Ultrascience Labs continues to use 88x31 pixel buttons despite advancements in screen resolutions and design trends. This seemingly outdated size stems from their early adoption of the dimension for physical buttons, which translated directly to their digital counterparts. Maintaining this size ensures consistency across their brand and product line, especially for long-time users familiar with the established button dimensions. While acknowledging the peculiarity, they prioritize familiarity and usability over adhering to modern design conventions, viewing the unusual size as a unique identifier and part of their brand identity.
MIT researchers have developed a new technique to make graphs more accessible to blind and low-vision individuals. This method, called "auditory graphs," converts visual graph data into non-speech sounds, leveraging variations in pitch, timbre, and stereo panning to represent different data points and trends. Unlike existing screen readers that often struggle with complex visuals, this approach allows users to perceive and interpret graphical information quickly and accurately through sound, offering a more intuitive and efficient alternative to textual descriptions or tactile graphics. The researchers demonstrated the effectiveness of auditory graphs with line charts, scatter plots, and bar graphs, and are working on extending it to more complex visualizations.
HN commenters generally praised the MIT researchers' efforts to improve graph accessibility. Several pointed out the importance of tactile graphs for blind users, noting that sonification alone isn't always sufficient. Some suggested incorporating existing tools and standards like SVG accessibility features or MathML. One commenter, identifying as low-vision, emphasized the need for high contrast and clear labeling in visual graphs, highlighting that accessibility needs vary widely within the low-vision community. Others discussed alternative methods like detailed textual descriptions and the importance of user testing with the target audience throughout the development process. A few users offered specific technical suggestions such as using spatial audio for data representation or leveraging haptic feedback technologies.
Ken Shirriff created a USB interface for a replica of the iconic "keyset" used in Douglas Engelbart's 1968 "Mother of All Demos." This keyset, originally designed for chordal input, now sends USB keystrokes corresponding to the original chord combinations. Shirriff's project involved reverse-engineering the keyset's wiring, designing a custom circuit board to read the key combinations, and programming an ATmega32U4 microcontroller to translate the chords into USB HID keyboard signals. This allows the replica keyset, originally built by Bill Degnan, to be used with modern computers, preserving a piece of computing history.
Commenters on Hacker News largely expressed fascination with the project, connecting it to a shared nostalgia for early computing and the "Mother of All Demos." Several praised the creator's dedication and the ingenuity of using a Teensy microcontroller to emulate the historical keyset. Some discussed the technical aspects, including the challenges of replicating the original chord keyboard's behavior and the choice of using a USB interface. A few commenters reminisced about their own experiences with similar historical hardware, highlighting the significance of preserving and interacting with these pieces of computing history. There was also some discussion about the possibility of using this interface with modern emulators or virtual machines.
A graphics tablet can be a surprisingly effective tool for programming, offering a more ergonomic and intuitive way to interact with code. The author details their setup using a Wacom Intuos Pro and describes the benefits they've experienced, such as reduced wrist strain and improved workflow. By mapping tablet buttons to common keyboard shortcuts and utilizing the pen for precise cursor control, scrolling, and even drawing diagrams directly within code comments, the author finds that a graphics tablet becomes an integral part of their development process, ultimately increasing productivity and comfort.
HN users discussed the practicality and potential benefits of using a graphics tablet for programming. Some found the idea intriguing, particularly for visual tasks like diagramming or sketching out UI elements, and for reducing wrist strain associated with constant keyboard and mouse use. Others expressed skepticism, questioning the efficiency gains compared to a keyboard and mouse for text-based coding, and citing the potential awkwardness of switching between tablet and keyboard frequently. A few commenters shared their personal experiences, with varying degrees of success. While some abandoned the approach, others found it useful for specific niche applications like working with graphical programming languages or mathematical notation. Several suggested that pen-based computing might be better suited for this workflow than a traditional graphics tablet. The lack of widespread adoption suggests significant usability hurdles remain.
The article "Beyond the 70%: Maximizing the human 30% of AI-assisted coding" argues that while AI coding tools can handle a significant portion of coding tasks, the remaining 30% requiring human input is crucial and demands specific skills. This 30% involves high-level design, complex problem-solving, ethical considerations, and understanding the nuances of user needs. Developers should focus on honing skills like critical thinking, creativity, and communication to effectively guide and refine AI-generated code, ensuring its quality, maintainability, and alignment with project goals. Ultimately, the future of software development relies on a synergistic partnership between humans and AI, where developers leverage AI's strengths while excelling in the uniquely human aspects of the process.
