#jupyter_notebook
SAM 2 is a powerful new AI model that can quickly and accurately separate objects in both images and videos, even if it has never seen them before. It works in real-time, allowing you to select objects with simple prompts like clicks or boxes and refine the results interactively. This makes tasks like video editing, object tracking, and image annotation much easier and faster. SAM 2’s ability to handle complex scenes and track objects smoothly across video frames helps improve creativity and productivity in many fields, from media production to computer vision research. It is open-source and easy to use with Python and PyTorch.
https://github.com/facebookresearch/segment-anything
I Built a Mesh Network Across the World | Data Slayer
That escalated quickly...
In my last video, I introduced #Reticulum—an open-source protocol that could allow anyone to build networks without relying on traditional internet infrastructure. But there was one big question left unanswered: how far can it actually go?
In this video, I start with a simple setup inside my house and begin pushing the limits—testing communication across rooms, neighborhoods, and beyond using WiFi HaLow and #mesh networking. The goal is simple: see if it’s possible to send real messages across distance without depending on ISPs, centralized servers, or the internet as we know it.
#Network#MeshNetwork
The Internet, Reinvented.
In this video, I build a #Reticulum#RNode and prove that completely different radios — #LoRa and Wi-Fi — can communicate through a hardware-agnostic networking stack. Reticulum routes traffic above the radio layer, automatically bridging dissimilar frequencies, interfaces, and modulation types. I then run it over Wi-Fi HaLow Haven nodes to create a long-range, encrypted IP #mesh with no traditional infrastructure.
Finally, I push it further by running #ATAK across the network, demonstrating a fully open-source, decentralized communication stack in action.
Checkout https://rmap.world/
You can install rnode software on your esp32/nrf52 based meshtastic/meshcore hardware