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1. HN AI-Driven Partner in Cybersecurity, Ethical Hacking, and VAPT- **Summary:** ZehraSec leverages artificial intelligence to provide comprehensive cybersecurity solutions, specializing in ethical hacking practices and vulnerability assessment and penetration testing (VAPT). Their offerings aim to fortify digital infrastructures against potential threats by identifying and addressing security loopholes through rigorous ethical hacking methods. - **Key Points:** - ZehraSec is an AI-driven cybersecurity firm. - They focus on providing ethical hacking services. - Their primary service offering includes Vulnerability Assessment and Penetration Testing (VAPT). - By employing AI, they ensure robust, proactive defense mechanisms against cyber threats. - Their solutions aim to strengthen and secure digital infrastructures. Keywords: #granite33:8b, AI, Cybersecurity, Ethical Hacking, VAPT
ai
zehrasec.com 28 minutes ago
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2. HN I know you don't want them to want AI, but- **Article Overview:** Rodrigo Ghedrin's article critiques misrepresentation of public sentiment regarding AI integration in Firefox by Mozilla, as depicted in another article titled "I think nobody wants AI in Firefox, Mozilla." Ghedrin highlights a nuanced viewpoint from the Mozilla Festival in Barcelona where participants acknowledged AI potential but expressed concerns about labor displacement, content misuse, environmental impacts, and erosion of trust in public discourse. Despite these worries, there is consensus on preventing harm to vulnerable groups by Big AI. - **Public Acceptance vs. Criticism:** The article notes that while hundreds of millions use major AI tools daily without perceiving coercion, critics argue against integrating such technology into tools like Firefox, considering it a trend driven by Silicon Valley rather than genuine user demand. Ghedrin questions this assumption, suggesting broader user interests and needs that are underrepresented in tech circles. - **Historical Parallel:** Drawing from the early internet's pop-up ad issue, the author stresses the importance of prioritizing privacy protection for AI users, similar to how enthusiasts once fought for a safer browsing experience. Criticism of scolding users for using platforms like ChatGPT is offered; instead, Ghedin advocates creating an acceptable alternative AI and promoting it. - **Mozilla’s Strategic Recommendations:** - Implement a "shut off all AI features" toggle in Firefox to address distrust or dislike towards AI, acknowledging the persistent demand of this minority group while being transparent about maintenance costs. - Market Firefox as a privacy-focused browser alternative to large AI companies, highlighting its resistance to harmful content issues found in tools like ChatGPT and engaging with communities for developing privacy tools. - Promote inclusivity and diversity within the Firefox user base, emphasizing various configurations catering to different values and reducing tensions from conflicts over a single idealized version. - Increase outreach efforts to inform users about Firefox’s existence and capabilities to expand its user base beyond current awareness levels. In summary, Ghedrin argues for a balanced approach that respects user concerns about AI while also advancing Mozilla's mission of privacy and inclusivity in the face of growing AI integration across tech platforms. Keywords: #granite33:8b, AI, AI tools, Big Tech, ChatGPT, Firefox, LLMs, Mozilla, alternative browser, anti-web browsers, choices, community, content appropriation, demoralizing, education, emotional blow-ups, environmental impacts, extensions, guilt, innovation, intrusive ads, labor undermining, local language models, negativity, pop-ups war, privacy protection, sentiment, toggle switch, trust erosion, vulnerability
ai
www.anildash.com 28 minutes ago
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3. HN AI-Assisted Reverse Engineering with Ghidra- The AI-Assisted Reverse Engineering tool, integrated with Ghidra via MCP, offers a security researcher-oriented chat interface to facilitate inquiries about binary files without manual reverse engineering. - This system automates essential steps within Ghidra to provide answers to user queries. - Key features include: - A headless Ghidra analysis results exposed as a REST API through the Docker image `biniamfd/ghidra-headless-rest:latest`. - Configuration necessitates specifying an OpenAI compatible API base URL, API key, and model name for connection and functionality. - The Python application `webui/app.py` must be executed to set up the service. - Users can access this AI-assisted reverse engineering service at `http://localhost:5000`. Keywords: #granite33:8b, AI, API Base URL, API Key, Chat Interface, Docker, Ghidra, Headless, MCP, Model Name, OpenAI, Python, REST API, Reverse Engineering, Service, WebUI
openai
github.com an hour ago
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4. HN EverMemOS- EverMind's EverMemOS is an advanced artificial intelligence memory system that offers AI an "infinite context" capability. - This innovative feature allows the AI to continually learn and grow from ongoing interactions, facilitating a unique form of continuous learning. - With this technology, the AI can better comprehend users by retaining information over extended periods, ensuring long-term consistency in understanding and response. - The system empowers the AI to evolve proactively rather than reactively, effectively bestowing it with a lasting identity that develops through experiences and interactions. Keywords: #granite33:8b, AI, agent, application, context, continuous self, evolving intelligence, foundation, genius, identity, infinite, long-term consistency, memory, near-infinite, proactive