Hacker News users discussed the potential of AI coding assistants to augment human creativity and problem-solving in the remaining 30% of software development not automated. Some commenters expressed skepticism about the 70% automation figure, suggesting it's inflated and context-dependent. Others focused on the importance of prompt engineering and the need for developers to adapt their skills to effectively leverage AI tools. There was also discussion about the potential for AI to handle more complex tasks in the future and whether it could eventually surpass human capabilities in coding altogether. Some users highlighted the possibility of AI enabling entirely new programming paradigms and empowering non-programmers to create software. A few comments touched upon the potential downsides, like the risk of over-reliance on AI and the ethical implications of increasingly autonomous systems.
The Honeycomb blog post explores the optimal role of humans in AI systems, advocating for a shift from "human-in-the-loop" to "human-in-the-design" approach. While acknowledging the current focus on using humans for labeling training data and validating outputs, the post argues that this reactive approach limits AI's potential. Instead, it emphasizes the importance of human expertise in shaping the entire AI lifecycle, from defining the problem and selecting data to evaluating performance and iterating on design. This proactive involvement leverages human understanding to create more robust, reliable, and ethical AI systems that effectively address real-world needs.
HN users discuss various aspects of human involvement in AI systems. Some argue for human oversight in critical decisions, particularly in fields like medicine and law, emphasizing the need for accountability and preventing biases. Others suggest humans are best suited for defining goals and evaluating outcomes, leaving the execution to AI. The role of humans in training and refining AI models is also highlighted, with suggestions for incorporating human feedback loops to improve accuracy and address edge cases. Several comments mention the importance of understanding context and nuance, areas where humans currently outperform AI. Finally, the potential for humans to focus on creative and strategic tasks, leveraging AI for automation and efficiency, is explored.
Sesame's blog post discusses the challenges of creating natural-sounding conversational AI voices. It argues that simply improving the acoustic quality of synthetic speech isn't enough to overcome the "uncanny valley" effect, where slightly imperfect human-like qualities create a sense of unease. Instead, they propose focusing on prosody – the rhythm, intonation, and stress patterns of speech – as the key to crafting truly engaging and believable conversational voices. By mastering prosody, AI can move beyond sterile, robotic speech and deliver more expressive and nuanced interactions, making the experience feel more natural and less unsettling for users.
HN users generally agree that current conversational AI voices are unnatural and express a desire for more expressiveness and less robotic delivery. Some commenters suggest focusing on improving prosody, intonation, and incorporating "disfluencies" like pauses and breaths to enhance naturalness. Others argue against mimicking human imperfections and advocate for creating distinct, pleasant, non-human voices. Several users mention the importance of context-awareness and adapting the voice to the situation. A few commenters raise concerns about the potential misuse of highly realistic synthetic voices for malicious purposes like deepfakes. There's skepticism about whether the "uncanny valley" is a real phenomenon, with some suggesting it's just a reflection of current technological limitations.
Jon Blow reflects on the concept of a "daylight computer," a system designed for focused work during daylight hours. He argues against the always-on, notification-driven nature of modern computing, proposing a machine that prioritizes deep work and mindful engagement. This involves limiting distractions, emphasizing local data storage, and potentially even restricting network access. The goal is to reclaim a sense of control and presence, fostering a healthier relationship with technology by aligning its use with natural rhythms and promoting focused thought over constant connectivity.
Hacker News users largely praised the Daylight Computer project for its ambition and innovative approach to personal computing. Several commenters appreciated the focus on local-first software and the potential for increased privacy and control over data. Some expressed skepticism about the project's feasibility and the challenges of building a sustainable ecosystem around a niche operating system. Others debated the merits of the chosen hardware and software stack, suggesting alternatives like RISC-V and questioning the reliance on Electron. A few users shared their personal experiences with similar projects and offered practical advice on development and community building. Overall, the discussion reflected a cautious optimism about the project's potential, tempered by a realistic understanding of the difficulties involved in disrupting the established computing landscape.
"What if Eye...?" explores the potential of integrating AI with the human visual system. The MIT Media Lab's Eye group is developing wearable AI systems that enhance and augment our vision, effectively creating "eyes for the mind." These systems aim to provide real-time information and insights overlaid onto our natural field of view, potentially revolutionizing how we interact with the world. Applications range from assisting individuals with visual impairments to enhancing everyday experiences by providing contextual information about our surroundings and facilitating seamless interaction with digital interfaces.
Hacker News users discussed the potential applications and limitations of the "Eye Contact" feature presented in the MIT Media Lab's "Eyes" project. Some questioned its usefulness in real-world scenarios, like presentations, where deliberate looking away is often necessary to gather thoughts. Others highlighted ethical concerns regarding manipulation and the potential for discomfort in forced eye contact. The potential for misuse in deepfakes was also brought up. Several commenters saw value in the technology for video conferencing and improving social interactions for individuals with autism spectrum disorder. The overall sentiment expressed was a mix of intrigue, skepticism, and cautious optimism about the technology's future impact. Some also pointed out existing solutions for gaze correction, suggesting that the novelty might be overstated.
