Best AI tools for< Floral Designer >

Lifelike is a website that offers a wide range of lifelike products and services to enhance your daily life. From lifelike artificial plants and flowers to lifelike animal sculptures and lifelike human figurines, we provide high-quality and realistic items to add beauty and charm to your surroundings. Our lifelike products are meticulously crafted to resemble their real counterparts, making them perfect for home decor, events, and gifts. With Lifelike, you can bring a touch of nature and artistry into your life with ease.

FLORA is an intelligent canvas that serves as a creative AI tool, connecting various AI applications to help users ideate, iterate, and bring their ideas to life. It allows real-time collaboration among team members using favorite AI tools, offering a platform to explore different workflows. FLORA simplifies AI complexities by curating the best text, image, and video models, empowering users to unleash their creativity on a new canvas.

Flora Incognita is an AI-supported plant identification application that allows users to identify over 30,000 plant species. It enables users to save plant observations, access extensive plant fact sheets, and contribute to science through citizen science projects. The app is free of charge, ad-free, and works offline, making it ideal for educational purposes and nature conservation initiatives. The research project 'Flora Incognita++' combines AI technology with citizen science to enhance plant identification accuracy.

APOLLO is a memory-efficient optimizer designed for large language model (LLM) pre-training and full-parameter fine-tuning. It offers SGD-like memory cost with AdamW-level performance. The optimizer integrates low-rank approximation and optimizer state redundancy reduction to achieve significant memory savings while maintaining or surpassing the performance of Adam(W). Key contributions include structured learning rate updates for LLM training, approximated channel-wise gradient scaling in a low-rank auxiliary space, and minimal-rank tensor-wise gradient scaling. APOLLO aims to optimize memory efficiency during training large language models.

SurveyX is an advanced academic survey automation system that leverages Large Language Models (LLMs) to generate high-quality, domain-specific academic papers and surveys. Users can request comprehensive academic papers or surveys tailored to specific topics by providing a paper title and keywords for literature retrieval. The system streamlines academic research by automating paper creation, saving users time and effort in compiling research content.

The Beta Machine Learning Toolkit is a package containing various algorithms and utilities for implementing machine learning workflows in multiple languages, including Julia, Python, and R. It offers a range of supervised and unsupervised models, data transformers, and assessment tools. The models are implemented entirely in Julia and are not wrappers for third-party models. Users can easily contribute new models or request implementations. The focus is on user-friendliness rather than computational efficiency, making it suitable for educational and research purposes.

This repository includes papers and blogs about Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation(RAG), and Evaluation for Long Context Modeling.

Creates the perfect floral arrangement for whatever is on the menu.

I'm your virtual wedding assistant, here to help with all your wedding needs!

Specializing in Japanese flora, providing detailed info and references. 日本の植物に特化し、詳細な情報と参考文献をあげるガイドです。

Especialista em teses de Botânica do Brasil