Top 10 Hacker News posts, summarized
HN discussion
(696 points, 226 comments)
Unable to access content: The article's publication date (January 17, 2026) is in the future. Content for this date is not yet available.
The discussion on Hacker News reflects a mixed sentiment towards jQuery 4.0.0, with many users expressing nostalgia for its past contributions to web development and appreciation for its continued maintenance. Several comments highlight jQuery's historical significance in simplifying web interactions and enabling careers in the field.
However, there is also a noticeable sentiment that jQuery is now largely outdated and bloated compared to modern JavaScript frameworks and libraries. Concerns are raised about its file size, with comparisons made to significantly smaller alternatives like Preact. The continued support for Internet Explorer 11 is also a point of contention, with some noting it as a feature planned for deprecation in a future version. Despite these criticisms, there is acknowledgment of jQuery's improvements, such as ES6 module support, Trusted Types, and CSP.
HN discussion
(459 points, 395 comments)
The article argues that OpenAI is not facing financial ruin, as suggested by some media reports, but is instead strategically positioning itself for a massive IPO and long-term profitability, with advertising being a key component of its revenue strategy. Despite significant operational costs, OpenAI's projected revenue growth, driven by subscriptions and API usage, is substantial. The author anticipates OpenAI will leverage its users' high-intent queries—similar to search engine queries—to generate significant ad revenue, potentially surpassing current industry benchmarks.
OpenAI's advertising strategy, set to roll out in early 2026, will initially feature sponsored products at the bottom of relevant answers and later expand to sidebar content and affiliate features. The company has outlined principles of answer independence, conversation privacy, and user control over personalization. The author predicts OpenAI's advertising revenue will grow rapidly, reaching tens of billions of dollars annually by 2029, driven by a maturing self-serve platform and conversational commerce features, all supported by strategic hires like Fidji Simo.
Commenters largely agree with the article's premise that AI companies, including OpenAI, will inevitably adopt advertising models due to the immense cost of scaling AI. Many expressed skepticism about the feasibility of an "ad-free" premium experience, drawing parallels to Google Search, and speculated that ads would eventually permeate all tiers. There's a recurring sentiment that "AGI" is being reinterpreted as "Advertisement Generated Income" or "Ads Generated Income," highlighting the financial pressures driving this shift.
Several commenters voiced concerns about the ethical implications of AI-powered advertising, particularly regarding its potential to be more manipulative and pervasive than current digital ads. The idea of AI seamlessly embedding advertisements into content and influencing user behavior was a significant point of discussion. Despite these concerns, some also presented a more pragmatic view, seeing advertising as a necessary evil to sustain AI development and a logical extension of the internet's monetization models.
HN discussion
(372 points, 126 comments)
A$AP Rocky's music video for "Helicopter" prominently features dynamic Gaussian splatting technology to capture and render human performances volumetrically. This innovative approach, developed by Evercoast, Chris Rutledge, and Wilfred Driscoll, allowed for unprecedented creative freedom in post-production, enabling radical manipulation of captured movements and scenes. The decision to use volumetric capture was driven by the director's desire for flexibility, which would have been prohibitively expensive and complex with traditional methods.
The production involved capturing over 10 terabytes of data using a 56-camera RGB-D array. This data was then processed in Houdini and rendered with OctaneRender, allowing for relighting and the creation of a highly dimensional "3D video" aesthetic. While some viewers perceive the visuals as AI-generated due to their synthetic feel, the article emphasizes that every action was physically performed and captured in real space, with the technology serving to preserve and recontextualize reality rather than replace it. This marks a significant real-world deployment of dynamic Gaussian splatting in a major music release.
The Hacker News discussion expresses a mix of surprise and admiration for seeing A$AP Rocky featured on the platform, alongside appreciation for the technological innovation. Several commenters directly link to the music video and praise its energetic and surreal aesthetic, even suggesting muting the music if it's not to one's taste. There's intrigue regarding the efficiency of the workflow, with one user noting that despite high data requirements, the compositing flexibility and rapid data deletion/storage make it a faster and more adaptable process than traditional methods.
