Stories with Tag mobile devices

• What even is a small language model now?

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  Posted: 2025-05-21 06:14:21

  Verbose tl;dr

  The definition of a "small" language model (LLM) is constantly evolving, driven by rapid advancements in LLM capabilities and accessibility. What was considered large just a short time ago is now considered small, with models boasting billions of parameters now readily available for personal use and fine-tuning. This shift has blurred the lines between small and large models, making the traditional size-based categorization less relevant. The article emphasizes that the focus is shifting from size to other factors like efficiency, cost of training and inference, and specific capabilities. Ultimately, "small" now signifies a model's accessibility and deployability on more limited hardware, rather than a rigid parameter count.

  The blog post "What even is a small language model now?" grapples with the rapidly evolving landscape of language models (LLMs) and the increasingly blurred lines defining model size. The author observes that the traditional categorization of LLMs into small, medium, and large based on parameter count is becoming less informative and even misleading. What was once considered a large language model, possessing billions of parameters, now pales in comparison to the behemoths containing hundreds of billions or even trillions of parameters. This dramatic shift in scale has redefined the meaning of "small," with models previously deemed large now falling into the "small" or "medium" category.

  The post further explores the implications of this changing landscape, highlighting the increasing accessibility of powerful LLMs. Previously, training and deploying large language models was an exclusive domain of resource-rich organizations due to the substantial computational requirements. However, advancements in model compression techniques, such as quantization and distillation, have enabled the creation of smaller models that retain much of the performance of their larger counterparts while requiring significantly less computational power. This democratization of access has led to a proliferation of powerful yet more manageable LLMs, blurring the lines further and challenging traditional size classifications.

  The author also delves into the nuances of evaluating LLMs, emphasizing that parameter count alone is an inadequate metric for assessing performance. Factors such as the training data, architecture, and specific tasks for which the model is optimized contribute significantly to its capabilities. Consequently, a smaller model meticulously trained on a curated dataset for a specific task might outperform a larger, more general-purpose model in that particular domain. This underscores the limitations of relying solely on size as a proxy for performance.

  Furthermore, the blog post discusses the emerging trend of specializing LLMs for specific tasks. Rather than training massive, general-purpose models, researchers are increasingly exploring the development of smaller, more focused models optimized for particular applications. This approach offers several advantages, including reduced computational costs, improved performance on the target task, and enhanced interpretability.

  In conclusion, the post argues that the definition of a "small" language model is in constant flux, driven by rapid advancements in the field. As model compression techniques continue to improve and specialized models gain prominence, the traditional size-based classifications are becoming less relevant. The author suggests that a more nuanced approach to evaluating LLMs is necessary, considering factors beyond parameter count to accurately assess their capabilities and suitability for specific applications. The future of LLMs likely lies in a diverse ecosystem of models ranging in size and specialization, each optimized for its intended purpose.

  • small language models
  • LLMs
  • Language Models
  • AI
  • artificial intelligence
  • natural language processing
  • NLP
  • Model Size
  • compute resources
  • hardware limitations
  • Parameter Efficiency
  • inference speed
  • Edge Computing
  • mobile devices
  • On-device AI
  • quantization
  • distillation
  • pruning
  • efficient AI
  • AI research

  Summary of Comments ( 38 )
  https://news.ycombinator.com/item?id=44048751

  Verbose tl;dr

  Hacker News users discuss the shifting definition of "small" language models (LLMs). Several commenters point out the rapid pace of LLM development, making what was considered small just months ago now obsolete. Some argue size isn't the sole determinant of capability, with architecture, training data, and specific tasks playing significant roles. Others highlight the increasing accessibility of powerful LLMs, with open-source models and affordable cloud computing making it feasible for individuals and small teams to experiment and deploy them. There's also discussion around the practical implications, including reduced inference costs and easier deployment on resource-constrained devices. A few commenters express concern about the environmental impact of training ever-larger models and advocate for focusing on efficiency and optimization. The evolving definition of "small" reflects the dynamic nature of the field and the ongoing pursuit of more accessible and efficient AI.

  The Hacker News post "What even is a small language model now?" generated several comments discussing the evolving definition of "small" in the context of language models (LLMs) and the implications for their accessibility and use.

  Several commenters highlighted the rapid pace of LLM development, making what was considered large just months ago now seem small. One commenter pointed out the constant shifting of the goalposts, noting that models previously deemed groundbreaking are quickly becoming commonplace and accessible to individuals. This rapid advancement has led to confusion about classifications, with "small" becoming a relative term dependent on the current state-of-the-art.

