered out, became a burden. This burden, he argues, outweighed the perceived benefits of a perfectly organized inbox.
The author then details his decision to undertake a radical simplification of his email management strategy: the complete deletion of all his email filters. This act, he describes, was driven by a desire to reclaim a more direct and unmediated relationship with his inbox. He acknowledges the potential for a temporary increase in inbox clutter but expresses hope that this initial chaos will pave the way for a more sustainable and less stressful approach to email.
Doctorow hypothesizes that confronting the full stream of incoming mail, without the intervention of filters, will force him to more actively engage with his inbox and develop healthier habits, such as promptly unsubscribing from unwanted mailing lists and more effectively prioritizing genuine communications. He further anticipates that this direct engagement will foster a greater awareness of the volume and nature of incoming mail, leading to more conscious decisions about which communications warrant his attention. He concludes by expressing optimism about this new, filter-free approach and invites readers to consider their own email management practices and the potential benefits of simplification.
The Hacker News post "I deleted all of my email filters" generated a robust discussion with 58 comments. Many commenters shared their own email management strategies and philosophies, often echoing or challenging the author's approach.
Several compelling comments emerged. One commenter advocated for a "single inbox" approach combined with aggressive unsubscribing and using a separate email address for less important communications. This commenter emphasized that dealing with email as it arrives, rather than filtering it, ultimately saves time and mental overhead. They described reaching a state of "inbox zero" daily using this method.
Another compelling comment thread discussed the benefits of using multiple email addresses for different purposes. One commenter explained their system of using one address for personal communication, another for work, and a third specifically for newsletters and mailing lists. This segregation allows them to focus on important emails without distraction and easily ignore lower-priority messages when necessary.
Some commenters challenged the author's assertion that email filters create a false sense of control. They argued that properly configured filters are essential for managing high volumes of email effectively, especially in professional contexts. One commenter specifically mentioned using filters to automatically label and categorize incoming emails, which allows them to prioritize and process messages more efficiently.
The discussion also touched upon the psychological impact of email overload and the constant pressure to stay connected. Some commenters expressed a sense of relief and liberation after simplifying their email management strategies, while others admitted to struggling with the sheer volume of incoming messages regardless of their filtering approach.
A few commenters offered alternative solutions to email filtering, such as using email clients with advanced search capabilities or employing third-party tools designed to manage newsletters and subscriptions. These suggestions highlighted the diversity of approaches individuals take to tame their inboxes.
Finally, some comments centered around the author's specific workflow and tools, questioning the generalizability of their experience to users with different needs and preferences. This led to a discussion about the importance of finding an email management system that works best for each individual's circumstances.
Tabby is presented as a self-hosted, privacy-focused AI coding assistant designed to empower developers with efficient and secure code generation capabilities within their own local environments. This open-source project aims to provide a robust alternative to cloud-based AI coding tools, thereby addressing concerns regarding data privacy, security, and reliance on external servers. Tabby leverages large language models (LLMs) that can be run locally, eliminating the need to transmit sensitive code or project details to third-party services.
The project boasts a suite of features specifically tailored for code generation and assistance. These features include autocompletion, which intelligently suggests code completions as the developer types, significantly speeding up the coding process. It also provides functionalities for generating entire code blocks from natural language descriptions, allowing developers to express their intent in plain English and have Tabby translate it into functional code. Refactoring capabilities are also incorporated, enabling developers to improve their code's structure and maintainability with AI-driven suggestions. Furthermore, Tabby facilitates code explanation, providing insights and clarifying complex code segments. The ability to create custom actions empowers developers to extend Tabby's functionality and tailor it to their specific workflow and project requirements.
Designed with a focus on extensibility and customization, Tabby offers support for various LLMs and code editors. This flexibility allows developers to choose the model that best suits their needs and integrate Tabby seamlessly into their preferred coding environment. The project emphasizes a user-friendly interface and strives to provide a smooth and intuitive experience for developers of all skill levels. By enabling self-hosting, Tabby empowers developers to maintain complete control over their data and coding environment, ensuring privacy and security while benefiting from the advancements in AI-powered coding assistance. This approach caters to individuals, teams, and organizations who prioritize data security and prefer to keep their codebase within their own infrastructure. The open-source nature of the project encourages community contributions and fosters ongoing development and improvement of the Tabby platform.
