Best AI tools for< Elaborate Concepts >

SciSpace is an AI-powered tool that helps researchers understand research papers better. It can explain and elaborate most academic texts in simple words. It is a great tool for students, researchers, and anyone who wants to learn more about a particular topic. SciSpace has a user-friendly interface and is easy to use. Simply upload a research paper or enter a URL, and SciSpace will do the rest. It will highlight key concepts, provide definitions, and generate a summary of the paper. SciSpace can also be used to generate citations and find related papers.

Elaborate.ai is an AI-powered tool that helps users generate incredible narratives and slides from their story outlines. It offers a range of features to assist with idea development, fine-tuning, content writing, research presentation, progress reports, and educational materials creation. Elaborate.ai aims to simplify and expedite the content creation process, enabling users to focus on the key message and effectively communicate their ideas.

VModel.AI is an AI fashion models generator that revolutionizes on-model photography for fashion retailers. It utilizes artificial intelligence to create high-quality on-model photography without the need for elaborate photoshoots, reducing model photography costs by 90%. The tool helps diversify stores, improve E-commerce engagement, reduce returns, promote diversity and inclusion in fashion, and enhance product offerings.

UnrealPhotoshoot is an AI-powered tool that allows users to generate hyper-realistic person images with just a few clicks. Users can specify the appearance, outfit, pose, and location of the person in the image, making it ideal for creative projects, marketing campaigns, and more. With features like modifying appearance, choosing outfits, specifying locations, cloning poses, and generating faces, UnrealPhotoshoot offers a convenient and innovative solution for creating realistic images without the need for professional models or elaborate photoshoots.

Awesome-AGI is a curated list of resources related to Artificial General Intelligence (AGI), including models, pipelines, applications, and concepts. It provides a comprehensive overview of the current state of AGI research and development, covering various aspects such as model training, fine-tuning, deployment, and applications in different domains. The repository also includes resources on prompt engineering, RLHF, LLM vocabulary expansion, long text generation, hallucination mitigation, controllability and safety, and text detection. It serves as a valuable resource for researchers, practitioners, and anyone interested in the field of AGI.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access a GPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval. The repo includes sample data so it's ready to try end to end. In this sample application we use a fictitious company called Contoso Electronics, and the experience allows its employees to ask questions about the benefits, internal policies, as well as job descriptions and roles.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

Notes on AI state of the art, with a focus on generative and large language models. These are the "raw materials" for the https://lspace.swyx.io/ newsletter. This repo used to be called https://github.com/sw-yx/prompt-eng, but was renamed because Prompt Engineering is Overhyped. This is now an AI Engineering notes repo.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

Mergekit is a toolkit for merging pre-trained language models. It uses an out-of-core approach to perform unreasonably elaborate merges in resource-constrained situations. Merges can be run entirely on CPU or accelerated with as little as 8 GB of VRAM. Many merging algorithms are supported, with more coming as they catch my attention.

Resonance is a framework designed to facilitate interoperability and messaging between services in your infrastructure and beyond. It provides AI capabilities and takes full advantage of asynchronous PHP, built on top of Swoole. With Resonance, you can: * Chat with Open-Source LLMs: Create prompt controllers to directly answer user's prompts. LLM takes care of determining user's intention, so you can focus on taking appropriate action. * Asynchronous Where it Matters: Respond asynchronously to incoming RPC or WebSocket messages (or both combined) with little overhead. You can set up all the asynchronous features using attributes. No elaborate configuration is needed. * Simple Things Remain Simple: Writing HTTP controllers is similar to how it's done in the synchronous code. Controllers have new exciting features that take advantage of the asynchronous environment. * Consistency is Key: You can keep the same approach to writing software no matter the size of your project. There are no growing central configuration files or service dependencies registries. Every relation between code modules is local to those modules. * Promises in PHP: Resonance provides a partial implementation of Promise/A+ spec to handle various asynchronous tasks. * GraphQL Out of the Box: You can build elaborate GraphQL schemas by using just the PHP attributes. Resonance takes care of reusing SQL queries and optimizing the resources' usage. All fields can be resolved asynchronously.

Graph of Thoughts (GoT) is an official implementation framework designed to solve complex problems by modeling them as a Graph of Operations (GoO) executed with a Large Language Model (LLM) engine. It offers flexibility to implement various approaches like CoT or ToT, allowing users to solve problems using the new GoT approach. The framework includes setup guides, quick start examples, documentation, and examples for users to understand and utilize the tool effectively.

gen.nvim is a tool that allows users to generate text using Language Models (LLMs) with customizable prompts. It requires Ollama with models like `llama3`, `mistral`, or `zephyr`, along with Curl for installation. Users can use the `Gen` command to generate text based on predefined or custom prompts. The tool provides key maps for easy invocation and allows for follow-up questions during conversations. Additionally, users can select a model from a list of installed models and customize prompts as needed.

LLM Blueprint is an official implementation of a paper that enables text-to-image generation with complex and detailed prompts. It leverages Large Language Models (LLMs) to extract critical components from text prompts, including bounding box coordinates for foreground objects, detailed textual descriptions for individual objects, and a succinct background context. The tool operates in two phases: Global Scene Generation creates an initial scene using object layouts and background context, and an Iterative Refinement Scheme refines box-level content to align with textual descriptions, ensuring consistency and improving recall compared to baseline diffusion models.

Expert in elaborating and deepening understanding of topics.

este specialist in scrierea fiselor de observatie elaborate de catre un student

Nutritionniste, fournissant un schéma de traitement nutritionnel, élaborant un menu en fonction des objectifs ::: langue française

CSIRT que lidera un equipo especializado en detectar y responder a incidentes de seguridad, maneja la contención y recuperación, organiza entrenamientos y simulacros, elabora reportes para optimizar estrategias de seguridad y coordina con entidades legales cuando es necesario