  The increasing accessibility of powerful models was a recurring theme. Commenters discussed how readily available open-source models and affordable cloud computing resources are empowering individuals and smaller organizations to experiment with and deploy LLMs that were previously exclusive to large tech companies. This democratization of access was viewed as a positive development, fostering innovation and competition.

  The discussion also touched upon the practical implications of this shift. One user questioned whether the focus should be on model size or its capabilities, suggesting a shift towards evaluating models based on their performance on specific tasks rather than simply their parameter count. Another commenter explored the trade-offs between model size and efficiency, noting the appeal of smaller, more specialized models for resource-constrained environments. The potential for fine-tuning smaller, pre-trained models for specific tasks was mentioned as a cost-effective alternative to training large models from scratch.

  Some comments expressed concern over the potential misuse of increasingly accessible LLMs. The ease with which these models can generate convincing text raised worries about the spread of misinformation and the ethical implications of their widespread deployment.

  Finally, several comments focused on the technical aspects of LLM development. Discussions included quantization techniques for reducing model size, the role of hardware advancements in enabling larger models, and the importance of efficient inference for practical applications.

• Your phone isn't secretly listening to you, but the truth is more disturbing

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  Posted: 2025-04-26 00:26:48

  Verbose tl;dr

  While the popular belief that smartphones constantly listen to conversations to target ads is untrue, the reality is more nuanced and arguably more disturbing. The article explains that these devices collect vast amounts of data about users through various means like location tracking, browsing history, app usage, and social media activity. This data, combined with sophisticated algorithms and data brokers, creates incredibly detailed profiles that allow advertisers to predict user behavior and target them with unsettling accuracy. This constant data collection, aggregation, and analysis creates a pervasive surveillance system that raises serious privacy concerns, even without directly listening to conversations. The article concludes that addressing this complex issue requires a multi-faceted approach, including stricter regulations on data collection and increased user awareness about how their data is being used.

  The article "Your phone isn't secretly listening to you, but the truth is more disturbing" from New Atlas delves into the persistent, yet unfounded, belief that smartphones actively listen to our conversations to target us with relevant advertising. The piece meticulously dismantles this conspiracy theory, emphasizing the lack of concrete evidence and the logistical and legal hurdles that would prevent such widespread, covert surveillance. It explains that constantly uploading audio data would rapidly deplete battery life and consume significant bandwidth, making it impractical. Furthermore, the potential legal repercussions and the inevitable public outcry if such a practice were discovered would be catastrophic for any company involved.

  However, the article argues that while our phones aren't actively listening, the reality of data collection is far more nuanced and, arguably, more concerning. It posits that the sheer volume of data already gathered about us through various legitimate means paints an incredibly detailed picture of our lives, interests, and desires. This data, collected through our online activity, app usage, location tracking, and interactions with social media platforms, is analyzed by sophisticated algorithms that can infer our needs and preferences with remarkable accuracy. The article illustrates this by citing examples of seemingly coincidental advertisements appearing after discussing a product or topic, explaining that these are not the result of eavesdropping but rather the product of sophisticated data analysis and predictive modeling.

  The article further elaborates on the intricate web of data brokers and advertising networks that trade and analyze this information, creating comprehensive profiles that are used to personalize our online experiences, including the advertisements we see. This ecosystem, while operating within the bounds of (often opaque) user agreements and privacy policies, raises significant concerns about the extent of data collection and the potential for manipulation. The piece highlights the potential for filter bubbles and echo chambers, where users are only exposed to information that confirms their existing biases, and the possibility of discriminatory advertising practices based on inferred demographics and characteristics. Ultimately, the article concludes that while our phones are not actively listening to our conversations, the reality of pervasive data collection and algorithmic profiling poses a greater, albeit less sensational, threat to our privacy and autonomy than the imagined scenario of constant surveillance. This complex system, operating largely in the background and beyond the immediate understanding of the average user, allows for a level of personalized targeting that, while not based on direct audio surveillance, can feel just as invasive and unsettling.

  • Smartphones
  • privacy
  • surveillance
  • Data Collection
  • Targeted Advertising
  • user tracking
  • online advertising
  • Data Privacy
  • Mobile Technology
  • digital privacy
  • algorithms
  • big data
  • Behavioral Targeting
  • data mining
  • Internet Privacy
  • mobile devices
  • Technology Ethics

  Summary of Comments ( 103 )
  https://news.ycombinator.com/item?id=43799802

  Verbose tl;dr

  Hacker News users generally agree that smartphones aren't directly listening to conversations, but the implication of the title—that data collection is still deeply problematic—resonates. Several comments highlight the vast amount of data companies already possess, arguing targeted advertising works effectively without needing direct audio access. Some point out the chilling effect of believing phones are listening, altering behavior and limiting free speech. Others discuss how background data collection, location tracking, and browsing history are sufficient to infer interests and serve relevant ads, making direct listening unnecessary. A few users mention the potential for ultrasonic cross-device tracking as a more insidious form of eavesdropping. The core concern isn't microphones, but the extensive, opaque, and often exploitative data ecosystem already in place.