The author explores the idea of imbuing AI with simulated emotions, specifically anger, not for the sake of realism but for practical utility. They argue that a strategically angry AI could be more effective at tasks like debugging or system administration, where expressing frustration can highlight critical issues and motivate human intervention. This "anger" wouldn't be genuine emotion but a calculated performance designed to improve communication and problem-solving. The author envisions this manifested through tailored language, assertive recommendations, and even playful grumbling, ultimately making the AI a more engaging and helpful collaborator.
Hacker News users largely disagreed with the premise of an "angry" AI. Several commenters argued that anger is a human emotion rooted in biological imperatives, and applying it to AI is anthropomorphism that misrepresents how AI functions. Others pointed out the potential dangers of an AI designed to express anger, questioning its usefulness and raising concerns about manipulation and unintended consequences. Some suggested that what the author desires isn't anger, but rather an AI that effectively communicates importance and urgency. A few commenters saw potential benefits, like an AI that could advocate for the user, but these were in the minority. Overall, the sentiment leaned toward skepticism and concern about the implications of imbuing AI with human emotions.
The post "UI is hell: four-function calculators" explores the surprising complexity and inconsistency in the seemingly simple world of four-function calculator design. It highlights how different models handle order of operations (especially chained calculations), leading to varied and sometimes unexpected results for identical input sequences. The author showcases these discrepancies through numerous examples and emphasizes the challenge of creating an intuitive and predictable user experience, even for such a basic tool. Ultimately, the piece demonstrates that seemingly minor design choices can significantly impact functionality and user understanding, revealing the subtle difficulties inherent in user interface design.
HN commenters largely agreed with the author's premise that UI design is difficult, even for seemingly simple things like calculators. Several shared anecdotes of frustrating calculator experiences, particularly with cheap or poorly designed models exhibiting unexpected behavior due to button order or illogical function implementation. Some discussed the complexities of parsing expressions and the challenges of balancing simplicity with functionality. A few commenters highlighted the RPN (Reverse Polish Notation) input method as a superior alternative, albeit with a steeper learning curve. Others pointed out the differences between physical and software calculator design constraints. The most compelling comments centered around the surprising depth of complexity hidden within the design of a seemingly mundane tool and the difficulties in creating a truly intuitive user experience.
The Therac-25 simulator recreates the software and hardware interface of the infamous radiation therapy machine, allowing users to experience the sequence of events that led to fatal overdoses. It emulates the PDP-11's operation, including data entry, mode switching, and the machine's response, demonstrating how specific combinations of user input and software flaws could bypass safety checks and activate the high-power electron beam without the necessary x-ray attenuating target. By interacting with the simulator, users can gain a concrete understanding of the race conditions, inadequate software testing, and poor error handling that contributed to the tragic accidents.
HN users discuss the Therac-25 simulator and the broader implications of software in safety-critical systems. Several express how chilling and impactful the simulator is, driving home the real-world consequences of software bugs. Some commenters delve into the technical details of the race condition and flawed design choices that led to the accidents. Others lament the lack of proper software engineering practices at the time and the continuing relevance of these lessons today. The simulator itself is praised as a valuable educational tool for demonstrating the importance of rigorous software development and testing, particularly in life-or-death scenarios. A few users share their own experiences with similar systems and emphasize the need for robust error handling and fail-safes.
A new "Calm Technology" certification aims to highlight digital products and services designed to be less intrusive and demanding of users' attention. Developed by Amber Case, the creator of the concept, the certification evaluates products based on criteria like peripheral awareness, respect for user attention, and providing a sense of calm. Companies can apply for certification, hoping to attract users increasingly concerned with digital overload and the negative impacts of constant notifications and distractions. The goal is to encourage a more mindful approach to technology design, promoting products that integrate seamlessly into life rather than dominating it.
HN users discuss the difficulty of defining "calm technology," questioning the practicality and subjectivity of a proposed certification. Some argue that distraction is often a function of the user's intent and self-control, not solely the technology itself. Others express skepticism about the certification process, wondering how "calmness" can be objectively measured and enforced, particularly given the potential for manipulation by manufacturers. The possibility of a "calm technology" standard being co-opted by marketing is also raised. A few commenters appreciate the concept but worry about its implementation. The overall sentiment leans toward cautious skepticism, with many believing the focus should be on individual digital wellness practices rather than relying on a potentially flawed certification system.
