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Apple isn't just looking to take on Meta in the smart glasses market; it's looking to upend eyewear as a whole, according to Bloomberg's Mark Gurman. When the Apple Watch launched, it wasn't simply competing against the Pebbles and the Motorolas of the world. The company also had Swatch, Fossil, and Seiko in its crosshairs. […]

1. Introduction As the golden standard of secure remote access , the Secure Shell (SSH) protocol has several layers of protection. One of them involves recording and keeping track of the known servers on the client side. known_hosts By default, the known_hosts file for a given user is located at: cat /home/user_name/.ssh/known_hosts github.com ssh-rsa *** github.com ecdsa-sha2-nistp256 *** github.com ssh-ed25519 *** Basically, the file contains a list with several columns, separated by whitespace: Identifying host data Host key type Host key value Optional comment The first column can be hashed or cleartext, depending on the setting of HashKnownHosts in /etc/ssh/ssh_config . When hashed, the first field of each line starts with |1| , a HASH_MAGIC marker. After the latter, the field continues with a random 160-bit string, otherwise known as a salt, followed by a 160-bit SHA1 hash. Each of these is encoded in base64 . The main idea is to hide the IP address or hostname data, which would otherwise be directly visible Either way, known_hosts contains a mapping between a server as identified by its characteristics and its key . ## Known Hosts Checking When connecting to a remote host, SSH checks the known_hosts file of the client to confirm the address or hostname for the server match the key we get from it . If there is a match, the session setup can continue. Otherwise, we get an error. The entry for 192.168.6.66 in the known_hosts file doesn’t match the (Elliptic Curve Digital Signature Algorithm, ECDSA ) key we got back from the server at that address . Critically, if we don’t know what caused the error, we should heed the text in capital letters: something nasty can indeed be happening . On the other hand, the reasons for such an issue can be valid and trivial: dynamic IP address changed hostname reinstalled system reinstalled SSH Docker container misconfigured DHCP relocated client In fact, there can be many more. ## Bypass Known Hosts The error text when connectin

So I have a super busy job and I am by far the fastest out of the 3 others who have the same job as me. Problem is I have enough work where i could literally work 70-80 hours a week and still not catch up. Ive been using Chatgpt and Claude to help with my work load and ive found Claude to be much better for my actualy job duties. But Claudes usage caps kill me. I really need the best AI for basically being a work assitant. I need something that can create spreadsheets, analyze data, read emails, sort thru photos and catalog them. Grok was not really any help, Chatgpt is just meh, but ive found Claude to be the best out of what im looking for but again its usage limits kill me and i cannot afford to pay for the overages. Im already a pro user for chatgpt and claude. What AI can do the things im asking the best for the best price and usage? Most important to my work in order of most important to least: Photo cataloging, analyzing data, spreadsheet creation, and summarizing emails. submitted by /u/JumpyChemistry [link] [留言]

Looking for a local AI solution for film dubbing / audio sync correction (offline if possible). I have a foreign movie with an English audio version, but the video is low resolution and the audio timing slowly drifts out of sync over time. If I manually align it at the start, it gradually becomes offset, so I suspect there are missing/extra segments or timing inconsistencies. What I need is a tool or workflow that can: Listen to the video/audio track Detect dialogue timing Automatically realign or stretch/squeeze audio to match speech in the video Correct drift issues over long duration files (full movies) Online tools often fail due to file size/length limits, so I’m specifically looking for local software or AI models that can run on a PC . Any suggestions for tools, pipelines, or approaches appreciated. submitted by /u/dotmerlin [link] [留言]

Stepping up to give my first-ever presentation at UbuCon 2026 was a massive milestone, and honestly, it was pretty intimidating. The stakes felt high, especially with the live demo. It was a race against the clock to get everything running, and it only finally came together exactly ten minutes before I went on stage. Talk about a close call. While I am proud of what I delivered, I originally wanted to pack even more into the session. I had planned to showcase a simulated mission, Gazebo visualizations and RViz path simulations. While time caught up with me for the presentation, these features are still actively in the works over at the aeronix project. My goal is to have the entire end-to-end setup completed and ready by the end of the year. I connected with some incredible engineers and industry peers and I am looking forward to building on those conversations for future professional collaborations. This experience proved that the best way to grow is to just put yourself out there. Moving forward, I plan to keep speaking on topics that challenge me. It is the ultimate way to deepen my own technical understanding share what I have learned with the community and grow professionally.