  The Hacker News post "Your phone isn't secretly listening to you, but the truth is more disturbing" generated a substantial discussion with a variety of viewpoints. Several commenters echoed the sentiment expressed in the title, arguing that while direct audio surveillance might not be the primary concern, the extensive data collection practices employed by tech companies are even more troubling.

  One compelling line of discussion revolved around the sheer volume and detail of data collected, even without audio surveillance. Commenters pointed out that location data, browsing history, app usage, and social media activity paint a remarkably comprehensive picture of an individual's life, preferences, and even their current emotional state. This information, they argued, is more than sufficient to target highly personalized advertising and potentially manipulate behavior.

  Several users shared anecdotes of seemingly coincidental ad targeting, which fueled suspicion of covert listening. However, other commenters countered these anecdotes with explanations based on existing data collection practices, such as targeted advertising based on recent searches, browsing history, and location. Some explained how correlation and inference from seemingly unrelated data points can lead to eerily accurate ad targeting. For example, a change in location data combined with specific web searches could accurately predict a user's intent to purchase a certain product, even without directly listening to conversations.

  Another significant point of discussion focused on the lack of transparency and control users have over their data. Many expressed frustration with the difficulty in understanding how their data is being collected, used, and shared. The opacity of these processes makes it difficult to assess the true extent of data collection and its potential implications. This lack of control contributes to the sense of unease and distrust surrounding these practices.

  Some comments explored the potential for misuse of this data, including discriminatory practices, manipulation, and surveillance by governments or other entities. The potential for unintended consequences and the lack of adequate safeguards were also raised as areas of concern.

  A few commenters downplayed the concerns, arguing that personalized advertising is a fair trade-off for free services. They suggested that users who are uncomfortable with data collection can opt out of personalized ads or choose alternative services. However, others countered that opting out is often difficult and ineffective, and that true alternatives are scarce.

  Finally, some commenters discussed potential solutions, including stronger privacy regulations, improved data transparency, and user-centric data control mechanisms. The need for greater public awareness and education about data collection practices was also highlighted.

• Android phones will soon reboot themselves after sitting unused for three days

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  Posted: 2025-04-19 12:14:13

  Verbose tl;dr

  Android phones will soon automatically reboot if left unused for 72 hours. This change, arriving with Android 14, aims to improve security by clearing out temporary data and mitigating potential vulnerabilities that could be exploited while a device is powered on but unattended. This reboot occurs only when the phone is locked, encrypted, and not connected to a charger, minimizing disruption to users. Google notes that this feature can also help preserve battery life.

  In a forthcoming update to the Android operating system, Google is introducing a new feature designed to enhance the security and privacy of devices left inactive for extended periods. Specifically, Android phones and tablets that remain powered on but unused for a duration of 72 hours, equivalent to three days, will automatically initiate a system reboot. This measure aims to mitigate potential security vulnerabilities that could arise from prolonged uptime, particularly when devices are lost or stolen.

  This automatic reboot functionality operates on the premise that a device left untouched for three days is likely not in the immediate possession of its owner. By rebooting, the system clears any active sessions and temporary files, thereby reducing the window of opportunity for malicious actors to exploit potential vulnerabilities or gain unauthorized access to sensitive data. This is particularly relevant for devices without screen locks or with easily bypassed security measures.

  The change will be implemented as part of a future Google Play system update, a mechanism that allows Google to distribute updates to core system components independently of full operating system updates. This approach ensures a broader and more timely rollout across a wide range of Android devices, irrespective of the manufacturer or specific Android version running on the device, as long as it supports Google Play Services. This bypasses the often lengthy and fragmented update process typical of the Android ecosystem, allowing for a more consistent and rapid deployment of critical security enhancements.

  While the article does not specify the exact timeline for the rollout of this feature, it is characterized as "soon," suggesting that users can anticipate this change in the near future. The automatic reboot is positioned as a proactive security measure that adds an additional layer of protection for users in situations where their devices might be misplaced or compromised. It leverages the principle of least privilege, minimizing the potential attack surface by regularly clearing volatile memory and terminating potentially vulnerable processes.

