https://nosible.com/blog 2026-07-16T10:31:25.000Z https://nosible.com/blog/tag/classification 2026-06-18 https://nosible.com/blog/tag/cybernaut-1 2025-08-26 https://nosible.com/blog/tag/faceted-search 2025-10-16 https://nosible.com/blog/tag/geopolitical-risk 2026-06-06 https://nosible.com/blog/tag/knowledge-graphs 2026-07-16T10:31:25.000Z https://nosible.com/blog/tag/nosible-world 2026-07-16T10:31:25.000Z https://nosible.com/blog/tag/quantitative-strategy 2026-06-16 https://nosible.com/blog/tag/research 2026-07-16T10:31:25.000Z https://nosible.com/blog/tag/sentiment 2025-12-12 https://nosible.com/blog/tag/signals 2025-12-12 https://nosible.com/blog/tag/technical 2026-06-18 https://nosible.com/blog/tag/trade-policy 2026-06-17 https://nosible.com/blog/tag/vector-search 2024-01-21 https://nosible.com/blog/point-in-time-knowledge-graphs-over-named-entities 2026-07-16T10:31:25.000Z https://nosible.com/images/2026/07/kg-hero-decade.png Point-in-Time Knowledge Graphs over Named Entities with NOSIBLE World Build point-in-time knowledge graphs from dated NOSIBLE World events using named entities and lift-scored co-mentions—without lookahead bias. https://nosible.com/blog/the-contrastive-geometry-of-risk 2026-06-18 https://nosible.com/images/2026/06/walkthrough_step9_number_line.png Two Tricks for Turning Sentence Embeddings into Clean Features Turn OpenAI sentence embeddings into clean geographic and systemic-risk features with two deterministic, training-free scoring techniques. https://nosible.com/blog/an-embedding-based-approach-to-trade-and-economic-policy-uncertainty 2026-06-17 https://nosible.com/images/2026/06/nosible-tpu-daily.png An Embedding-Based Approach to Trade and Economic Policy Uncertainty Rebuild the Fed’s Trade Policy Uncertainty index from 14.9 million NOSIBLE World events using embeddings, then extend the method to broader policy risk. https://nosible.com/blog/turning-news-into-a-risk-on-risk-off-equity-signal 2026-06-16 https://nosible.com/images/2026/06/news-stress-overlay-hero.png Turning News into a Risk-On/Risk-Off Equity Signal Build a point-in-time market-stress signal from NOSIBLE World that cuts S&P 500 drawdown and transfers unchanged to the Nasdaq and Russell 2000. https://nosible.com/blog/rebuilding-the-geopolitical-risk-index-from-nosible-world 2026-06-06 https://nosible.com/images/2026/06/nosible-gpr-vs-published.png We Rebuilt the Geopolitical Risk Index with Nosible World Rebuild the geopolitical risk index from 13.2 million NOSIBLE World events and reproduce its global, country, country-pair and oil-risk signals. https://nosible.com/blog/fast-enough-to-matter-productionizing-tiny-transformers-for-signal-extraction 2025-12-12 https://nosible.com/blog/illustrations/the-sprinter.png Matching GPT-5.1 at Financial Sentiment with Active Learning and Qwen3 Fine-tune Qwen3 0.6B with active learning to match GPT-5.1 on financial sentiment, with open models, datasets and training code. https://nosible.com/blog/can-faceted-search-at-web-scale-self-organize 2025-10-16 https://nosible.com/blog/illustrations/vortex.png Can Faceted Search at Web-Scale Self Organize? See how adaptive named-entity tagging lets a web-scale search index organize itself into useful facets without relying on a fixed taxonomy. https://nosible.com/blog/introducing-cybernaut-1-agentic-search-with-mcts 2025-08-26 https://nosible.com/blog/illustrations/cyber.png Introducing Cybernaut-1: Agentic Search using MCTS Meet Cybernaut-1, NOSIBLE’s agentic search system combining hybrid retrieval with LLM-guided Monte Carlo Tree Search. https://nosible.com/blog/the-road-to-cybernaut-1 2025-08-20 https://nosible.com/blog/illustrations/track.png The Road to Cybernaut-1: Rebuilding Search for AI Why AI needs a purpose-built search engine, and how NOSIBLE rebuilt hybrid retrieval on the road to its Cybernaut-1 agentic search system. https://nosible.com/blog/ensemble-and-distil 2024-02-06 https://nosible.com/blog/illustrations/cube.png A Pattern for Scaling the Value Proposition of LLMs: Ensemble and Distil 🚀 Train a simple regression on sentence embeddings to distil an LLM ensemble—and outperform GPT-4 on financial sentiment classification. https://nosible.com/blog/news-sentiment-showdown-who-checks-vibes-best 2024-01-28 https://nosible.com/blog/illustrations/eye.png News Sentiment Showdown: Who Checks Vibes Best? Compare TextBlob, VADER, FinBERT, Gemini, GPT-3.5 and GPT-4 on 10,368 labelled financial news stories, including the dataset and code. https://nosible.com/blog/using-vector-search-to-see-signals-in-company-news 2024-01-21 https://nosible.com/blog/illustrations/inspect.png Using Vector Search to See Signals in Company News Use vector search over company news to extract investment signals from a multi-terabyte, point-in-time corpus of more than 55 million embeddings.