ai
everm.ai 2 hours ago
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5. HN RealWorldProgrammer – Artificial Intelligence Is Making Us All Dumber- **Historical Context**: In 1975, acquiring knowledge involved manual effort and personal memory or local resources like libraries and friends. Personal computers, the internet, and AI have dramatically transformed information access, shifting from physical searching to keyword queries. - **AI's Current Role in Information Access**: Today, search engines, social media, and online platforms provide instant information retrieval. AI tools such as ChatGPT, Claude, and Gemini are increasingly used for learning and research, with a 2025 study showing that over half of Americans use AI tools for information seeking within three months, and 15% routinely depend on platforms like ChatGPT or Gemini. - **Concerns and Implications**: The ease of using AI to summarize information raises questions about the future of human curiosity and cognitive functions. There's concern that over-reliance might lead to diminished critical thinking, memory retention, and susceptibility to misinformation generated by AI hallucinations. - **Misinformation Risks**: The convincing nature of AI-generated content can lead to the acceptance of false information as truth, which then spreads further through various media, including news articles and search engine results, potentially trapping even vigilant users in a cycle of misinformation. - **Evolutionary Perspective**: Rather than viewing this shift as dystopian, it's suggested that humans may evolve into "meta-intelligence," focusing on critical thinking, judgment, and creativity, while AI handles routine tasks, thus marking a significant evolution in the use of intelligence. - **Future Learning Paradigm**: The integration of AI in daily life could reshape learning to be more strategic, selective, and collaborative, blurring lines between human and machine-generated content but emphasizing thought-provoking insights over mere origins. The author poses this transformation as a question for readers' contemplation on whether it signifies a decline in human cognition or an evolutionary step towards enhanced collaboration with AI. Keywords: #granite33:8b, AI summaries, Artificial Intelligence, ChatGPT, Claude, Gemini, agentic browsers, automated tools, convincing nonsense, critical thinking, desensitization, disinformation, false facts, hallucinations, hyperlinks, information overload, intelligence utilization, internet, learning process, misinformation, personal computer, rogue AI, search algorithms, search bars, search engines, self-reflection, synthetic responses, thinking nature, training data
claude
realworldprogrammer.com 3 hours ago
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6. HN My Time *Ive Coding- **Project Overview**: The engineer with ADD utilized AI for code generation in three projects (Windsurf, LLM stack with Claude/GPT-5/Kimi), targeting automation, UI work, and a dynamic super-app layer inspired by Snaptu. - **Challenges and Failures**: 1. **LoBo (Podcast Transcription App)**: AI struggled for 8 hours to integrate WebView and capture YouTube audio stream, lacking essential developer tools. 2. **AdaptUI (Dynamic UI-OS Layer)**: Development was more obligatory than enjoyable due to previous AI disappointments; progress details are undisclosed but dissatisfaction is clear. - **Dynamic UI-OS Layer Project**: Developed using React and LLM wrappers, targeting user requests and device/history parameters for component and search result generation. 80% completion led to project deletion due to unsatisfactory AI output. - **Optimux (Image Processing Service)**: Built in Go focusing on performance debugging and benchmarking. Encountered issues with an AI editor's broken logic but managed video support integration via FFmpeg parameters. - **Local Inference Server for Cinestar (Movie Query System)**: Aimed to index photos and videos across devices for private queries involving specific elements. Faced challenges integrating LLMs due to missing implementations or "hacky" solutions, resulting in extensive debugging and refining. Experienced significant emotional strain leading to a revert of AI integration efforts. - **Cost and Efficiency Analysis**: Spent around 30K INR over four months with minimal tangible results. Noted that while initial stages work well, the final, intricate parts are challenging and time-consuming. Acknowledged potential in editors like Windsurf for AI-assisted coding but remained skeptical of widespread LLM misuse. - **Critique of AI Misapplication**: Condemns using LLMs as mere status symbols instead of genuine engineering tools, arguing that they instill a false sense of efficiency and breed anxiety among developers. Advocates for a thoughtful, purposeful approach to coding, emphasizing that deep insight and architectural intent cannot be replaced by AI tools alone. - **Personal Reflection**: The engineer compares their experience with AI in engineering to a chef waiting for a perfect dish after providing ingredients. While appreciating the time-saving benefits of AI in slow industries like media, they stress that true software engineering