  • Android
  • Mobile
  • Smartphones
  • Operating Systems
  • Reboot
  • Automatic Restart
  • Power Management
  • Battery Life
  • Security
  • software updates
  • Firmware
  • Android OS
  • mobile devices
  • Technology
  • Gadgets

  Summary of Comments ( 88 )
  https://news.ycombinator.com/item?id=43735902

  Verbose tl;dr

  Hacker News users largely criticized the proposed Android feature of automatic reboots after 72 hours of inactivity. Many considered it an unnecessary intrusion, arguing that users should have control over their devices and that the purported security benefits were minimal for average users. Several commenters suggested alternative solutions like remote wipe or enhanced lock screen security. Some questioned the actual security impact, suggesting a motivated attacker could simply wait out the 72 hours. A few users pointed out potential downsides like losing unsaved progress in apps or missing time-sensitive notifications. Others wondered if the feature would be optional or forced upon users, expressing a desire for greater user agency.

  The Hacker News thread discussing the Ars Technica article about Android phones automatically rebooting after three days of inactivity contains a moderate number of comments, mostly focused on the security implications and practical annoyances of this change.

  Several commenters express concern about the potential for data loss if the reboot occurs during a long-running process, such as a large file download or a multi-day GPS tracking activity. One user points out the inconvenience of returning to a device after a short trip only to find it has rebooted and requires re-authentication, potentially losing unsaved work in apps.

  The most compelling comments revolve around the security rationale behind the change. Some users question the actual benefit, arguing that a three-day window is too short to meaningfully address vulnerabilities and that a malicious actor gaining physical access to a device could easily circumvent this protection. Others propose alternative solutions, like requiring a PIN or password after a period of inactivity, as a more effective security measure.

  A few commenters speculate about the potential reasons for this change beyond security, suggesting it might be related to memory management or app behavior issues. However, these remain speculative.

  There is a thread discussing the potential impact on specific use cases, such as using an old phone as a dedicated music player or security camera. These scenarios highlight the frustration of having a device reboot unexpectedly, interrupting its intended function.

  Overall, the sentiment in the comments leans towards skepticism about the effectiveness and necessity of this automatic reboot feature, with many users expressing concerns about its potential downsides. The comments highlight the tension between security concerns and the desire for a seamless user experience.

• Automatically tagging politician when they use their phone on the livestreams

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  Posted: 2025-03-06 10:22:06

  Verbose tl;dr

  Belgian artist Dries Depoorter created "The Flemish Scrollers," an art project using AI to detect and publicly shame Belgian politicians caught using their phones during parliamentary livestreams. The project automatically clips videos of these instances and posts them to a Twitter bot account, tagging the politicians involved. Depoorter aims to highlight politicians' potential inattentiveness during official proceedings.

  Belgian artist Dries Depoorter has developed and deployed a sophisticated, automated system designed to identify and publicly highlight instances of Flemish politicians using their mobile phones during legislative sessions broadcast via livestream. This project, titled "The Flemish Scrollers," utilizes computer vision technology to meticulously analyze publicly accessible video feeds of parliamentary proceedings. The system is engineered to detect the characteristic shapes and movements associated with smartphone usage, such as the distinctive rectangular form of a phone held in a hand and the subtle yet discernible gestures involved in scrolling or tapping on a screen. Upon successful identification of such behavior, the system automatically generates a short video clip capturing the politician in the act of phone use. This clip is then promptly posted to a dedicated Twitter account specifically created for the project, thereby bringing the politician's in-session phone activity to the immediate attention of a wider audience. The system's aim is not simply to document these moments but to foster greater transparency and accountability regarding politicians' attention levels and engagement during official governmental proceedings. By making these instances of potential distraction readily accessible to the public, the project encourages scrutiny and discussion regarding appropriate conduct within the legislative chamber. The underlying technology employed represents a novel application of artificial intelligence and image recognition, demonstrating the potential for automated systems to monitor and analyze human behavior in public settings.

  • Politics
  • Technology
  • livestream
  • social media
  • Belgium
  • Flanders
  • politicians
  • phones
  • mobile devices
  • Internet
  • privacy
  • surveillance
  • art
  • digital art
  • Data Visualization
  • algorithmic art
  • artificial intelligence
  • computer vision
  • Automation
  • transparency
  • accountability

  Summary of Comments ( 105 )
  https://news.ycombinator.com/item?id=43278473

  Verbose tl;dr

  HN commenters largely criticized the project for being creepy and invasive, raising privacy concerns about publicly shaming politicians for normal behavior. Some questioned the legality and ethics of facial recognition used in this manner, particularly without consent. Several pointed out the potential for misuse and the chilling effect on free speech. A few commenters found the project amusing or a clever use of technology, but these were in the minority. The practicality and effectiveness of the project were also questioned, with some suggesting politicians could easily circumvent it. There was a brief discussion about the difference between privacy expectations in public vs. private settings, but the overall sentiment was strongly against the project.

