Persuva generates Shopify product pages, landing pages and advertorials in one click, aimed at dropshippers. The site lists an audience analyser among its features and states the product is built and optimised for stores on Shopify. Pricing details with explicit plans are not stated in the supplied documents.
Gensim is a free open-source Python library for topic modelling and semantic NLP. It trains large-scale semantic models, represents text as semantic vectors and finds semantically related documents. The site describes streaming of arbitrarily large corpora, platform independence, and pretrained models and corpora published by the community.
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Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features, delivering structured data to AI and LLM applications during training and inference. Documented use cases include real-time recommendations, fraud detection, risk scoring, and customer segmentation.
Vellum is a personal AI assistant available locally or in the cloud, with long-term memory across conversations. It can send emails, manage calendars, browse the web, create slides, write code, run research, and execute recurring background tasks. It offers fine-grained permissions requiring approval for high-stakes actions until marked trusted. Two plans exist: Base (free) and Pro packages Mighty, Super, and Ultra.
Neuroph is a lightweight, open source Java neural network framework released under the Apache 2.0 license. It provides a Java library and a GUI editor, Neuroph Studio, based on the NetBeans Platform, for creating, training and saving neural networks. It supports architectures including Perceptron, Multi Layer Perceptron, Hopfield, Kohonen and RBF networks, and both supervised and unsupervised learning rules.
VLFeat is an open-source library of computer vision algorithms focused on image understanding and local feature extraction and matching. Algorithms include SIFT, MSER, Fisher Vector, VLAD, k-means, SLIC superpixels, and SVM training. It is written in C with MATLAB interfaces and supports Windows, Mac OS X, and Linux.
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Gensim is a free open-source Python library for topic modelling and semantic NLP. It trains large-scale semantic models, represents text as semantic vectors and finds semantically related documents. The site describes streaming of arbitrarily large corpora, platform independence, and pretrained models and corpora published by the community.
The AI Safety Summit 2023 is a global event held on 1 and 2 November at Bletchley Park, Buckinghamshire. It brings together international governments, AI companies, civil society groups and researchers to consider AI risks, especially at the frontier of development, and discuss mitigation through internationally coordinated action.
Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features, delivering structured data to AI and LLM applications during training and inference. Documented use cases include real-time recommendations, fraud detection, risk scoring, and customer segmentation.
Vellum is a personal AI assistant available locally or in the cloud, with long-term memory across conversations. It can send emails, manage calendars, browse the web, create slides, write code, run research, and execute recurring background tasks. It offers fine-grained permissions requiring approval for high-stakes actions until marked trusted. Two plans exist: Base (free) and Pro packages Mighty, Super, and Ultra.
Neuroph is a lightweight, open source Java neural network framework released under the Apache 2.0 license. It provides a Java library and a GUI editor, Neuroph Studio, based on the NetBeans Platform, for creating, training and saving neural networks. It supports architectures including Perceptron, Multi Layer Perceptron, Hopfield, Kohonen and RBF networks, and both supervised and unsupervised learning rules.
VLFeat is an open-source library of computer vision algorithms focused on image understanding and local feature extraction and matching. Algorithms include SIFT, MSER, Fisher Vector, VLAD, k-means, SLIC superpixels, and SVM training. It is written in C with MATLAB interfaces and supports Windows, Mac OS X, and Linux.