The Hacker News post titled "Tabby: Self-hosted AI coding assistant" linking to the GitHub repository for TabbyML/tabby generated a moderate number of comments, mainly focusing on the self-hosting aspect, its potential advantages and drawbacks, and comparisons to other similar tools.
Several commenters expressed enthusiasm for the self-hosted nature of Tabby, highlighting the privacy and security benefits it offers by allowing users to keep their code and data within their own infrastructure, avoiding reliance on third-party services. This was particularly appealing to those working with sensitive or proprietary codebases. The ability to customize and control the model was also mentioned as a significant advantage.
Some comments focused on the practicalities of self-hosting, questioning the resource requirements for running such a model locally. Concerns were raised about the cost and complexity of maintaining the necessary hardware, especially for individuals or smaller teams. Discussions around GPU requirements and potential performance bottlenecks were also present.
Comparisons to existing AI coding assistants, such as GitHub Copilot and other cloud-based solutions, were inevitable. Several commenters debated the trade-offs between the convenience of cloud-based solutions versus the control and privacy offered by self-hosting. Some suggested that a hybrid approach might be ideal, using self-hosting for sensitive projects and cloud-based solutions for less critical tasks.
The discussion also touched upon the potential use cases for Tabby, ranging from individual developers to larger organizations. Some users envisioned integrating Tabby into their existing development workflows, while others expressed interest in exploring its capabilities for specific programming languages or tasks.
A few commenters provided feedback and suggestions for the Tabby project, including requests for specific features, integrations, and improvements to the user interface. There was also some discussion about the open-source nature of the project and the potential for community contributions.
While there wasn't a single, overwhelmingly compelling comment that dominated the discussion, the collective sentiment reflected a strong interest in self-hosted AI coding assistants and the potential of Tabby to address the privacy and security concerns associated with cloud-based solutions. The practicality and feasibility of self-hosting, however, remained a key point of discussion and consideration.
Simon Ask has introduced Werk, a novel build tool and command runner meticulously designed for simplicity and speed. Werk aims to address the perceived complexities and performance overhead of existing tools like Make, Just, Ninja, and similar task runners, particularly within the context of Rust development where compilation times can be substantial.
The core principle behind Werk is a straightforward approach to defining and executing build processes. Instead of relying on complex declarative syntax or domain-specific languages, Werk employs a simple, imperative scripting style using standard shell commands, directly within a werk.py file. This Python script defines functions, each representing a build target, which execute shell commands when invoked. This design choice promotes transparency and ease of understanding, making it readily apparent how the build process unfolds.
Werk's commitment to speed is realized through several key optimizations. First, it leverages efficient hashing algorithms to meticulously track file dependencies and avoid unnecessary rebuilds. This ensures that only modified files and their dependents are recompiled, significantly reducing build times. Second, Werk supports parallel execution of build targets, effectively utilizing multi-core processors to further accelerate the build process. Finally, it's implemented in Rust, a language renowned for its performance characteristics, contributing to its overall speed and efficiency.
Werk boasts several notable features designed to enhance the developer experience. It provides robust support for defining and managing dependencies, ensuring that build targets are executed in the correct order. It offers clear and concise error reporting, facilitating swift debugging of build issues. Additionally, Werk includes built-in caching mechanisms, enabling it to efficiently reuse previously compiled artifacts, further minimizing build times.
While currently geared towards Rust projects, the author emphasizes Werk's potential applicability to other programming languages and build scenarios. Its minimalist design, coupled with its focus on speed and simplicity, positions Werk as a promising alternative to existing build tools, particularly for projects seeking a streamlined and efficient build process. The author also acknowledges that Werk is still in its early stages of development and encourages feedback from the community.
The Hacker News post for "Show HN: Werk, a simple build tool and command runner" has generated a moderate amount of discussion, with a number of commenters sharing their thoughts and experiences. Several key themes and compelling comments emerge from the discussion:
Simplicity and Speed: Several users praised Werk's simplicity and speed, particularly when compared to more complex build tools. One commenter specifically mentioned appreciating its speed and ease of use for simple projects where the overhead of other tools isn't warranted. Another highlighted the appeal of a faster, less complex alternative to tools like Bazel, suggesting that Werk occupies a useful niche for smaller, less demanding projects.