  The Hacker News comments section for the post "Automatically tagging politician when they use their phone on the livestreams" (regarding the project "The Flemish Scrollers") contains a robust discussion with a variety of perspectives on the project's implications.

  Several commenters express concerns about privacy and surveillance. They question the ethics of publicly shaming politicians for using their phones, arguing that it's a form of public shaming and doesn't necessarily indicate wrongdoing. Some highlight the potential for misuse of this technology and the slippery slope towards increased surveillance of individuals. The idea that this could normalize such tracking and lead to its application to everyday citizens is a recurring worry. Some also point out the potential for false positives and the lack of context surrounding phone usage. A politician might be responding to an urgent matter or using their phone for work-related tasks, and the automatic tagging system doesn't differentiate between these scenarios.

  Others see the project as a valuable tool for transparency and accountability. They argue that it holds politicians accountable for their attention during public sessions and allows the public to see how engaged their representatives are. Some suggest that it could discourage distractions and encourage politicians to be more present during important discussions. The sentiment that the public has a right to know what their elected officials are doing is prevalent in these comments.

  A few commenters discuss the technical aspects of the project, including the use of facial recognition and AI. They delve into the accuracy of the system and the potential for biases in the algorithms. Some express interest in the technical implementation details and the challenges involved in identifying individuals and tracking their phone usage in real-time.

  There's also a discussion about the broader implications of this technology beyond just politicians. Some commenters speculate about its potential use in other contexts, such as monitoring student attention in classrooms or employee engagement in meetings. The ethical implications of such applications are debated, with some arguing that it could be a useful tool while others express concern about the potential for abuse.

  Finally, a handful of comments offer alternative perspectives or humorous takes on the situation. Some suggest that the project is more of an art piece or social commentary than a practical tool. Others joke about the potential reactions of politicians to being caught using their phones.

  Overall, the comments section reveals a complex and nuanced discussion about the project's ethical, technical, and societal implications. There is a clear divide between those who see it as a positive step towards transparency and accountability and those who view it as a potentially invasive form of surveillance. The discussion highlights the important questions surrounding the use of AI and facial recognition technology in public spaces and the balance between privacy and public access to information.

• How Google tracks Android device users before they've even opened an app

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  Posted: 2025-03-04 11:16:47

  Verbose tl;dr

  The Register reports that Google collects and transmits Android user data, including hardware identifiers and location, to its servers even before a user opens any apps or completes device setup. This pre-setup data collection involves several Google services and occurs during the initial boot process, transmitting information like IMEI, hardware serial number, SIM serial number, and nearby Wi-Fi access point details. While Google claims this data is crucial for essential services like fraud prevention and software updates, the article raises privacy concerns, particularly because users are not informed of this data collection nor given the opportunity to opt out. This behavior raises questions about the balance between user privacy and Google's data collection practices.

  A March 4th, 2025 article published by The Register, titled "How Google tracks Android device users before they've even opened an app," details research revealing how Google collects and transmits significant amounts of user data from Android devices, even prior to any application usage or user interaction. This pre-app data collection, occurring during the device setup phase and before a user logs in with a Google account, involves the transmission of unique identifiers such as hardware IDs, including the device's IMEI, MAC addresses for Wi-Fi and Bluetooth components, and various other build characteristics.

  The research, conducted by Douglas Leith at Trinity College Dublin, highlights that this initial data transmission allows Google to link the device and its associated identifiers to a specific user once they eventually log in with their Google account. This effectively creates a detailed pre-profile of the device and its potential user, associating hardware specifics with a later-provided Google identity.

  Leith’s study also underscores the discrepancy in data collection practices between Android and iOS. While both operating systems transmit some telemetry data during setup, Android is found to send significantly more information to Google, approximately 10 times the volume transmitted by iOS to Apple. This difference is particularly notable given the pre-login context, raising concerns about the extent of data collection before explicit user consent via account login.

  Furthermore, the research indicates that data transmission to Google occurs not just during the initial setup but also when a factory reset is performed, essentially resetting the data collection process. This continuous gathering of pre-login data emphasizes the pervasive nature of Google's tracking mechanisms within the Android ecosystem. The collected information, which can be used to build a comprehensive profile of the device and its user, raises privacy implications, especially considering the data transmission occurs before users actively engage with any applications or explicitly agree to data sharing through account creation.

  The article concludes by noting that this pre-app data collection practice allows Google to establish a link between a device and its eventual user even before any explicit interaction with Google services or applications. This preemptive data gathering raises questions about the transparency and user control over data sharing within the Android operating system.