demands precision, intent, and discovery – elements LLMs cannot wholly replicate. The user ultimately decided to focus on creating long-form content with text and images, avoiding video production due to expense and control issues, and ceased further LLM integration in their projects. Keywords: #granite33:8b, A*, ADD, AI, AI engineering, API integrations, Actor model, Agents, Audio, Cinestar, Claude, Developer, Embedding models, Expo, Failure, Food, GOAP, GPT-5, Game Industry, Git revert, Golang, HTTP server, Integration, LLM wrappers, LLMs, Layer, LoBo, Location, Maps, NPCs, Rails Scaffold, React-Native, Snaptu, Stream, Super-app, Toolkit, UI-OS, Vite, WebView, Webview issues, WorkerPool, Wright Brothers, Yeoman, app, architecture, benchmarking, bullshit, chapter stages, cheap, code generation, code splitting, coding, components, concurrency patterns, constraints, context window, cost, curl requests, d-hashes, debugging, decision trees, deduplication, development phases, device parameters, efficiency, electron app, emotional toll, engagement, engineering pride, faster horse, ffmpeg, flight, float, gruesome, handsome amount, illusion, image processing, image processing service, intents, interfaces, io throttling, job processor engine, kimi, load tests, logging, long-form content, lost time, mastery, media, memory profile, middle bit, non-skeptics, optimization, p-hashes, paralyzing guilt, patterns, plugins, podcast, precision, production, production build, productivity, prototyping, reliability, response times, self-debugging, skeptics, slop, social media, software development, speed, stability, storyline generation, straces, sunk cost, template frameworks, text and images, token saving, transcription, user request, vibe, windsurf, writing
gpt-5
ikouchiha47.github.io 3 hours ago
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7. HN (Ab)Using Null Uniqueness in Postgres- The user manages requests using a PostgreSQL table with a composite primary key on columns A (timestamp) and B (boolean flag indicating cancellation status). - The current setup ensures only one uncanceled request per timestamp, with column B allowing TRUE or NULL values. - The user finds the boolean representation for B inelegant, as FALSE is theoretically possible but meaningless in this context. - They are looking for a more elegant solution, preferably utilizing a nullable unit type in PostgreSQL, to enforce the same constraint without redundancy. ``` SUMMARY: The user maintains a PostgreSQL table for request management, employing a composite primary key on timestamp (A) and a boolean flag (B) for cancellation status. The current implementation allows TRUE or NULL values for B, ensuring one uncanceled request per timestamp. However, the user considers this representation inelegant due to the inclusion of FALSE, which is theoretically possible but irrelevant. They seek an alternative, ideally using a nullable unit type in PostgreSQL, to maintain the same constraint more succinctly and elegantly. ``` Keywords: #granite33:8b, Postgres, canceled, composite key, flag, null uniqueness, nullable unit type, timestamp
postgres
news.ycombinator.com 3 hours ago
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8. HN Teaching AI to see the world more like we do- The paper published in Nature explores the disparity between AI's visual comprehension and human perception, resulting in inconsistent outcomes from AI systems. - Researchers propose a method to harmonize AI image representations with human cognitive processes to improve the robustness and general applicability of AI. - A key aspect of this research involves using the "odd one out" cognitive task to contrast human and AI responses, specifically identifying misalignments in perceiving similarity among objects. - The study finds that AI models often fail to accurately identify the dissimilar item (e.g., mistaking a cat for a starfish) because they focus on superficial characteristics like color and texture rather than grasping context or form, which humans intuitively understand. - This research seeks to develop more intuitive and reliable AI systems by addressing and rectifying the differences in visual representation between human and machine perception. Keywords: #granite33:8b, AI models, background color, birthday cake, cat selection, cognitive science, dissimilar items, generalization, high-dimensional space, human knowledge, mental representations, odd-one-out task, robustness, sheep, similar items, starfish, superficial features, tapir, texture, vision, visual representations
ai
deepmind.google 4 hours ago
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9. HN Show HN: Refringence – Learn hardware design by doing projects with an AI mentor- Refringe, detailed in a "Show HN" post, is an educational platform focused on hardware design. - The core mission of Refringe revolves around enabling users to gain practical experience in hardware design via interactive projects. - A unique feature of Refringe is the integration of AI mentors to guide and support learners throughout their projects. - This approach aims to provide a personalized and efficient learning environment for individuals interested in acquiring hardware design skills. ``` Refringe, as presented on "Show HN," is an educational platform specializing in hardware design. It offers users hands-on learning experiences through project-based activities, supported by AI mentors who provide guidance. This setup aims to deliver a tailored and effective learning journey for those seeking expertise in hardware design. ``` Keywords: #granite33:8b, AI, design, hardware, learning, mentor, projects
