NeoServer SSH Mosh Terminal vs Tensor Camera

NeoServer manages your servers over SSH, with no extra software to install. Whether it's a Home Server, NAS, cloud server, development environment, or AI compute node, you can connect, monitor, manage files, and operate containers directly through NeoServer. ◉ Terminal and Remote Access • Mosh support — stays connected when switching networks • Deep tmux and zellij support for fast session recovery after disconnects • ZMODEM (rz/sz) file transfer — send and receive files right in the terminal • Built for Claude Code, with direct paste or upload of images, videos, and files • Password, Private Key, 2FA, and SSH Agent forward authentication • Jump Server, Failover, and Socks5 Proxy support • Automatically run Shell initialization scripts after connecting • Built-in special keyboard, copy and paste, and quick actions • Command completion hints, with double-tap to trigger TAB • Custom themes and fonts, including programming ligature fonts ◉ AI Assistant No Agent installation required. Manage your servers directly with AI: it can read metrics, run commands, and manage files — like an always-on operations assistant that helps you handle complex maintenance tasks. • Supports mainstream LLM APIs via standard protocols. No model service is included — bring your own API configuration for any provider you need • Custom Skills system: AI can read and create skills, synced across devices via iCloud • Built-in browser skill: AI can open web pages, extract content, and run scripts in-app • Local file sandbox: AI can read and write local files with live preview • Runs continuously in the background, with automatic notifications when tasks complete • Upload images, screenshots, and files for AI to analyze in context • Plan mode: plan first, then execute — more control over complex tasks ◉ File Management (SFTP) • Browse server files and directories • Upload, download, delete, and rename files • View file size, permissions, and modification time • Edit files online • Syntax highlighting for common programming languages • Preview images, logs, configuration files, and more ◉ Batch Script Execution • Run scripts on one or multiple servers • Organize servers into groups • View script execution history • Run maintenance tasks in batches at once • Suitable for batch updates, deployments, and inspections ◉ Server Monitoring View server status in real time: • Uptime • 1 / 5 / 15 minute system load • CPU model, temperature, and usage • Memory usage • GPU usage and GPU task information • Disk capacity, IOPS, and I/O Wait • Disk read/write speed and total read/write volume • Network upload and download speed • Total traffic statistics Key metrics can also be shown directly in iOS widgets. ◉ Process Management • View the system process list • Show PID, user, CPU, memory usage, and more • Sort by columns • Send signals to terminate processes ◉ Docker and Podman Management • View container status • View container logs • View Inspect information • Create, start, stop, and restart containers • Pause and delete containers • Manage images and container resources ◉ Remote Wake and Automation • Wake-on-LAN (WOL) remote startup • Remote shutdown and daily operations support ◉ Security and Data Sync • Face ID / Touch ID app protection • Sync data with your private iCloud storage ◉ Who NeoServer Is For • Home Server enthusiasts • NAS users (Synology, QNAP, TrueNAS, and more) • Website administrators and operations engineers • Developers and programmers • AI model researchers • Cloud server administrators ◉ Feedback and issues: makerneo.lab@gmail.com ◉ Data Privacy: ◦ Your private data — such as SSH private keys and server configurations — is stored only on your device and your own iCloud storage (if you enable sync). It is never uploaded to our servers or shared with any third party. ◦ Privacy Policy: https://www.makerneo.com/en/doc/neoserver-privacy.html ◦ Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

Introducing our innovative Tensor Camera App, designed to streamline the process of testing and evaluating newly trained models in real-world scenarios. Our app seamlessly integrates with Python servers, providing a user-friendly interface to send camera feeds for instant predictions. Real-time Camera Feed: Capture live camera feeds directly within the app for immediate processing by your Computer Vision models. Whether you're testing object detection, image classification, or any other task, our app delivers real-time results. Python Server Integration: Connect effortlessly with Python servers to leverage the power of your trained models. Our app sends captured images to the server for prediction, ensuring smooth communication and seamless testing. Prediction Display: Receive predictions in real-time, displayed within the app interface. Visualize the model's output directly on your device screen, allowing for quick validation and analysis of results. User-Friendly Interface: Enjoy a seamless user experience with our intuitive and easy-to-navigate interface. Whether you're a seasoned developer or new to Computer Vision testing, our app makes the process accessible to all skill levels. Steps to Use: -Download and install the app from the respective app store on your device. -Go to my GitHub Repository from the App and learn how to set up the server. -Launch the app and configure settings such as server connection details and model selection. -Position your camera to capture the desired scene or object for testing. -Initiate the camera feed within the app and observe real-time predictions generated by your Computer Vision model. -Analyze and evaluate the model's performance based on the displayed predictions. -Optionally, adjust settings or switch to a different model for further testing. Experience the future of Computer Vision testing with our cutting-edge app. Whether you're a researcher, developer, or enthusiast, our app empowers you to test and iterate on your models with ease and efficiency.