  • Google
  • Android
  • tracking
  • privacy
  • Data Collection
  • Mobile
  • Operating System
  • User Data
  • surveillance
  • digital privacy
  • mobile devices
  • Tech
  • Technology
  • Apps
  • Pre-Install
  • Software

  Summary of Comments ( 22 )
  https://news.ycombinator.com/item?id=43253167

  Verbose tl;dr

  HN commenters discuss the implications of Google's data collection on Android even before app usage. Some highlight the irony of Google's privacy claims contrasted with their extensive tracking. Several express resignation, suggesting this behavior is expected from Google and other large tech companies. One commenter mentions a study showing Google collecting data even when location services are disabled, and another points to the difficulty of truly opting out of this tracking without significant technical knowledge. The discussion also touches upon the limitations of using alternative Android ROMs or de-Googled phones, acknowledging their usability compromises. There's a general sense of pessimism about the ability of users to control their data in the Android ecosystem.

  The Hacker News post discussing The Register's article about Google's Android tracking practices has generated a substantial discussion with various viewpoints and insights.

  Several commenters express concerns about the extent of data collection occurring before users even interact with apps. They discuss the implications of pre-installed apps and system-level services sending data to Google, highlighting the potential privacy risks, especially for users unaware of this background activity. Some debate the necessity of this data collection for functionality versus Google's potential exploitation for advertising or other purposes. The discussion also touches upon the difficulty for users to opt out of this tracking, given its integration within the Android operating system itself.

  One recurring theme is the comparison of Android's data collection practices to those of Apple's iOS. Commenters debate which operating system provides better privacy, with some arguing that Apple's approach is more transparent and user-centric. Others point out that both companies collect significant user data, albeit through different mechanisms.

  A few commenters delve into the technical aspects of the data collection, discussing the role of Firebase Cloud Messaging (FCM) and other system-level components. They explain how these components facilitate communication between devices and Google servers, enabling features like push notifications but also potentially contributing to the pre-app usage data collection.

  The discussion also extends to the broader issue of data privacy in the tech industry. Commenters express frustration with the lack of control users have over their data and the pervasive nature of tracking across various platforms and services. Some advocate for stronger regulations and greater transparency from tech companies regarding data collection practices.

  There are also more skeptical comments questioning the novelty or significance of the findings in The Register's article. Some suggest that this type of background data transmission is inherent in modern mobile operating systems and necessary for basic functionality. They argue that the article might be overstating the privacy implications or presenting information already known within the tech community.

  Finally, some commenters offer practical advice for users concerned about privacy, such as using alternative ROMs like LineageOS or exploring privacy-focused mobile operating systems like GrapheneOS. They discuss the trade-offs between functionality and privacy, acknowledging that more privacy-centric options may require technical expertise or involve sacrificing certain features.

• Using eSIMs with devices that only have a physical SIM slot via a 9eSIM SIM car

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  Posted: 2025-01-20 11:33:15

  Verbose tl;dr

  The article explores using a 9eSIM SIM card to enable eSIM functionality on devices with only physical SIM slots. The 9eSIM card acts as a bridge, allowing users to provision and switch between multiple eSIM profiles on their device through a companion app, effectively turning a physical SIM slot into an eSIM-capable one. The author details their experience setting up and using the 9eSIM with both Android and Linux, highlighting the benefits of managing multiple eSIM profiles without needing a physically dual-SIM device. While the process isn't entirely seamless, particularly on Linux, the 9eSIM offers a practical workaround for using eSIMs on older or incompatible hardware.

  This blog post by Neil Hughes explores a workaround for utilizing the convenience of eSIM profiles on devices limited by having only a physical SIM card slot. The author details his experience with the 9eSIM SIM card, a physical SIM card that acts as an intermediary, allowing users to store and switch between multiple eSIM profiles on devices that lack native eSIM support. He meticulously outlines the process, focusing on Android and Linux environments.

  Hughes begins by explaining the limitations of physical SIM cards and the advantages offered by eSIM technology, such as the ability to switch between carriers without physically swapping SIMs and the potential for streamlined device setup. He then introduces the 9eSIM card as a solution for bridging this gap, describing it as a physical SIM card that essentially emulates eSIM functionality.

  The core of the blog post lies in the step-by-step instructions for configuring the 9eSIM card. This involves downloading and installing the required Android application, scanning a QR code provided by 9eSIM to link the physical card with the user account, and then adding eSIM profiles to the 9eSIM account through the app. Hughes thoroughly explains the process of selecting a desired eSIM profile from within the app, which is then subsequently communicated to the physical 9eSIM card, effectively activating that chosen profile on the device.