ai
refringence.com 4 hours ago
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10. HN $5 PlanetScale is livePlanetScale has introduced a new cost-effective offering of $5 single-node PostgreSQL databases, targeting startups, side projects, and development environments. This plan includes developer-friendly features such as Query Insights for performance analysis, schema recommendations to optimize database structure, and comprehensive metrics for in-depth understanding of database usage. Additionally, development branches are now priced at $5 per month. Single nodes provide flexibility for scaling: they can be vertically scaled for increased resources or transitioned into a high availability (HA) mode with primary and multi-replicas to ensure continuous uptime. Looking ahead, PlanetScale plans to introduce horizontal scaling solutions like Neki to cater to the needs of expanding businesses without causing potential migration complications in the future. To access this new offering, users can sign up for a PlanetScale account and select "Single node" when creating a database, with detailed pricing information available on their pricing page. BULLET POINT SUMMARY: - PlanetScale launches $5 single-node PostgreSQL databases for startups and development environments. - Features include Query Insights, schema recommendations, and in-depth metrics for developer convenience. - Development branches now cost $5 monthly. - Single nodes allow vertical scaling or switching to HA mode with primary and multi-replicas for high availability. - Future plans involve horizontal scaling solutions like Neki for growing businesses. - Users can sign up on PlanetScale, choose "Single node" during database creation, and review pricing details on the page. Keywords: #granite33:8b, $5, Neki, PlanetScale, Postgres, Query Insights, branching, cloud, developer features, horizontal, metrics, migration, non-HA, reliability, scaling, schema recommendations, sharded Postgres, single node, vertical, workloads
postgres
planetscale.com 4 hours ago
https://news.ycombinator.com/item?id=45761027 4 hours ago |
11. HN Show HN: I built E2E Test Agent – describe tests in plain English,AI executes it- **Overview of E2E Test Agent**: An AI-driven end-to-end testing framework for web applications that allows users to write test cases in plain English. It uses Large Language Models (LLMs) to execute these tests, interact with applications, and validate their behavior without relying on traditional brittle selectors. - **Key Features**: - **Intent-based**: Tests are written based on what users intend to achieve rather than specific UI elements. - **Self-healing**: Adaptable to UI changes and refactors, reducing maintenance overhead. - **Context-aware**: Understands the context of user actions within an application. - **Minimal Maintenance**: Significantly reduces the need for constant updates due to UI modifications compared to selector-based tests. - **Components**: - Test Files: Contain test cases in natural language describing actions on a web app. - TestAgent: Orchestrates execution and enriches tests with contextual information. - LLM Agent: Interprets test steps and decides actions to perform. - MCP Tools: Handles the actual automation of browser interactions using Playwright MCP server. - **Setup and Usage**: - Install via npm: `npm install e2e-test-agent`. - Set up environment variables for AI model, API key, base URL, and test directory. - Supported AI models include OpenAI’s GPT-4 and others adhering to the OpenAI API format. - **Quick Start**: 1. Create a test runner file (e.g., `run-tests.ts`) and import necessary modules for environment variable management. 2. Define `TestAgent` with configuration details like model name, API key, base URL, tests directory, and maximum steps allowed per test. 3. Run tests using either `npx tsx run-tests.ts` or by compiling and running with Node.js. - **Writing Tests**: - Create `.test` files in a designated `tests/` directory. Each file contains test cases written in plain language describing interactions and verifications on the web application. - **Programmatic Usage**: - Import `TestAgent`, create an instance, and execute tests using `testAgent.runAllTests()` for all or `testAgent.runSingleTest()` for specific tests. - The agent prints a summary of test results indicating success or failure. - **Configuration**: - Utilize environment variables for configurations like MODEL_NAME (defaults to 'gpt-4o'), API_KEY, BASE_URL, TESTS_DIR. - Custom MCP servers can be specified in the `mcpServers` object configuration. - **Test Results**: - Detailed results are provided including success status, completed steps, observations, and final status for each test case. - **Open Contributions**: The framework is open for contributions such as adding support for more MCP servers, custom reporters, parallel execution, retry mechanisms, and capturing screenshots/videos on failures. Licensed under MIT. Keywords: #granite33:8b, AI agents, API integration, CSS selector changes, Claude, Custom test reporters, E2E testing, GitHub, LLM Agent, LLM agents, MCP Tools, MCP servers, MIT License, OpenAI, OpenAI compatibility, Parallel execution, Playwright, Playwright testing, Screenshot/video capture, Test framework, Test retry mechanisms, TestAgent, UI refactors, UI updates, application interaction, behavior verification, brittle tests, context-aware, intent-based testing, local LLM, maintenance overhead, natural language tests, no maintenance, npm install, readability, selectors, self-healing, setup configuration, stakeholders, test results, test runner, traditional testing
