Quino
|
Tags
|
Pricing model
Upvote
0
Quino is a study aid enhanced by AI that enables users to upload documents or research papers, creating tailored notes, summaries, bullet points, and quiz questions. Additionally, it features a chat function for retrieving contextual information and references from within the document and provides tools for organizing notes and learning materials to boost productivity.
Similar neural networks:
0
Vizologi is an AI-driven business strategy tool designed to assist businesses in addressing inquiries and generating ideas. It includes a business model canvas database with numerous examples, a mash-up approach for developing and refining business plans, and an autopilot function for conducting market research and competitive analysis. This tool has enabled thousands of users to answer over 1.5 million questions across more than 25,000 projects.
0
ZBrain is a holistic platform designed for empowering enterprises with AI, assisting organizations from the initial evaluation of AI readiness to full-scale implementation. Using ZBrain XPLR, businesses can assess their readiness and pinpoint areas for AI application, crafting a strategic roadmap. ZBrain Builder facilitates the development of bespoke AI applications and agents utilizing proprietary data, ensuring secure development and deployment. These AI agents are customized for specific departments including finance, sales, and marketing, automating processes such as variance analysis, lead management, and personalized content generation. ZBrain enables a smooth transition to AI-driven enterprise operations within a unified framework.
0
MiniGPT-4 is an instrument that improves vision-language comprehension by merging a fixed visual encoder with a fixed large language model (LLM) through a single projection layer. It can produce comprehensive image descriptions, convert handwritten drafts into websites, compose stories and poems based on provided images, offer solutions to issues presented in images, and instruct users on cooking from photographs of food. MiniGPT-4 is notably computationally efficient, needing only the training of the linear layer to align visual features with Vicuna using around 5 million aligned image-text pairs.