  The author further extends the discussion by detailing his experience integrating the 9eSIM card with Linux. He provides specific command-line instructions for interacting with the 9eSIM card using tools like qmicli, enabling users to manage eSIM profiles directly from a Linux terminal. This portion of the post showcases a more technical approach, offering a deeper level of control for users comfortable with command-line interfaces.

  Throughout the post, Hughes incorporates screenshots to visually guide the reader through the different stages of configuration, making the process easier to follow. He emphasizes the convenience of being able to manage multiple eSIM profiles from a single physical card, highlighting the potential cost savings from utilizing data plans from different carriers depending on location or specific needs. He concludes by reflecting on his overall positive experience with the 9eSIM card, presenting it as a valuable solution for individuals who wish to leverage the benefits of eSIM technology on devices restricted to physical SIM cards. He also notes that while he focused on Android and Linux, the 9eSIM card theoretically supports iOS devices as well, although he has not personally tested that functionality.

  • eSIM
  • physical SIM
  • 9eSIM
  • SIM card
  • dual SIM
  • Android
  • Linux
  • mobile devices
  • compatibility
  • Hardware
  • Technology
  • Telecommunications
  • connectivity

  Summary of Comments ( 96 )
  https://news.ycombinator.com/item?id=42767584

  Verbose tl;dr

  Hacker News users discussed the practicality and security implications of using a 9eSIM to bridge the gap between eSIM-only services and devices with physical SIM slots. Some expressed concerns about the security of adding another layer into the communication chain, questioning the trustworthiness of the 9eSIM provider and the potential for vulnerabilities. Others were skeptical of the use case, pointing out that most devices support either physical SIM or eSIM, not both simultaneously, making the 9eSIM's functionality somewhat niche. The lack of open-source firmware for the 9eSIM also drew criticism, highlighting the difficulty in independently verifying its security. A few commenters saw potential in specific situations, such as using the 9eSIM as a backup or for managing multiple eSIM profiles on a single physical SIM device. Overall, the sentiment was cautiously curious, with many acknowledging the cleverness of the solution but remaining hesitant about its real-world security and usefulness.

  The Hacker News post discussing the use of eSIMs with physical SIM slots via a 9eSIM card has generated several comments exploring various aspects of the technology and its potential implications.

  One user expresses skepticism about the practicality of the solution, pointing out the added cost and complexity compared to simply using a standard physical SIM card. They question the target audience for such a product, suggesting that individuals who frequently switch between SIM profiles are more likely to already possess eSIM-compatible devices. This comment highlights the niche nature of the 9eSIM solution and challenges its value proposition.

  Another commenter raises concerns about the security implications of using the 9eSIM, particularly regarding the potential for cloning or unauthorized access. They question the robustness of the security measures implemented by the 9eSIM and express a preference for the inherent security of a physical SIM card. This concern reflects a broader anxiety surrounding the security of digital SIM technologies compared to their physical counterparts.

  A different perspective is offered by a user who sees the 9eSIM as a valuable tool for travelers, particularly those who require multiple SIM profiles for different regions or carriers. They highlight the convenience of switching between profiles without physically swapping SIM cards. This comment underscores a potential use case for the 9eSIM, catering to the needs of international travelers.

  Further discussion revolves around the technical details of the 9eSIM's functionality, with one user inquiring about the specific method used to provision the eSIM profiles onto the card. This technical question demonstrates the curiosity surrounding the inner workings of the 9eSIM technology.

  Finally, a commenter mentions the potential for using the 9eSIM as a backup solution in case of a lost or stolen phone. They suggest that the ability to quickly transfer a SIM profile to a different device could be a valuable feature. This comment expands the potential applications of the 9eSIM beyond its primary use case.

  In summary, the comments on the Hacker News post reflect a mixed reception to the 9eSIM technology. While some users acknowledge its potential benefits for specific use cases like international travel or backup solutions, others express concerns about its cost, complexity, and security implications. The discussion also delves into the technical aspects of the technology, indicating a general interest in understanding its functionality.

• Tcl's bet on screens that look like paper

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  Posted: 2025-01-15 12:50:15

  Verbose tl;dr

  TCL is betting on "NXTPAPER" screen technology, which aims to mimic the look and feel of paper for a more comfortable reading experience. This technology utilizes multiple layers of reflective material to enhance contrast and reduce blue light, creating a display that appears brighter in sunlight than typical LCDs while maintaining low power consumption. While not e-ink, NXTPAPER 2.0 boasts improved color gamut and refresh rates, making it suitable for not just e-readers, but also tablets and potentially laptops. TCL aims to expand this technology across its product lines, offering a paper-like alternative to traditional screens.