Niche and Use Cases: Commenters discussed the specific contexts where Werk shines. The author themselves chimed in to explain they built it for personal use and simple, self-contained projects where a full-blown build system is overkill. This reinforces the idea that Werk isn't trying to be a universal solution, but rather a targeted tool for a specific type of workflow.
Comparison to Other Tools: Unsurprisingly, comparisons to other build tools and task runners are frequent. Make, Just, Task, and npm scripts are all mentioned. Some users expressed skepticism about Werk's value proposition over these existing tools, particularly for larger or more complex projects. One commenter questioned the long-term maintainability and feature creep potential, suggesting that starting simple is easy, but maintaining that simplicity over time as needs evolve can be challenging.
Language Choice (Zig): The use of Zig as the implementation language for Werk garnered some attention. While some expressed interest in Zig, others questioned the choice, citing concerns about the relatively small community and potential for future maintenance challenges. This sparked a small side discussion about the benefits and drawbacks of using newer, less established languages for tooling.
Features and Functionality: Specific features of Werk, such as support for file watching and parallel execution, were also discussed. One commenter suggested a potential integration with a caching mechanism to further improve build speeds.
Documentation and Examples: A couple of commenters mentioned the need for clearer documentation and more comprehensive examples to better showcase Werk's capabilities and facilitate adoption. One user specifically requested an example demonstrating how to handle dependencies.
In summary, the comments generally reflect a cautious but curious reception to Werk. While the simplicity and speed are acknowledged as strengths, there are questions about its long-term viability, its niche compared to established alternatives, and the implications of its implementation in Zig. The discussion highlights the trade-offs inherent in choosing a simpler, more specialized tool versus a more complex, feature-rich one.
Summary of Comments ( 55 )
https://news.ycombinator.com/item?id=42712807
HN commenters largely discuss the implications of Microsoft ending support for Office apps on Windows 10. Several express frustration with Microsoft's push to upgrade to Windows 11, viewing it as a forced upgrade and an attempt to increase Microsoft 365 subscriptions. Some highlight the inconvenience this poses for users with older hardware incompatible with Windows 11. Others note the potential security risks of using unsupported software and the eventual necessity of upgrading. A few commenters point out the continuing support for Office 2019, although with limited functionality updates, and discuss the alternative of using web-based Office apps or open-source office suites like LibreOffice. Some speculate this is a move to bolster Microsoft 365 subscriptions, making offline productivity increasingly dependent on the service.
The Hacker News post titled "Microsoft won't support Office apps on Windows 10 after October 14th" has generated a number of comments discussing the implications of Microsoft's decision. Several commenters express frustration and cynicism regarding Microsoft's perceived strategy of pushing users towards newer operating systems and subscription services.
One highly upvoted comment points out the confusion this creates for users, especially given that Windows 10 is still supported until 2025. They highlight the discrepancy between supporting the OS but not the core productivity suite on that OS, questioning the logic behind this move. The commenter suggests this is a tactic to force upgrades to Windows 11, even if users are content with their current setup.
Another commenter echoes this sentiment, expressing annoyance at the constant pressure to upgrade, particularly when they are satisfied with the performance and stability of their existing software. They feel this is a blatant attempt by Microsoft to increase revenue through forced upgrades and subscriptions.
The theme of planned obsolescence is also raised, with one user arguing that this is a classic example of a company artificially limiting the lifespan of perfectly functional software to drive sales. They express disappointment in this practice and the lack of consideration for users who prefer stability over constant updates.
Some commenters discuss the technical implications, questioning the specific reasons why Office apps wouldn't function on a supported OS. They speculate about potential security concerns or underlying changes in the software architecture that necessitate the change. However, there's a general skepticism towards these explanations, with many believing it's primarily a business decision rather than a technical necessity.
A few users offer practical advice, suggesting alternatives like LibreOffice or using older, perpetual license versions of Microsoft Office. They also discuss the possibility of using virtual machines to run Windows 11 if necessary.
Several comments mention the security implications, with some suggesting that this move might actually improve security by forcing users onto a more modern and regularly updated platform. However, this is countered by others who argue that forced upgrades can disrupt workflows and create vulnerabilities if not handled properly.
Overall, the comments reflect a general sentiment of frustration and skepticism towards Microsoft's decision. Many users perceive it as a manipulative tactic to drive revenue and force upgrades, rather than a move based on genuine technical necessity or user benefit. The discussion highlights the ongoing tension between software companies' desire for continuous updates and users' preference for stability and control over their systems.