Thoth Machine Learning
We released Thoth ML, the machine learning module of project Thoth (https://github.com/trulia/thoth) to open source. Thoth is a real-time Solr monitor and search analysis engine. The Thoth ML module applies machine learning algorithms to the data collected by Thoth to gain useful insights. Currently, this module consists of the query time predictor and the query pattern recognition tool. The query time predictor receives a Solr search request and in real time (1-3 milli seconds) predicts if the query is going to be slow or fast. This prediction can be used by the search…
What it does
In the maker’s words, at launch
We released Thoth ML, the machine learning module of project Thoth (https://github.com/trulia/thoth) to open source. Thoth is a real-time Solr monitor and search analysis engine. The Thoth ML module applies machine learning algorithms to the data collected by Thoth to gain useful insights. Currently, this module consists of the query time predictor and the query pattern recognition tool. The query time predictor receives a Solr search request and in real time (1-3 milli seconds) predicts if the query is going to be slow or fast. This prediction can be used by the search infrastructure in multiple ways. At Trulia, the slow or fast prediction is used to route some requests to either a slow pool or a fast pool. This is done to ensure that critical user queries don't have to compete with complex, time consuming queries for resources. This leads to instantaneous query execution and hence, a pleasant user experience. The query pattern recognition tool uses probabilistic topic modeling to find commonly recurring patterns in Solr search requests. These patterns can be quite useful as seen in the example here (https://github.com/trulia/thoth-ml/wiki/Query-Pattern-Recognition). Here's the Thoth Machine Learning repository link : https://github.com/trulia/thoth-ml
Does the same job
all alternatives →- TAThoth – a real-time Solr monitor and search analysis engine2014 · github.com · ▲17





More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com