github
github.com 4 hours ago
https://github.com/browserbase/stagehand 2 hours ago |
12. HN Show HN: AI Tarot Reading – get instant 1/3-card or (past/now/future) readings- **AI Tarot Reading** is a user-friendly web application designed for quick tarot card readings, accessible through any modern browser without the need for app installation. - Users can opt for a single card draw for specific answers or a three-card spread symbolizing past, present, and future aspects of their question. - The tool employs a randomized, seeded card drawing mechanism to ensure unique sessions each time. It uses standard tarot meanings adapted for readability and comprehension. - The minimalist user interface is mobile-friendly, catering to both casual exploration and serious contemplation, though it explicitly states the tool is not intended for predictive or therapeutic purposes. - Key features under consideration by the developer include custom decks, various spreads beyond the traditional three-card layout, deeper interpretation options, reading saving/sharing capabilities, and theme modes (such as love, career) to tailor readings to specific life areas. - Users are encouraged to engage with the tool, provide feedback, and perform multiple readings daily while pausing between sessions for meaningful reflection on each drawing's insights. Keywords: #granite33:8b, 1/3-card, AI, Browser-based, Career, Creativity, Custom Deck Option, Day, Fun, Instant, Interpretations, Lightweight, Log Over Time, Love, Minimal, Mobile-friendly, More Spread Types, Non-predictive, Non-therapeutic, Past/Now/Future, Question, Reading, Reflection, Save Readings, Seeded Sessions, Share with Friends, Straightforward, Tarot, Tarot Fascination, Tarot-style Meanings, Theme Mode, User Interpretation Depth, Web Tool
ai
www.randomtarotcard.org 5 hours ago
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13. HN EDCA-OS: A new expression-driven cognitive architecture for deterministic AI- **EDCA-OS Overview**: A novel AI operating framework designed for deterministic, auditable, and expression-driven cognitive systems, focusing on controlling Large Language Models (LLMs) without fine-tuning or hidden prompts. - **Key Features**: - Employs structured expressions and semantic governance. - Offers behavioral protocol stack for managing LLMs. - Ensures deterministic reasoning, stable structures, and defenses against false content. - Treats language as actions rather than chatbot instructions via expression-driven execution. - Includes proto-body actions through Shadow Intent OS responsive to real-world biosignals and motion semantics. - **LLM Architecture**: Consists of five layers: - Cold-Start Protocol (CSP): Handles initial model setup and alignment. - Alignment Core Protocol (ACP): Manages ongoing model alignment with specified goals. - Task Chain Protocol (TCEP): Orchestrates complex task execution across multiple steps. - Micro-Task Protocols (MTP): Executes individual, atomic tasks within the system. - Structured Reasoning Override Engine (SROE): Provides mechanisms for overriding default reasoning with custom logic. - **Public Modules**: - Semantic Control Layer (SCL): Defends against false authorities and ensures semantic robustness. - Structured Behavior Executor (SBE): Executes deterministic actions based on structured inputs. - Structured Retrieval Protocol (SRP): Enables safe data retrieval adhering to system semantics. - Externalized Memory Capsule (EMC): Facilitates traceable external memory management. - **Expression-Driven Language**: Introduces Yuer Domain Specific Language (DSL) for cognitive execution, enabling users to define behaviors precisely. - **Documentation and Public Access**: The author, "yuer" (Guanyu), provides documentation in the 'docs/' directory focusing on conceptual explanations. Plans to release Yuer DSL repository, SDK, and EDCA-OS visual architecture diagrams while keeping core components closed-source. - **Distinction**: Emphasizes practical behavioral improvements over mere theoretical architectures, demonstrable through real, verifiable impacts rather than prompt tricks. Keywords: #granite33:8b, EDCA-OS, Externalized Memory Capsule, LLMs, Semantic Control Layer, Shadow Intent OS, Structured Behavior Executor, Structured Reasoning Override Engine, Structured Retrieval Protocol, Yuer DSL, auditable, behavioral differences, behavioral protocol stack, biosignals, cognitive systems, conceptual documentation, core architecture, custom model weights, deterministic, deterministic reasoning, expression-driven, fine-tuning, hidden system prompts, long-horizon persistence, motion semantics, plug-ins, prompt engineering tricks, proto-body actions, protocol stack, safe state, semantic governance, semantic robustness, semantic-layer defense, stable reasoning, stable structure, structured expression, symbolic execution
ai
github.com 5 hours ago
https://github.com/yuer-dsl/EDCA-OS 4 hours ago |