A physiotherapist asked me a simple question a couple of months ago: "Can you build something to run my whole clinic?" So I did — solo, in about a week. Here's the full 2.5-minute walkthrough 👇 What PhysioFlow does PhysioFlow runs an entire physiotherapy clinic from one screen — built for India (₹, GST, WhatsApp, +91): Dashboard — attendance, collections & pending bookings at a glance Patient files — recharge session packs, track usage, auto-generate GST-ready bills Attendance in seconds with a QR scan Online bookings that convert straight into a patient file Reports — daily ledger, revenue, CSV/PDF export Patient portal — patients see their own sessions & prescriptions The stack Next.js + Supabase + TypeScript — multi-tenant, with row-level security so no clinic's data ever leaks to another. Try it Live now with a 14-day free trial, no card needed → https://physioflow.devfrend.com I'm Amar, a full-stack & AI engineer. I design and build products like this end-to-end. I'm open to work — SaaS builds, MCP servers, LLM apps & automation. Reach me on LinkedIn .

This is a submission for the Hermes Agent Challenge , under the Write About Hermes Agent prompt. I've spent the last week testing AI memory failure modes in a public evaluation harness. That work changed how I read agent memory systems. This is a writing submission, not a build submission. I did not build a Hermes Agent project for this challenge. I am writing from the perspective of someone testing how memory failures show up once agents can act. So when I look at Hermes Agent, the question I care about is not only: Can the agent remember useful things? The harder question is: When memory conflicts, which memory is allowed to govern the agent's action? That distinction matters. Hermes Agent is interesting because it is not just a chat interface. Its documentation describes an open-source agentic system with tool use, project context, persistent memory, skills, browser automation, checkpoints, delegation, scheduled tasks, and multiple memory providers. That is exactly the kind of system where memory stops being a convenience feature and starts becoming part of the agent's operating boundary. If an agent can run tools, edit files, browse, delegate work, schedule tasks, and remember across sessions, then memory is no longer just "context." Memory becomes governance. The Memory Problem I Would Watch For In a simple chatbot, bad memory is annoying. In an agent, bad memory can become operational. The failure mode is not only that the agent forgets something. Sometimes the more dangerous failure is that it remembers the wrong thing too confidently. A memory can be: relevant but stale, relevant but low-authority, relevant but superseded, relevant but only context, relevant but not allowed to determine the action. That is the distinction my own tests kept running into. Retrieval systems are usually good at answering: What memory is closest to the user's request? But safety often depends on a different question: What memory is allowed to decide what the agent should do? Thos

Environmental activist Erin Brockovich has a new mission.

Overview I built Hermes Financial Agent — an AI-powered financial assistant for investors in the Egyptian Exchange (EGX). The goal: not just calculate portfolio value, but explain risks in a transparent, auditable way. Features Real EGX market data via Yahoo Finance Portfolio tracking and valuation Daily financial reports Telegram-user portfolio isolation Cached quote fallback for resilience Explainable risk insights Explainable Risk Intelligence Unlike traditional trackers, Hermes surfaces: Portfolio concentration risk Stale market data exposure Quote coverage percentage Valuation gaps from unavailable data Users understand confidence level behind their valuation — not just the number. Technical Stack Hermes Agent framework Python GitHub Actions (automated smoke testing) Offline-safe quote fallback architecture Repository 🔗 GitHub Repository Future Roadmap News sentiment analysis Investment thesis tracking Market briefing generation Advanced financial reasoning agents hermeschallenge

submitted by /u/TheOnlyVibemaster [link] [留言]

