IBM has introduced Granite 4.0 3B Vision, a specialized vision-language model (VLM) engineered for high-fidelity enterprise document data extraction. Unlike monolithic multimodal models, this release uses a modular LoRA adapter architecture, adding approximately 0.5B parameters to the Granite 4.0 Micro base model. This design allows for efficient dual-mode deployment, activating vision capabilities only when multimodal processing is required. The model excels at converting complex visual elements, such as charts and tables, into structured machine-readable formats like JSON, HTML, and CSV. By utilizing a high-resolution tiling mechanism and a DeepStack architecture for improved spatial alignment, Granite 4.0 3B Vision achieves impressive accuracy in tasks like Key-Value Pair extraction and chart reasoning, ranking highly on industry benchmarks.
This guide helps engineers build and ship LLM products by covering the full technical stack. It moves from core mechanics (tokenization, embeddings, attention) to training methodologies (pretraining, SFT, RLHF/DPO) and deployment optimizations (LoRA, quantization, vLLM). The focus is on managing critical production tradeoffs between accuracy, latency, memory, and cost
A gateway that bridges Meshtastic mesh radios and Iridium SBD satellite modems. Send messages between off-grid mesh networks and global satellite coverage from a single box.
This research introduces Doc-to-LoRA (D2L), a method for efficiently processing long documents with Large Language Models (LLMs). D2L creates small, adaptable "LoRA" modules that distill key information from a document, allowing the LLM to answer questions without needing the entire document in memory. This significantly reduces latency and memory usage, enabling LLMs to handle contexts much longer than their original capacity and facilitating faster knowledge updates.
Stridetastic is an open-source monitoring and observability framework for Meshtastic® LoRa mesh networks. It helps operators capture, inject, and visualize mesh network data.
Information about Meshtastic, an open-source, decentralized, off-grid mesh network, and the MDARC's involvement with it, including node locations and configurations.
A terminal interface for chatting via Meshtastic mesh networks with real-time message display, node discovery, and radio configuration.
A Pygame-based Meshtastic / LoRa node visualizer for offline SIGINT and field research, reading live serial data to display GPS positions, mesh links, and signal reach in real time.
Arduino has released the Nesso N1, a compact IoT controller built around the ESP32-C6 RISC-V microcontroller, featuring Wi-Fi 6, Thread, LoRa, a touch display, and multiple sensors for rapid prototyping and portable embedded applications.
LILYGO has announced a raft of new microcontroller development boards targeting different niches: a low-frequency LoRa board, an ultra-widescreen display board, a LoRa-equipped ePaper display board, and a CAN bus board. The boards are powered by the Espressif ESP32-S3 microcontroller.