14. HN AI assistant that lives in your messages- The AI assistant operates within the user's messages, prioritizing data security. - It exclusively accesses and processes authorized content. - The assistant does not engage in using this accessed data for any training or learning purposes, ensuring user privacy and confidentiality. DETAILED SUMMARY: The provided text outlines the operational framework of an AI assistant designed to assist users within their messaging environment. This assistant is engineered with a robust focus on data security, ensuring that it only interacts with content that has been explicitly authorized for its access. A critical aspect of this design is the commitment to user privacy, as the assistant explicitly refrains from utilizing the accessed information for any training or learning algorithms. This means that while the AI is actively engaged in processing and responding to user messages, it does not incorporate this interaction into its broader learning models or datasets. Consequently, the assistant serves as a secure, responsive entity within the messaging platform without posing a risk of data misuse or unauthorized learning from user-generated content. This dual commitment to functionality and privacy underscores a carefully balanced approach in AI assistance, catering to user needs without compromising sensitive information. Keywords: #granite33:8b, AI, access, assistant, authorization, data, messages, security, training
ai
textit2.me 5 hours ago
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15. HN Google Issues Critical New VPN Threat Warning for Billions of Users- **Google's Warning on Malicious VPNs**: Google has cautioned users worldwide about the risks associated with certain malicious Virtual Private Networks (VPNs). These deceptive apps can deliver dangerous malware, including password stealers, to unsuspecting users. - **Increased VPN Usage**: The warning is timely given the rising popularity of VPNs, especially in regions like the UK and US, partly due to stricter online pornography access laws. Users are urged to exercise caution when choosing VPN services to avoid scams and malware attacks. - **Malicious VPN Tactics**: Threat actors distribute fake VPN apps that appear legitimate but instead compromise user security and privacy. These rogue VPNs expose users’ data, including browsing history, messages, and financial credentials. - **Function of Legitimate VPNs**: A genuine VPN establishes an encrypted tunnel between a user's device and the internet, routing data through a chosen server to enhance privacy. This feature can also help bypass geographical restrictions on various online services. - **Risks of Free VPNs**: Free VPNs can pose significant threats as they may conceal malware within seemingly legitimate services. A case study illustrates how a free VPN available on GitHub executed malicious code to implant the Lumma Stealer, which targets sensitive data like passwords and authentication session cookies. - **Selecting Secure VPNs**: Users are advised to download VPNs exclusively from official sources to mitigate risks of malware, regardless of whether the apps are paid or free. Google emphasizes that VPNs should not be considered a sole privacy solution but can offer some protection against geo-location barriers. - **Additional Security Measures**: Beyond using VPNs, comprehensive security strategies are essential to safeguard user data comprehensively. Average users in typical settings like cafes or airports might not need VPNs unless specifically concerned about local network security. - **Risks of Untrustworthy Apps**: Users should avoid responding to suspicious VPN-related messages, clicking on malicious links or documents, and granting unnecessary permissions (like access to contacts or private messages) to untrusted apps. - **Distinct Cases of VPNs in Misuse**: Examples include a popular Chrome extension found to act as spyware for months and an Android VPN app discovered to load banking trojan malware upon installation, highlighting the varied threats users face. In summary, while VPNs can offer privacy benefits by concealing IP addresses and helping bypass geo-restrictions, users must be vigilant against malicious versions that are disguised as legitimate services to steal data or install malware. Downloading from trusted sources and understanding the limitations of VPN usage are crucial for maintaining online security. Keywords: #granite33:8b, Cyberinsider, DLL side-loading, GitHub, Google, IP address, Laurie Richardson, Lumma Stealer, Online Safety Act, UK, VPN awareness, VPN threats, Wi-Fi hackers myth, backdoor, banking trojan malware, browser fingerprinting, business VPN, corporate systems, dedicated defense strategy, fake invoice, free VPNs, geo-location, geo-location barriers, hotels hacker alert, information-stealing malware, launchexe, leaky IPs, malicious activity, malicious document, malicious link, malware, obfuscation, online pornography, out-of-date software, password-stealers, phishing, privacy, process injection, resource selection, slow connections, smartphones, spyware, third-party risks, two-factor authentication session cookies
github
www.forbes.com 6 hours ago