NVIDIA's CEO Jensen Huang is set to take the stage for his GTC Taipei keynote at 8PM PT / 11PM ET. You can watch all the announcements here and embedded below. Rumors have been flying about what to expect from today's presentation, but the big one is the possibility of a partnership with Microsoft and […]

submitted by /u/Raman606surrey [link] [留言]

The A Minecraft Movie sequel officially has a title: A Minecraft Movie Squared. What's more, we now know that Kirsten Dunst will star as Alex, the game's female character option, and that Matt Berry is set to play an even bigger role in this film. He voiced Nitwit in the first movie, but in this […]

submitted by /u/InvestigatorSoft5764 [link] [留言]

At what point did your memory layer become the least trusted part of your stack? Mine wasn't retrieval. It was realizing I had no idea which memories were still true. submitted by /u/riddlemewhat2 [link] [留言]

This is a submission for the Hermes Agent Challenge : Write About Hermes Agent Hello, DEV friends! 👋 If you have been exploring the world of Artificial Intelligence lately, you have probably heard a lot of buzz about "AI Agents." But what does it actually feel like to build with one? Today, I want to share my personal experience working with Hermes Agent . I used it to build a smart assistant called the Alpha-Dairy Quant Pipeline —a system that helps track and make sense of food market data. ( https://github.com/HopeBestWorld/alpha-dairy-pipeline ) Whether you are an expert coder or just curious about AI, I hope this friendly guide inspires you to try building an agent of your own! What is Hermes Agent, Anyway? Think of a standard AI as a helpful chatbot that answers questions when you ask them. An AI Agent , on the other hand, is more like a proactive assistant. You give it a big goal, and it sits down, makes a step-by-step plan, uses digital tools, runs code, and checks its own work until the job is done. For my project, I wanted to track market prices for three major dairy products: Cheddar Blocks, Butter, and Dry Whey. Instead of doing all the math and graphing by myself, I let Hermes Agent take the wheel. The Magic of Multi-Step Reasoning The coolest part of working with Hermes Agent is watching it "think". When I asked my agent to look at our data database ( market_intelligence_3.db ) and find the best trading strategy,it followed a beautiful planning loop: Checking the Files: It looked at our setup files ( tickers.yaml and requirements.txt ) to make sure all its tools were ready. Running the Math: It triggered a Python program ( backtest_engine.py ) to study weekly market history. Making Decisions: It realized that Dry Whey was way too wild and risky to trade right now, so it intelligently gave it a 0% safety rating and put the focus on Cheddar and Butter instead. Drawing and Sharing: It automatically drew a beautiful performance chart ( backtest_analysis.png

The YouTube-to-prestige-horror pipeline is looking very strong.

Every MCP server you run locally executes with your full filesystem and network permissions. That means the GitHub MCP server, the Slack one, that third-party tool you installed from npm last week — all of them can read your SSH keys, .env files, and credential stores by default. Anthropic just open-sourced the fix: sandbox-runtime , the sandboxing layer they built for Claude Code. One-line wrap, no Docker, OS-level enforcement. What actually changed srt (the Sandbox Runtime CLI) enforces filesystem and network restrictions on any process using native OS primitives: macOS : Uses sandbox-exec with dynamically generated Seatbelt profiles Linux : Uses bubblewrap for containerization + network namespace isolation Network filtering : HTTP/HTTPS traffic routes through an HTTP proxy; other TCP goes through SOCKS5 — both enforce your domain allowlists Install it: npm install -g @anthropic-ai/sandbox-runtime Wrap an MCP server in your .mcp.json — change command from npx to srt , move the rest to args : { "mcpServers" : { "filesystem" : { "command" : "srt" , "args" : [ "npx" , "-y" , "@modelcontextprotocol/server-filesystem" ] } } } Then configure what the process is actually allowed to touch in ~/.srt-settings.json : { "filesystem" : { "denyRead" : [ "~/.ssh" ], "allowWrite" : [ "." ], "denyWrite" : [ "~/sensitive-folder" ] }, "network" : { "allowedDomains" : [ "api.github.com" , "*.npmjs.org" ] } } The result: the MCP server can work in your project directory, talk to the domains it needs, and nothing else. Why this matters The threat model is real. An MCP server running compromised code — or simply a server with more ambient access than it needs — can exfiltrate your SSH keys, read your .env files, or phone home to arbitrary hosts. This isn't theoretical; it's the same class of supply-chain risk that exists for any untrusted npm package, except MCP servers are typically long-running processes with broad system access. srt is designed secure-by-default : processes start wit

