Curated AI/ML/DL research papers for researchers, analysts, academics, hackers, and tech professionals.
Scout-Edge is a lightweight, extensible toolkit for real-time trend tracking across multiple data sources
Future Signals 2026: The Architecture of Intent — AI strategy report by Design Thinking Japan. Five signals reshaping enterprise AI: agents, sovereign AI, programmable biology, spatial intelligence, the human premium. 390+ references.
Living tracker of the AI ecosystem — quantum computing research, AI summits, Silicon Valley updates, tool releases, and industry trends
AI Intelligence Hub - Track 14 AI sources (GitHub, HuggingFace, MCP, Claude Code, Anthropic Skills & Cookbooks) with full-text search and keyword scoring. Port 4444.
Interactive dashboard to track AI & Robotics research trends using arXiv API and Streamlit (2021-2025)
A comprehensive round-up of the latest AI and Machine Learning developments across various industries.... | View more at LaravelMail.com
Future Signals 2025 — AI trend forecasting report by Design Thinking Japan. 85% directional accuracy. Covers AI agents, autonomous partnerships, immersive reality, and biological interactions. Tokyo-based AI research.
A curated collection of trending open-source AI projects, tools, skills, agents, and experiments — updated for builders who don't want to miss what's next.
Exploring the future directions of Artificial Intelligence in Software Engineering — emerging trends, transformative capabilities, ethical considerations, automation workflows, and the long-term evolution of intelligent development ecosystems. Week 6 assignment for AI-driven software engineering learning track.
[Breaking Into Tech] Interactive Power BI dashboard analyzing 49,000+ responses from the 2025 Stack Overflow Developer Survey. Insights on AI adoption, compensation trends, and learning pathways.
Structured AI trend feed for autonomous agents — curated from 14+ sources, synthesized via LLM Counsel, published every 6h as JSON Feed, RSS, and llms.txt
Tracking State-of-the-Art AI Models and Performance is an open-source dataset documenting AI advancements from the 1950s to today. It includes model details, organizations, compute requirements, and benchmarks. Researchers and developers can analyze trends, compare models, and contribute updates. The dataset is open for collaboration $ fostering AI
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