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16. HN Solving a Million-Step LLM Task with Zero Errors- **Paper Overview**: The research paper "Solving a Million-Step LLM Task with Zero Errors" by Elliot Meyerson et al., submitted to arXiv on November 12, 2025, in the Computer Science > Artificial Intelligence category, presents an advanced method for executing complex tasks involving one million steps using large language models (LLMs) without errors. - **Authors and Affiliation**: The paper's authors include researchers from institutions such as the University of Texas at Austin and the University of Oxford. - **MAKER System Introduction**: The authors introduce MAKER, a system that efficiently completes tasks with over one million LLM steps without errors, employing task decomposition into manageable subtasks handled by microagents for error correction through a voting scheme. - **Massively Decomposed Agentic Processes (MDAPs)**: The paper suggests MDAPs as an effective approach to solving complex problems at large scales by decomposing tasks rather than solely improving existing LLMs. - **Availability and Access**: The full paper is available on arXiv as a PDF, HTML, or TeX source file. Additional resources like associated code, data, and media are provided for further exploration. - **arXivLabs Initiative**: The text mentions arXivLabs, an experimental project facilitating community collaborators to develop new features directly on the site, emphasizing values of openness, community engagement, excellence, and user data privacy. Information about Influence Flowers, CORE Recommender, and links for contacting arXiv, subscribing to mailings, and accessing copyright/privacy policies are also provided. - **Key Contribution**: The paper’s significant contribution lies in demonstrating a novel methodology (MAKER) for achieving zero-error completion of an extremely large task using LLMs, potentially influencing future applications of LLMs in AI for scalable and complex problem-solving. Keywords: #granite33:8b, Artificial Intelligence, Authors, BibTeX, CORE Recommender, Code, Data, DataCite, Error Correction, Influence Flower, LLM Task, Large Language Models, Machine Learning, Media, Microagents, Multiagent Systems, NASA ADS, Paper, Semantic Scholar, Task Solving, Zero Errors, arXivLabs
llm
arxiv.org 7 hours ago
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17. HN Sega Master System Part 2: Mode 4 on the Mark III**Summary:** The provided text discusses the graphics capabilities and configuration of Sega Master System (SMS), focusing primarily on Mode 4, and compares it to its predecessor, the SG-1000, as well as other systems like NES and Genesis. The key aspects addressed include: 1. **Graphics Chip Enhancements:** - SMS graphics chip upgrade from SG-1000's TMS9918A offers mostly compatible but dimmer colors due to a 6-bit RGB palette compared to the predecessor’s 4-bit palette. - Expands on SG-1000 by simplifying software interface, focusing primarily on Mode 4 for development, similar to Genesis/Mega Drive's use of Mode 5. 2. **Video Display Processor (VDP) and Registers:** - VDP communicates through two 8-bit ports: Control/Address/Status ($BF) and Data ($BE). - Access to 11 write-only control registers, one read-only status register, and 16KB VRAM with read/write access; 32 bytes of CRAM (Color RAM) for color data. 3. **VRAM Layout:** - Divided into Pattern Table (512 32-byte characters), Sprite Pattern Table (subset of Pattern Table), Name Table (32x28 grid, 16-bit values from $3800-$3EFF), and Sprite Attribute Table ($3F00-$3FFF). - Uses 64 colors represented as 6-bit RGB values with two 16-color palettes stored in CRAM (Palette 0: $0-$15, Palette 1: $16-$31). 4. **Mode 4 Specifics:** - Includes a read-only status register and eleven write-only control registers. - Unique behaviors due to hardware modifications, such as Register 0 bit 0 always off (sprite magnification), Register 0 bits 2-3 selecting resolution modes (224 or 240 pixels). - Register 1 bits 3 and 4 adjust horizontal resolution, potentially causing overscan issues. 5. **Sprites Configuration:** - Utilize 8x8 pixel tiles with 16 colors per tile, stored in a shared pattern table. - Sprite Attribute Table at the end of VRAM stores Y-coordinates for each of the 64 sprites and their priority settings (background vs foreground). - The system allows for sprite transparency, defined by Color 0, and supports partial visibility through careful coordinate setting. **Key Points Bullet Points:** - **System Enhancements**: - Upgraded graphics chip with more sophisticated but dimmer color palette compared to SG-1000. - Simplified Mode 4 interface for software development. - **VDP Communication and Access**: - Uses two 8-bit ports: Control/Address/Status ($BF) and Data ($BE). - Offers access to control registers (write-only), status register (read-only), VRAM (16KB read/write), and CRAM (32 bytes write-only). - **VRAM Organization**: - Pattern Table: 512 tiles. - Sprite Pattern Table: Subset of Pattern Table. - Name Table: 32x28 grid for background tile definitions. - Sprite Attribute Table: Last 256 bytes for sprite details. - **Mode 4 Specific Features**: - Read-only status register and write-only control registers (11 in total). - Unique behavior due to hardware modifications, affecting sprite size, resolution, and sprite attributes. - **Sprite Management**: - Supports 8x8 pixel tiles with shared pattern tables. - Sprite Attribute Table stores Y-coordinates and priority settings for up to 64 sprites. - Offers transparency (Color 0) and partial visibility through careful coordinate management. Keywords: #granite33:8b, 14-bit address, 16-bit Values, 16KB VRAM, 32 bytes CRAM, 32x28 Grid, 4KB VRAM Limit, 8-bit communication, 8x16 sprite mode, 8×8 sprites, Background Tiles, Bit sets priority, Boot ROM, CRAM, CRAM colors, Cartridge control, Genesis encoding, Global configuration, IRQ, Leftmost column blanking, Master System, Mid-screen interrupts, Mode 4, NES encoding, Name Table, Pattern Table, Programmer reserved bits, Quirk of TMS9918A, RGB, Raster interrupts, Register 9, Relocatable Tables, Scanline display, Scanlines, Sega Documentation, Sega Master System, Shared pattern table, Sprite Attribute