# Verified Sources Directory — highsignal.sh Every story published on highsignal.sh is grounded in verified, tier-ranked primary sources. ### [AI Snake Oil (Princeton)](https://www.aisnakeoil.com/feed) - **Type**: Research - **Description**: Critical analyses of AI capabilities vs claims by Princeton researchers Arvind Narayanan and Sayash Kapoor. ### [AWS Machine Learning Blog](https://aws.amazon.com/blogs/machine-learning/feed/) - **Type**: Lab - **Description**: Cloud ML infrastructure, foundation models, and distributed training systems. ### [Alignment Forum](https://www.alignmentforum.org/feed.xml) - **Type**: Research - **Description**: Technical research, mathematical formalisms, and discussions on AI safety and alignment. ### [Andrej Karpathy](https://karpathy.bearblog.dev/feed/) - **Type**: Research - **Description**: Engineering notes, neural networks, and educational deep dives. ### [ArXiv CS.AI](https://rss.arxiv.org/rss/cs.AI) - **Type**: Research - **Description**: Open preprints in artificial intelligence from arXiv. ### [ArXiv CS.CL (Computation and Language)](https://rss.arxiv.org/rss/cs.CL) - **Type**: Research - **Description**: Open preprints in computation and language from arXiv. ### [ArXiv CS.LG (Machine Learning)](https://rss.arxiv.org/rss/cs.LG) - **Type**: Research - **Description**: Open preprints in machine learning from arXiv. ### [Ars Technica AI](https://arstechnica.com/tag/ai/feed/) - **Type**: Research - **Description**: In-depth technical reporting on generative models, compute, and AI policy. ### [Astral Codex Ten (AI)](https://www.astralcodexten.com/feed) - **Type**: Research - **Description**: Long-form essays analyzing frontier AI progress, reasoning models, and existential risk. ### [Berkeley AI Research (BAIR)](https://bair.berkeley.edu/blog/feed.xml) - **Type**: Research - **Description**: Academic AI research and foundational breakthroughs from UC Berkeley. ### [Center for AI Safety](https://cais.substack.com/feed) - **Type**: Research - **Description**: Empirical research benchmarks, safety metrics, and risk evaluations from CAIS. ### [Chip Huyen](https://huyenchip.com/feed.xml) - **Type**: Research - **Description**: Machine learning systems design, post-training, and AI application engineering. ### [EleutherAI Blog](https://blog.eleuther.ai/index.xml) - **Type**: Research - **Description**: Non-profit research collective advancing open-science foundation models and interpretability. ### [Eugene Yan](https://eugeneyan.com/rss/) - **Type**: Research - **Description**: Applied ML systems, LLM patterns, evals, and production architectures. ### [Georgetown CSET](https://cset.georgetown.edu/feed/) - **Type**: Research - **Description**: Data-driven research on AI governance, compute supply chains, and safety policy. ### [Google DeepMind](https://deepmind.google/blog/rss.xml) - **Type**: Lab - **Description**: AI research and scientific applications. ### [Google Keyword (AI)](https://blog.google/technology/ai/rss/) - **Type**: Lab - **Description**: Official AI research breakthroughs, Gemini updates, and model releases from Google. ### [Hacker News (AI Discussions)](https://news.ycombinator.com/front) - **Type**: Community - **Description**: Technical discussion. Comments are opinion, not verified reporting. ### [Hamel Husain](https://hamel.dev/index.xml) - **Type**: Research - **Description**: Pragmatic, anti-hype guides to fine-tuning, evals, and shipping LLMs. ### [Hugging Face Blog](https://huggingface.co/blog/feed.xml) - **Type**: Research - **Description**: Open-source models, datasets, and tools. ### [IEEE Spectrum AI](https://spectrum.ieee.org/feeds/topic/artificial-intelligence.rss) - **Type**: Research - **Description**: Engineering and computing breakthroughs from the global IEEE engineering community. ### [Jack Clark (Import AI)](https://importai.substack.com/feed) - **Type**: Research - **Description**: Weekly technical reviews of AI research papers, compute, and policy. ### [Jacob Steinhardt (Bounded Regret)](https://bounded-regret.ghost.io/rss/) - **Type**: Research - **Description**: Foundational essays on machine learning safety, forecasting, and alignment from UC Berkeley. ### [Jay Alammar](https://jalammar.github.io/feed.xml) - **Type**: Research - **Description**: Visual and intuitive explainers for transformers, LLMs, and neural networks. ### [Johann Rehberger (Embrace The Red)](https://embracethered.com/blog/index.xml) - **Type**: Research - **Description**: Offensive security research, prompt injection, and LLM red-teaming. ### [Last Week in AI](https://lastweekin.ai/feed) - **Type**: Research - **Description**: Weekly curated synthesis of significant research papers, industry releases, and policy news. ### [Latent Space](https://www.latent.space/feed) - **Type**: Research - **Description**: Technical newsletter and podcast covering AI engineering and agents. ### [Lilian Weng (Lil'Log)](https://lilianweng.github.io/index.xml) - **Type**: Research - **Description**: In-depth literature reviews on reasoning, agents, safety, and foundation models. ### [MIT AI