This article discusses why larger Meshtastic networks may benefit from switching from the default LongFast LoRa preset to higher bandwidth options like MediumSlow, MediumFast, ShortSlow, or ShortFast, detailing the trade-offs between range, speed, and reliability.
A repository containing extracted system prompts and tools for various AI models including FULL v0, Cursor, Manus, Same.dev, Lovable, Devin, Replit Agent, Windsurf Agent, and VSCode Agent. It offers insights into the structure and functionality of these models and includes a security notice for AI startups.
This article details a schema-grounded approach to Conversational User Interface (CUI) development using OpenCUI, focusing on declaring schemas, attaching interaction and language annotations, and leveraging statecharts for efficient dialog management. It emphasizes building CUIs around backend service APIs.
Bethere.ai: The author introduces bethere.ai, a platform built to natively support both flows and state machines for building hybrid conversational experiences.
SWE-agent is an agent that uses a language model (like GPT-4) to automatically fix GitHub issues, perform web tasks, solve cybersecurity challenges, or execute custom tasks through configurable agent-computer interfaces.
SWE-agent is an open-source tool that utilizes large language models (LLMs) like GPT-4o and Claude Sonnet 3.5 to autonomously fix bugs in GitHub repositories, solve cybersecurity challenges, and perform complex tasks. It features a mode called EnIGMA for offensive cybersecurity and prioritizes simplicity and adaptability.
This article details building a Retrieval-Augmented Generation (RAG) system to assist with research paper tasks, specifically question answering over a PDF document. It covers document loading, splitting, embedding with Sentence Transformers, using ChromaDB as a vector database, and implementing a query interface with LangChain.
Datadog has acquired Metaplane to expand its data observability offerings, particularly for AI applications. Metaplane uses AI-powered anomaly detection and data lineage tracking. The acquisition aims to unify observability across applications and data.
Two top CISA officials, Bob Lord and Lauren Zabierek, have resigned citing their work on the Secure by Design program, coinciding with White House cuts and a potential shift in the program’s direction. The agency faces significant budget cuts and staff reductions.
"TL;DR: We unify over 23 methods in contrastive learning, dimensionality reduction, spectral clustering, and supervised learning with a single equation."
"As the field of representation learning grows, there has been a proliferation of different loss functions to solve different classes of problems. We introduce a single information-theoretic equation that generalizes a large collection of mod- ern loss functions in machine learning. In particular, we introduce a framework that shows that several broad classes of machine learning methods are precisely minimizing an integrated KL divergence between two conditional distributions: the supervisory and learned representations. This viewpoint exposes a hidden information geometry underlying clustering, spectral methods, dimensionality re- duction, contrastive learning, and supervised learning. This framework enables the development of new loss functions by combining successful techniques from across the literature. We not only present a wide array of proofs, connecting over 23 different approaches, but we also leverage these theoretical results to create state-of-the-art unsupervised image classifiers that achieve a +8% improvement over the prior state-of-the-art on unsupervised classification on ImageNet-1K. We also demonstrate that I-Con can be used to derive principled debiasing methods which improve contrastive representation learners."