A significant portion of the conversation revolves around understanding Gaussian splatting itself. Users inquire about its rendering quality, its potential to replace conventional filming, and what specific advancements have made its current "maturity" possible. Questions arise about the scope of what was scanned (actors vs. entire scenes) and whether the technology genuinely reduced costs compared to alternatives like drone cinematography. The use of specific software like Houdini and OctaneRender is noted, with a developer of GSOPs for Houdini even offering further insight and resources. Some commenters find the technical jargon inaccessible, while others compare it to earlier DIY music production methods, acknowledging the significant team effort involved in this project.
HN discussion
(282 points, 199 comments)
This article demonstrates how standard command-line tools can significantly outperform Hadoop for certain data processing tasks. The author analyzes chess game data, initially showing that a local laptop using shell commands processed 3.46GB of data in about 12 seconds, while a 7-node Amazon EMR cluster took 26 minutes for a smaller dataset. The article details the construction of a shell pipeline using `cat`, `grep`, `sort`, `uniq`, and `awk` to extract and count game results, progressively optimizing it by parallelizing the `grep` process with `xargs` and eventually consolidating filtering into `awk` for maximum efficiency.
The core argument is that for datasets that fit on a single machine, leveraging shell commands and their inherent parallelism via pipes can be substantially faster and more memory-efficient than distributed frameworks like Hadoop. The final optimized pipeline, using `find`, `xargs`, and `mawk`, achieved a processing speed of approximately 270MB/sec, about 235 times faster than the Hadoop implementation. The article concludes by advocating for the judicious use of simpler tools for tasks where they are more appropriate, rather than defaulting to "Big Data" solutions.
The Hacker News discussion largely echoes the article's sentiment, with many commenters agreeing that Hadoop and similar distributed systems are often overused for datasets that could be handled efficiently on a single machine. Several users recall similar observations from years past, noting that this theme of simpler tools outperforming complex ones for smaller data volumes is a recurring discussion. The rise of modern tools like DuckDB and ClickHouse is mentioned as further evidence that powerful, single-machine data processing is increasingly viable.
Commenters also reflect on the industry's trend towards adopting complex "modern data stacks" and layers of abstraction, sometimes at the expense of efficiency and cost. There's a sentiment that incentives often favor implementing trendy solutions over optimizing for performance and cost with simpler, more robust tools. Some participants also point out the potential drawbacks of parallelizing with `xargs` directly to the terminal and suggest alternative tools for managing parallel execution more effectively. The question is raised about how large data truly needs to be for distributed systems to become necessary, with suggestions to consider tools like Lichess's massive chess database for further benchmarking.
HN discussion
(228 points, 106 comments)
The article "A Social Filesystem" by Dan Abramov proposes a radical shift in how social media data is managed, drawing a parallel between traditional personal computing file systems and the future of social computing. It argues that user-created content, whether a document or a social media post, should be treated as a "file" that the user owns and controls, rather than being trapped within proprietary applications. The author introduces the concept of an "everything folder" where all user-generated social content is stored as structured data (records) organized into collections, forming a distributed social filesystem. This approach, exemplified by the AT protocol and platforms like Bluesky, aims to empower users by allowing their data to outlive specific applications and enabling new applications to be built on top of existing data.
The core of the proposed system relies on structured data formats ("lexicons") that define "records," which are essentially JSON files representing social interactions. These records are organized into "collections" named using a domain-like structure to avoid conflicts. The system emphasizes robust identity management using Decentralized Identifiers (DIDs) to ensure data permanence and portability, even if hosting or handles change. Ultimately, the goal is to create an "everything ecosystem" where user data is the source of truth, and applications are reactive consumers and presenters of this data, fostering innovation and user control.
The Hacker News discussion largely embraces the core idea of user-owned, portable social data, drawing parallels to file formats like SVG and personal computing paradigms. Many commenters express enthusiasm for the concept of data liberation from walled-garden social apps and see it as a positive step towards a more user-centric internet. There's a consensus that treating social contributions as files provides valuable ownership and interoperability.