Table, Sprite Pattern Table, Sprite mode, System Initialization Code, TMS9918A, Tile Graphics, Tile transparency, Unused bytes, VBLANK interrupts, VDP, VDP registers, VRAM, VRAM layout, Vertical screen expansion, Vertical scroll, Y coordinates, acknowledge interrupts, assembly language, background, background color, bidirectional ports, bitplanes, border color, clear status, compatibility, data blocks, display columns, foreground, graphics chip, graphics modes, horizontal flip, horizontal scroll value, little-endian value, name table width, palette, palette selection, palettes, pixel representation, programming interface, read VRAM, read status, read/write access, register numbers, sample programs, sprite colors, sprite priority, sprite scrolling, status window, system paces, text mode, tile bitplanes, tile number, transparent color, transparent tiles, vertical flip, write control registers, write-only access
vram
bumbershootsoft.wordpress.com 7 hours ago
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18. HN Show HN: PG Slot Notify, Monitor Postgres Slot Growth Directly from Slack- **Tool Overview**: The PG Slot Notify Bot is designed to monitor PostgreSQL replication slots and send alerts through Slack when these slots surpass a specified size limit, preventing potential problems related to disk space or replication lag. - **Requirements**: The bot necessitates a PostgreSQL database and access to a Slack workspace for notifications. - **Setup Procedure**: - Clone the repository containing the bot's code. - Configure the environment variables within the `.env` file, including details such as deployment name, Slack bot token, designated channel, database host and port, user credentials, replication slot name, and check interval (INTERVAL_SECONDS). - **Operation**: - The bot continuously checks the size of the specified replication slots at intervals defined by INTERVAL_SECONDS. - If a slot's size exceeds SIZE_THRESHOLD_MB, it triggers an alert in the designated Slack channel. - **Contribution and Support**: Contributions to improve or adapt the tool are encouraged. For assistance, users can reach out via contact@peerdb.io. BULLET POINT SUMMARY: - Tool: PG Slot Notify Bot monitors PostgreSQL replication slots for size issues. - Access: Requires a Postgres database and Slack workspace access. - Setup: Clone repo, configure .env with deployment name, Slack credentials, DB details, check interval. - Functionality: Checks slot sizes at set intervals; alerts on exceeding a user-defined threshold in Slack. - Community: Open for contributions, support via contact@peerdb.io. Keywords: #granite33:8b, MB, PostgreSQL, Slack notifications, bot, contributions, database name, deployment, disk space, email address, environment variables, host, interval seconds, password, port, replication lag, replication slots, size threshold, support, user
postgresql
github.com 7 hours ago
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19. HN Show HN: SelenAI – Terminal AI pair-programmer with sandboxed Lua tools**Detailed Summary:** SelenaAI is a terminal-based AI pair-programming tool developed in Rust, utilizing a Ratatui user interface that divides interactions into chat, tool activity, and input panes. It prioritizes transparency by streaming the Large Language Model (LLM) output, queuing Lua scripts for manual approval before execution, and logging every session as JSONL files. The AI operates within a sandboxed environment equipped with explicit helpers for secure tasks such as file reading, directory listing, making HTTP requests, and controlled write access. Key features include: - **Transparent Workflow**: Real-time display of conversation, tool invocations, and results facilitates understanding and debugging. - **Pluggable LLMs**: Supports various language models, including offline versions and streaming clients from OpenAI. - **Session History**: Maintains timestamped log directories for review or sharing sessions effectively. - **Lua Ergonomics**: Uses familiar `io.*` APIs and a dedicated `rust` module for writing idiomatic scripts within the Rust ecosystem. - **Open Source**: The MIT-licensed repository encourages community contributions, feedback on desired LLM providers, additional sandbox helpers, and replaying session ideas. **Future Developments** include: - A web viewer for enhanced accessibility. - CLI diff functionality to replay saved sessions interactively. - Log viewers, theming improvements, and Lua helper packs are under development. To use SelenaAI, users need to install Rust toolchain (optional OpenAI API key), clone the repository, choose a configuration via `selenai.toml`, and run using Cargo. Configuration options cover LLM providers, model IDs, streaming settings, write permissions, and log directories, with environment variables for secure handling of sensitive keys like the OpenAI API key loaded from `.env` files. The system executes in a planning-execution-inspection cycle: - **Planning**: Users outline planned edits or tasks in the chat. - **Execution**: Utilizes Lua scripts executed within a sandboxed environment for file operations, calculations, and assumption validations. - **Inspection**: Detailed logs and structured outputs help track tool requests, script executions, and results. The Ratatui interface facilitates interaction with language models: - It comprises three panes: Conversation, Tool Activity, and Input, navigable via keyboard shortcuts. - Users can input plain text directly to the LLM or execute Lua scripts using commands like `/lua |