News](https://news.mit.edu/rss/topic/artificial-intelligence2) - **Type**: Lab - **Description**: Campus research news on artificial intelligence from MIT. ### [MIT Technology Review AI](https://www.technologyreview.com/topic/artificial-intelligence/feed/) - **Type**: Research - **Description**: Rigorous journalism analyzing the technical, social, and commercial impact of AI. ### [Marcus on AI (Gary Marcus)](https://garymarcus.substack.com/feed) - **Type**: Research - **Description**: Skeptical analysis of generative AI limitations, reasoning failures, and neurosymbolic alternatives. ### [Max Woolf (minimaxir)](https://minimaxir.com/index.xml) - **Type**: Research - **Description**: Experiments, benchmarks, and creative engineering with generative models. ### [Microsoft Research AI](https://www.microsoft.com/en-us/research/blog/feed/) - **Type**: Lab - **Description**: Frontier research in foundation models, reasoning, and multi-agent systems. ### [Mitchell Hashimoto](https://mitchellh.com/feed.xml) - **Type**: Research - **Description**: Explorations in local LLM inference, Claude Code, and developer workflows. ### [Nathan Lambert (Interconnects)](https://www.interconnects.ai/feed) - **Type**: Research - **Description**: RLHF, reasoning models, post-training, and open-weight model analysis. ### [Nature Machine Learning](https://www.nature.com/subjects/machine-learning.rss) - **Type**: Lab - **Description**: Peer-reviewed scientific breakthroughs across neural networks and machine intelligence. ### [One Useful Thing (Ethan Mollick)](https://www.oneusefulthing.org/feed) - **Type**: Research - **Description**: Empirical experiments and real-world observations on working with generative AI. ### [OpenAI News](https://openai.com/news/rss.xml) - **Type**: Lab - **Description**: Model releases, product updates, and research. ### [Reddit r/LocalLLaMA](https://www.reddit.com/r/LocalLLaMA/.rss) - **Type**: Community - **Description**: Open-weight models, local inference runtimes, and quantization engineering discussions. ### [Reddit r/MachineLearning](https://www.reddit.com/r/MachineLearning/.rss) - **Type**: Community - **Description**: Community discussion, paper announcements, and practitioner debates. Requires primary corroboration. ### [Replicate Blog](https://replicate.com/blog/rss) - **Type**: Research - **Description**: Open-source machine learning models, inference performance, and developer patterns. ### [Sebastian Raschka](https://sebastianraschka.com/rss_feed.xml) - **Type**: Research - **Description**: Architectural deep-dives, PyTorch implementations, and foundation model benchmarks. ### [SemiAnalysis](https://semianalysis.com/feed) - **Type**: Research - **Description**: Detailed teardowns of AI accelerators, semiconductor nodes, datacenter clusters, and compute costs. ### [Simon Willison](https://simonwillison.net/atom/everything/) - **Type**: Research - **Description**: Hands-on LLM engineering, prompt injection research, and developer tools. ### [Simon Willison (Bluesky)](https://bsky.app/profile/simonwillison.net/rss) - **Type**: Research - **Description**: Hands-on LLM engineering notes and links from Simon Willison. ### [Synced Review](https://syncedreview.com/feed/) - **Type**: Research - **Description**: Global artificial intelligence news, technical breakthroughs, and paper reviews. ### [TechCrunch AI](https://techcrunch.com/category/artificial-intelligence/feed/) - **Type**: Research - **Description**: Startup and industry coverage of artificial intelligence. ### [The Gradient](https://thegradient.pub/rss/) - **Type**: Research - **Description**: Rigorous essays and perspectives written by AI researchers and practitioners. ### [The Verge (AI)](https://www.theverge.com/rss/index.xml) - **Type**: Research - **Description**: Technology news and analysis. ### [Tim Dettmers](https://timdettmers.com/feed/) - **Type**: Research - **Description**: Quantization research (QLoRA, bitsandbytes), GPU hardware, and memory bandwidth. ### [Together AI Blog](https://www.together.ai/blog/rss.xml) - **Type**: Research - **Description**: Inference acceleration, distributed training kernels, and open-weight model deployment. ### [Understanding AI](https://www.understandingai.org/feed) - **Type**: Research - **Description**: Timothy B. Lee's deep-dive explanations of how modern AI systems actually work. ### [Vicki Boykis](https://vickiboykis.com/index.xml) - **Type**: Research - **Description**: Practical systems engineering, embeddings, and data architectures. ### [Weaviate Blog](https://weaviate.io/blog/rss.xml) - **Type**: Research - **Description**: Vector databases, semantic retrieval, RAG architectures, and multimodal embeddings. ### [Wired AI](https://www.wired.com/feed/tag/ai/latest/rss) - **Type**: Research - **Description**: Authoritative reporting on artificial intelligence, hardware, and industry shifts. ### [X - OpenAI Announcements](https://x.com/OpenAI) - **Type**: Community - **Description**: Official announcements from OpenAI on X. ### [fast.ai](https://www.fast.ai/index.xml) - **Type**: Research - **Description**: Practical deep learning research and democratization of AI.