However, significant concerns are raised regarding the practical implementation, scalability, and potential for a new set of centralized entities to emerge. Several users express skepticism about the AT protocol's ability to truly decentralize or prevent exploitation, likening it to existing models where companies offload server costs while maintaining control. Critiques also point to potential over-engineering, challenges with iteration speed for new features, and the difficulty of making self-hosting accessible to average users. The comparison to existing decentralized or federated systems like Mastodon and Solid is frequent, with some arguing that existing models are more mature or offer better solutions to issues like data deletion and privacy.
HN discussion
(224 points, 110 comments)
This article highlights the philosophy and impact of ThinkNext Design, emphasizing that design extends beyond mere aesthetics to embody a brand's identity and values. The firm prioritizes empathy and purpose, aiming to understand user desires to create innovative and enduring products. The text showcases several iconic design achievements, particularly within the ThinkPad line, including the introduction of distinct aesthetic elements, security enhancements like the security keystick, comfort-focused TrackPoint caps, and practical innovations such as the ThinkLight.
The article further details how ThinkNext Design has consistently pushed boundaries with products like the Netfinity 7000's rack-and-stack solution, the revolutionary IBM PC redesign integrating flat-panel technology, and the modular ThinkPad X1 Tablet. The enduring legacy of ThinkPad, with over 200 million units sold, is presented as a testament to the strategic and purposeful design initiatives led by David Hill and his team, who have successfully balanced aesthetic appeal with functional excellence and brand resonance.
The Hacker News discussion reveals a strong and often nostalgic appreciation for ThinkPads, with many users expressing loyalty to the brand due to their durability, longevity, and repairability. Several commenters shared personal anecdotes of using older ThinkPads for extended periods, often repurposing them as servers or donating them. However, a significant number of recent comments voiced disappointment with Lenovo's current product quality and customer service, citing issues like bricked devices, faulty USB ports, and overall declining reliability, leading some to question the future of the brand and consider alternatives like Framework laptops.
There was also a notable discussion around specific design elements, with some praising the timeless aesthetic of ThinkPads while others found recent branding (like the red Lenovo logo) unappealing. The functionality of accessories like the "Precision Wireless Travel Mouse" was questioned, and a humorous, albeit concerning, anecdote about a TrackPoint cap was shared. Overall, the sentiment indicates a deep respect for the design heritage of ThinkPads but growing concern about current manufacturing and quality control standards under Lenovo.
HN discussion
(143 points, 184 comments)
The article posits that as of 2026, communication has become the paramount skill for software engineers, eclipsing traditional technical proficiencies like coding and system design. This shift is attributed to the rapid advancement of AI coding agents, which can now handle the majority of programming tasks. The author argues that the effectiveness of these AI tools hinges on clear and comprehensive specifications, which are difficult to achieve without strong soft skills like questioning assumptions, facilitating discussions, and managing scope. Consequently, skills previously considered optional for individual contributors are now essential for success in the field.
The author emphasizes that while AI can assist with technical tasks, it cannot replicate human empathy and communication. Therefore, software engineers must focus on developing these "soft" skills to effectively interact with colleagues and stakeholders, a crucial aspect of problem-solving in a human-centric world.
The Hacker News discussion largely agrees with the article's premise that soft skills are becoming increasingly critical for software engineers, especially with the rise of AI. Several commenters noted the irony of universities struggling with AI-assisted cheating in writing while the industry emphasizes communication skills. A common sentiment was that skills once relegated to senior roles are now expected of junior engineers, including business impact, communication, and project management.
However, some commenters questioned the premise, suggesting it might be based on outdated stereotypes of coders being antisocial. Others argued that soft skills have always been important for career progression and that this is not a new phenomenon. A recurring theme was the idea that AI will automate many coding tasks, potentially leading to fewer but more specialized roles, or even requiring Universal Basic Income due to widespread displacement. Some also pointed out that the "soft" skill of writing clear prompts for AI could be seen as a new form of technical skill.
HN discussion
(190 points, 83 comments)
This article introduces flux2.c, a C program that enables image generation from text prompts using the FLUX.2-klein-4B model. Developed without external dependencies beyond the C standard library, it offers optional MPS and BLAS acceleration. The author, Salvatore, generated the entire codebase using AI (Claude Code) over a weekend, aiming to create accessible AI inference systems outside the Python stack. The project supports both text-to-image and image-to-image generation, directly utilizing safetensors models without quantization.