  This blog post by Gergely Orosz delves into TCL's strategic investment in "NXTPAPER," a display technology designed to mimic the appearance and feel of paper. The author meticulously examines TCL's rationale for pursuing this technology, analyzing it within the broader context of the display market and the company's product portfolio. Orosz begins by highlighting the growing demand for e-ink displays, particularly in e-readers, and the limitations of this technology, such as low refresh rates and limited color reproduction. This sets the stage for introducing TCL's NXTPAPER, which aims to bridge the gap between the comfortable readability of e-ink and the vibrancy and responsiveness of traditional LCD or OLED screens.

  The core of the post focuses on the technical underpinnings of NXTPAPER. Orosz explains that it's not an entirely new display technology but rather a combination of existing LCD technology and a highly reflective layered display stack. He details how this layered structure, which includes a dedicated reflective layer and multiple optical films, minimizes backlight reliance, thereby reducing power consumption and achieving a paper-like effect. The author emphasizes the importance of ambient light in NXTPAPER's functionality, contrasting it with emissive displays that generate their own light. He further elaborates on the technology's advantages, including reduced blue light emission, a claimed 65% reduction compared to typical LCDs, which contributes to improved eye comfort. The post also discusses color reproduction capabilities of NXTPAPER, noting that while it doesn't achieve the wide color gamuts of high-end displays, it offers acceptable color performance for everyday use.

  Orosz further analyzes TCL's market positioning for NXTPAPER. He observes that TCL is initially targeting the tablet and e-reader segment, aiming to provide a more versatile and colorful alternative to traditional e-ink devices. He also speculates about the potential application of NXTPAPER in other product categories, such as laptops, particularly given the increasing demand for devices suitable for both work and content consumption. The author concludes by discussing the potential challenges and opportunities facing TCL's NXTPAPER technology, acknowledging the competitive landscape and the need for further development to fully realize its potential. He raises questions about the technology's long-term viability and its ability to compete with established display technologies, ultimately positioning NXTPAPER as an intriguing development worth watching in the evolving world of display technology.

  • TCL
  • NxtPaper
  • display technology
  • e-paper
  • e-ink
  • reflective display
  • low power display
  • eye strain
  • reading comfort
  • screen technology
  • mobile devices
  • tablets
  • e-readers

  Summary of Comments ( 38 )
  https://news.ycombinator.com/item?id=42710296

  Verbose tl;dr

  Hacker News commenters discuss TCL's NxtPaper display technology, generally expressing skepticism about its widespread adoption. Some doubt the claimed power savings, especially given the backlight required for color displays. Others question the "paper-like" feel and wonder if it truly offers advantages over existing e-ink or LCD technologies for typical use cases. A few commenters express interest, particularly for niche applications like e-readers or note-taking, but overall the sentiment is cautious, awaiting real-world reviews and comparisons to determine if the technology lives up to its promises. Some also discuss the history of similar display technologies and their ultimate lack of success.

  The Hacker News post "Tcl's bet on screens that look like paper" generated a moderate amount of discussion with 24 comments. Several commenters focused on the practical implications and potential applications of the NxtPaper technology.

  One commenter expressed skepticism about the "reflective LCD" description, arguing that it likely functions more like e-ink and questioning the claimed power savings for video playback. This sparked a short thread discussing the potential use of a backlight and how it might affect battery life compared to traditional LCDs.

  Another user highlighted the importance of clarifying the refresh rate, especially given the marketing around "video." They pointed out that even a slightly slow refresh rate can significantly impact the user experience, making it unsuitable for smooth video playback.

  A few comments centered around the niche appeal of such displays. One commenter suggested that devices with this technology could be ideal for reading in direct sunlight, addressing a common shortcoming of traditional screens. Another pointed out the potential for educational uses, particularly in developing countries where power consumption is a major concern.

  Several users brought up comparisons with existing e-ink devices, particularly those from Remarkable and Onyx Boox. They discussed the trade-offs between refresh rate, color accuracy, and power consumption, suggesting that NxtPaper might occupy a middle ground between e-ink and traditional LCDs.

  One commenter shared a personal anecdote about using a reMarkable tablet, praising its paper-like feel but lamenting the lack of backlighting for use in low-light conditions. This tied back to the earlier discussion about the potential benefits and drawbacks of incorporating a backlight in NxtPaper devices.

  A couple of commenters expressed concerns about TCL's track record with software updates and customer support. They questioned whether the company would provide adequate long-term support for devices using this technology.

  Finally, a few comments simply expressed interest in the technology and hoped to see wider adoption in the future. Overall, the comments reflect a cautious optimism about NxtPaper, acknowledging its potential benefits while also raising valid concerns about its practical limitations and TCL's ability to deliver a compelling product.