"ELIZA Reanimated" revisits the classic chatbot ELIZA, not to replicate it, but to explore its enduring influence and analyze its underlying mechanisms. The paper argues that ELIZA's effectiveness stems from exploiting vulnerabilities in human communication, specifically our tendency to project meaning onto vague or even nonsensical responses. By systematically dissecting ELIZA's scripts and comparing it to modern large language models (LLMs), the authors demonstrate that ELIZA's simple pattern-matching techniques, while superficially mimicking conversation, actually expose deeper truths about how we construct meaning and perceive intelligence. Ultimately, the paper encourages reflection on the nature of communication and warns against over-attributing intelligence to systems, both past and present, based on superficial similarities to human interaction.
The Hacker News comments on "ELIZA Reanimated" largely discuss the historical significance and limitations of ELIZA as an early chatbot. Several commenters point out its simplistic pattern-matching approach and lack of true understanding, while acknowledging its surprising effectiveness in mimicking human conversation. Some highlight the ethical considerations of such programs, especially regarding the potential for deception and emotional manipulation. The technical implementation using regex is also mentioned, with some suggesting alternative or updated approaches. A few comments draw parallels to modern large language models, contrasting their complexity with ELIZA's simplicity, and discussing whether genuine understanding has truly been achieved. A notable comment thread revolves around Joseph Weizenbaum's, ELIZA's creator's, later disillusionment with AI and his warnings about its potential misuse.
Cosmos Keyboard is a project aiming to create a personalized keyboard based on a 3D scan of the user's hands. The scan data is used to generate a unique key layout and keycap profiles perfectly tailored to the user's hand shape and size. The goal is to improve typing ergonomics, comfort, and potentially speed by optimizing key positions and angles for individual hand physiology. The project is currently in the prototype phase and utilizes readily available 3D scanning and printing technology to achieve this customization.
Hacker News users discussed the Cosmos keyboard with cautious optimism. Several expressed interest in the customizability and ergonomic potential, particularly for those with injuries or unique hand shapes. Concerns were raised about the reliance on a phone's camera for scanning accuracy and the lack of key travel/tactile feedback. Some questioned the practicality of the projected keyboard for touch typing and the potential distraction of constantly looking at one's hands. The high price point was also a significant deterrent for many, with some suggesting a lower-cost, less advanced version could be more appealing. A few commenters drew comparisons to other projected keyboards and input methods, highlighting the limitations of similar past projects. Overall, the concept intrigued many, but skepticism remained regarding the execution and real-world usability.
Summary of Comments ( 49 )
https://news.ycombinator.com/item?id=43596570
Hacker News users generally agreed with the premise of the article, pointing out that the 88x31 button size became a standard due to early GUI limitations and the subsequent network effects of established tooling and libraries. Some commenters highlighted the inertia in UI design, noting that change is difficult even when the original constraints are gone. Others offered practical reasons for the standard's persistence, such as existing muscle memory and the ease of finding pre-made assets. A few users suggested the size is actually aesthetically pleasing and functional, fitting well within typical UI layouts. One compelling comment thread discussed the challenges of deviating from established norms, citing potential compatibility issues and user confusion as significant barriers to adopting alternative button sizes.
The Hacker News post "We are still using 88x31 buttons" generated a moderate amount of discussion with a focus on practicality, aesthetics, and the enduring nature of established conventions.
Several commenters highlighted the practical advantages of the 88x31 button size. One commenter emphasized the established tooling and readily available resources for this size, making it a convenient choice for developers. This ease of access, combined with its familiarity among users, contributes to its continued usage. Another echoed this sentiment, suggesting that the size has become a standard, and deviating from it requires strong justification. They argue that unless there's a compelling reason to change, sticking with the known quantity is often the most efficient approach.
The aesthetic aspect was also discussed. One user mentioned that the size, while seemingly arbitrary, "looks right" and fits well within various layouts. This suggests a certain visual harmony that has been achieved with the 88x31 dimensions. Another commenter pointed out that the size is large enough to accommodate labels and icons comfortably, contributing to a user-friendly experience. They also touched on the idea of visual consistency, implying that maintaining a uniform button size across platforms and applications provides a sense of familiarity and predictability for users.
The historical context of the 88x31 size was also brought up. A commenter speculated that the dimensions might be related to older screen resolutions or limitations in early graphical user interfaces. While no definitive answer was provided, this comment hinted at the possibility of the size being a legacy from earlier computing eras.
Finally, the discussion touched on the inertia of established conventions. One commenter expressed a general sentiment of "if it ain't broke, don't fix it," suggesting that the 88x31 button size continues to serve its purpose adequately and therefore doesn't warrant change. This reinforces the idea that in the absence of compelling reasons for change, sticking with established standards is often the most pragmatic approach. Another commenter mentioned that rebuilding all existing UIs to accommodate a different button size would be a massive undertaking, and the benefits likely wouldn't outweigh the costs. This underscores the practical challenges involved in disrupting well-established conventions, even if there are theoretical advantages to doing so.