The program is designed for ease of use, requiring no Python runtime or CUDA toolkit for inference. It integrates the Qwen3-4B text encoder and offers features like optional GPU acceleration, memory efficiency through automatic encoder release, and adjustable generation parameters. The article details build instructions for various backends (generic C, BLAS, MPS) and provides examples of usage for both text-to-image and image-to-image transformations, along with an API for integration into other C/C++ projects.
The discussion highlights a mix of excitement and concern regarding the implications of a powerful, standalone image generation tool. Some users expressed enthusiasm for its potential integration into game engines, creative software, and other applications, while others voiced apprehension about its broad applicability and potential for misuse. There was significant interest in the author's meta-experiment of using AI to generate code, with questions about the process, the quality of the output, and whether such AI-assisted projects can be considered "from scratch."
Further points of discussion included licensing, the potential for this C implementation to improve performance compared to Python-based solutions, and the author's motivation for avoiding the Python ecosystem. Users also inquired about the training process, the practicality of the generic C backend's speed, and practical suggestions like embedding seeds into image metadata. Some comments touched upon the author's broader relationship with open-source communities and the perceived shift in his stance on certain projects.
HN discussion
(131 points, 121 comments)
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The discussion indicates a mixed reaction to the concept of prediction markets, with some commenters expressing concern about their potential for manipulation and their perceived alignment with gambling. Several users suggest that these markets can be easily gamed by those with financial influence, potentially distorting outcomes rather than providing accurate predictions. There is a sentiment that the proliferation of such markets signifies a broader societal shift towards gambling and a decline in belief in traditional values, exacerbated by economic conditions.
Conversely, some contributors argue that prediction markets, when properly understood, can offer valuable insights, even surpassing traditional polling methods. They question why prediction markets are considered more dangerous than other speculative financial instruments like NFTs or options trading. Some users also point out the relatively low stakes of some popular prediction markets compared to established forms of gambling. There's also a debate about whether these markets are genuinely predictive or simply a form of "corporatized bookmaking." The legality of US residents participating in platforms like Polymarket is also raised as a point of discussion.
HN discussion
(152 points, 33 comments)
The article introduces Singularity, a free and open-source rootkit for Linux developed by Matheus Alves. Designed as a research tool, Singularity aims to advance security research by demonstrating current rootkit capabilities. It allows for remote code execution, disabling of security features, and hiding of files and processes. The rootkit leverages the kernel's Ftrace mechanism to hook system calls and evade detection, preventing modifications to the CPU trap-handling vector and kernel function patching. Singularity focuses on hiding its presence, attacker-controlled processes, network communication, and associated files by manipulating kernel interfaces and system call responses.
Singularity employs several techniques to maintain stealth, including self-removal from the list of active kernel modules and blocking further module loading. It hides processes by maintaining a small, fixed-size list of PIDs and intercepting system calls related to process existence and information retrieval. File hiding is achieved by filtering directory entries and adjusting link counts. The rootkit also hides network activity and is designed for compatibility across 32-bit and 64-bit system call interfaces on x86/x86_64 architectures. Despite its sophistication, Singularity has limitations, such as not hiding from physical disk forensics and potential detection through ftrace's inability to be disabled.
Commenters expressed a mix of fascination and concern regarding the release of an open-source rootkit. Some found the MIT license choice interesting, noting that a GPL license might have imposed additional obligations on malicious users. There was curiosity about the technical implementation, with discussions around how Ftrace can be effectively disabled at compile time and the potential for performance impacts from file system operation hiding. Several users saw Singularity as a valuable tool for security researchers and for understanding advanced attack vectors, with some speculating on its potential repurposing for benevolent uses like protecting dissidents and journalists.
A recurring theme was the ethical implications of releasing such tools. Some commenters voiced apprehension about the potential for misuse by "imbeciles" and the increase in cyberattack capabilities. The discussion also touched on the rootkit's ability to bypass various EDR (Endpoint Detection and Response) solutions, highlighting the ongoing cat-and-mouse game between security software and malware. The specific method of ftrace disabling was also a point of interest, with suggestions on how to improve its stealth further.
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