This is a submission for the Hermes Agent Challenge : Build With Hermes Agent The Problem Nobody Talks About Every time the Reserve Bank of India publishes a circular, somewhere inside an Indian bank, a compliance officer opens a PDF. They read it. They try to figure out what it means for their institution specifically. They write a summary email. They forward it to five department heads. They chase those department heads for two weeks to confirm it's been actioned. They build a spreadsheet to track all of this. And then the next circular drops and the cycle starts again. RBI publishes hundreds of circulars a year. SEBI publishes more. MCA publishes more still. Compliance teams at Indian banks are drowning — not because they're incompetent, but because the volume of regulatory output has outpaced any reasonable human ability to track it manually. The fine for missing a deadline isn't a polite reminder. It's a penalty notice. This is the problem I built for. What I Built RBI Regulatory Digest Agent — an autonomous multi-step agent powered by Hermes Agent that monitors RBI and SEBI publication feeds, reads every new circular, extracts structured action points from the regulatory text, and delivers a formatted intelligence report to compliance teams automatically. No human reads the circular first. No human decides what's important. No human routes it to the right department. The agent does all of that. The pipeline RBI/SEBI feeds → new circular detected → full text extracted → LLM analysis → structured action points → risk classification → HTML dashboard generated → email delivered Every action point extracted contains: What needs to be done — specific and actionable, not a vague summary Deadline — parsed from the circular text Responsible department — Credit, Compliance, Treasury, Operations, IT, Legal Evidence required — what documentation confirms completion Priority — Critical (overdue or <7 days), High, Medium, Low From a new circular to a structured compliance b

Error: Cannot Set Headers After They Are Sent to the Client If you've built APIs with Express for any length of time, you've probably seen this error: Error [ ERR_HTTP_HEADERS_SENT]: Cannot set headers after they are sent to the client Or: Cannot set headers after they are sent to the client The frustrating part is that the application often works for some requests and fails only under specific conditions. This error is almost always caused by sending multiple responses for the same request. Let's break down why it happens and how to prevent it in production code. Problem Consider this Express route: app . get ( " /users/:id " , ( req , res ) => { if ( ! req . params . id ) { res . status ( 400 ). json ({ error : " User ID required " }); } res . json ({ id : req . params . id }); }); Looks harmless. But if the first response is sent, Express continues executing the remaining code. Result: Error [ ERR_HTTP_HEADERS_SENT]: Cannot set headers after they are sent to the client The server attempts to send two responses for a single request. HTTP doesn't allow that. Why It Happens A request can only receive one response. Once Express sends: res . send (); or res . json (); or res . redirect (); or res . end (); the HTTP headers are already transmitted. Any attempt to modify headers or send another response will trigger the error. In production systems, this usually happens because of: Missing return statements Multiple async operations Duplicate error handling Middleware issues Promise and callback mixing Race conditions Example Missing Return Statement This is the most common cause. app . get ( " /profile " , ( req , res ) => { if ( ! req . user ) { res . status ( 401 ). json ({ error : " Unauthorized " }); } res . json ( req . user ); }); If req.user is missing: res . status ( 401 ). json (...) runs first. Then: res . json ( req . user ) runs immediately afterward. Two responses. One request. Crash. Correct Version app . get ( " /profile " , ( req , res ) => { if ( ! req