Research
Technical insights, product updates, and deep dives from the Nosible team
Can Faceted Search at Web-Scale Self Organize?
Can Faceted Search at Web-Scale Self Organize? As it turns out, yes it can! In this post we outline our new and improved adaptive named entity tagging system!
Introducing Cybernaut-1: Agentic Search using MCTS
Cybernaut-1 combines our powerful hybrid-3 search algorithm with LLM-guided Monte Carlo Tree Search to deliver world class search results on difficult queries.
The Road to Cybernaut-1: Rebuilding Search for AI
AI needs its own search engine. This is how we’re rebuilding search for AI -- and the road to Cybernaut-1, the first high-trust agentic search engine.
A Pattern for Scaling the Value Proposition of LLMs: Ensemble and Distil 🚀
We introduce the ensemble and distil data pattern and use it to fit an ordinary least squares linear regression that outperforms GPT-4 at financial news sentiment classification using sentence transformer embeddings as features.
News Sentiment Showdown: Who Checks Vibes Best?
A comparison of sentiment classifications made by TextBlob, VADER, Flair, SigmaFSA, FinBERT, FinBERT-Tone, Text-Bison, Text-Unicorn, Gemini-Pro, GPT-3.5, GPT-4, and GPT-4-Turbo. We look at accuracy, time, and cost and include a dataset of 10,368 labelled news stories (with code) for our followers.
Using Vector Search to See Signals in Company News
How we use vector search to extract investment signals from a multi-terabyte company news dataset that currently contains over 55 million embeddings, 150+ million sentences, 4+ billion words, and 5+ billion GPT tokens.