Best AI tools for< Develop Methods >

The Max Planck Institute for Informatics focuses on Visual Computing and Artificial Intelligence, conducting research at the intersection of Computer Graphics, Computer Vision, and Artificial Intelligence. The institute aims to develop innovative methods to capture, represent, synthesize, and simulate real-world models with high detail, robustness, and efficiency. By combining concepts from Computer Graphics, Computer Vision, and Machine Learning, the institute lays the groundwork for advanced computing systems that can interact intelligently with humans and the environment.

The Visual Computing & Artificial Intelligence Lab at TUM is a group of research enthusiasts advancing cutting-edge research at the intersection of computer vision, computer graphics, and artificial intelligence. Our research mission is to obtain highly-realistic digital replica of the real world, which include representations of detailed 3D geometries, surface textures, and material definitions of both static and dynamic scene environments. In our research, we heavily build on advances in modern machine learning, and develop novel methods that enable us to learn strong priors to fuel 3D reconstruction techniques. Ultimately, we aim to obtain holographic representations that are visually indistinguishable from the real world, ideally captured from a simple webcam or mobile phone. We believe this is a critical component in facilitating immersive augmented and virtual reality applications, and will have a substantial positive impact in modern digital societies.

Design Sparks is an AI-powered creativity tool that helps users generate new ideas and solve design problems. The tool uses a variety of AI techniques, including machine learning and natural language processing, to understand user input and generate relevant ideas. Design Sparks is designed to be used by a wide range of users, from designers and engineers to marketers and business professionals. The tool is easy to use and can be accessed through a web-based interface.

IllumiDesk is a generative AI platform designed for instructors and content developers. It enables users to create and monetize tailored content up to 10 times faster than traditional methods. The platform offers a range of features including automated grading, collaboration tools, real-time collaboration, AI-powered content creation, and integrations with various services. IllumiDesk is suitable for a wide range of users, from freelancers and solopreneurs to large organizations and educational institutions.

Seedbox is an AI-based solution provider that crafts custom AI solutions to address specific challenges and boost businesses. They offer tailored AI solutions, state-of-the-art corporate innovation methods, high-performance computing infrastructure, secure and cost-efficient AI services, and maintain the highest security standards. Seedbox's expertise covers in-depth AI development, UX/UI design, and full-stack development, aiming to increase efficiency and create sustainable competitive advantages for their clients.

SEO Vendor is a white label SEO, PPC, and web design reseller platform that provides agencies with the tools and resources they need to grow their businesses. With SEO Vendor, agencies can offer their clients a full suite of marketing services, including SEO, PPC, web design, and content marketing. SEO Vendor's platform is powered by CORE AI, a patent-pending AI technology that delivers 10X better results than traditional SEO methods. With SEO Vendor, agencies can close more deals, retain clients longer, and grow their businesses faster.

Phenaki is a model capable of generating realistic videos from a sequence of textual prompts. It is particularly challenging to generate videos from text due to the computational cost, limited quantities of high-quality text-video data, and variable length of videos. To address these issues, Phenaki introduces a new causal model for learning video representation, which compresses the video to a small representation of discrete tokens. This tokenizer uses causal attention in time, which allows it to work with variable-length videos. To generate video tokens from text, Phenaki uses a bidirectional masked transformer conditioned on pre-computed text tokens. The generated video tokens are subsequently de-tokenized to create the actual video. To address data issues, Phenaki demonstrates how joint training on a large corpus of image-text pairs as well as a smaller number of video-text examples can result in generalization beyond what is available in the video datasets. Compared to previous video generation methods, Phenaki can generate arbitrarily long videos conditioned on a sequence of prompts (i.e., time-variable text or a story) in an open domain. To the best of our knowledge, this is the first time a paper studies generating videos from time-variable prompts. In addition, the proposed video encoder-decoder outperforms all per-frame baselines currently used in the literature in terms of spatio-temporal quality and the number of tokens per video.

ScaDS.AI (Center for Scalable Data Analytics and Artificial Intelligence) is a research center focusing on Data Science, Artificial Intelligence, and Big Data with locations in Dresden and Leipzig. It is one of the five new AI centers in Germany funded under the federal government's AI strategy by the Federal Ministry of Education and Research and the Free State of Saxony. The center collaborates closely with TUD Dresden University of Technology and Leipzig University, aiming to bridge the gap between mass data utilization, knowledge management, and advanced AI methods.

Code & Pepper is an elite software development company specializing in FinTech and HealthTech. They combine human talent with AI tools to deliver efficient solutions. With a focus on specific technologies like React.js, Node.js, Angular, Ruby on Rails, and React Native, they offer custom software products and dedicated software engineers. Their unique talent identification methodology selects the top 1.6% of candidates for exceptional outcomes. Code & Pepper champions human-AI centaur teams, harmonizing creativity with AI precision for superior results.

Clarion Technologies is an AI-assisted development company that offers a wide range of software development services, including custom software development, web app development, mobile app development, cloud solutions, and Power BI solutions. They provide services for various technologies such as React Native, Java, Python, PHP, Laravel, and more. With a focus on AI-driven planning and Agile Project Execution Methodology, Clarion Technologies ensures top-quality results with faster time to market. They have a strong commitment to data security, compliance, and privacy, and offer on-demand access to skilled developers and tech architects.

JMIR AI is a new peer-reviewed journal focused on research and applications for the health artificial intelligence (AI) community. It includes contemporary developments as well as historical examples, with an emphasis on sound methodological evaluations of AI techniques and authoritative analyses. It is intended to be the main source of reliable information for health informatics professionals to learn about how AI techniques can be applied and evaluated.

Vocapia Research develops leading-edge, multilingual speech processing technologies exploiting AI methods such as machine learning. These technologies enable large vocabulary continuous speech recognition, automatic audio segmentation, language identification, speaker diarization and audio-text synchronization. Vocapia's VoxSigma™ speech-to-text software suite delivers state-of-the-art performance in many languages for a variety of audio data types, including broadcast data, parliamentary hearings and conversational data.

Simplilearn is an online bootcamp and certification platform that offers courses in various fields, including AI and machine learning, project management, cyber security, cloud computing, and data science. The platform partners with leading universities and companies to provide industry-relevant training and certification programs. Simplilearn's courses are designed to help learners develop job-ready skills and advance their careers.

Storybooks is an online platform that allows users to create personalized children's stories. With Storybooks, users can choose their own storylines, illustrations, and characters to create unique and engaging stories for their children. Storybooks also offers a variety of features to help children learn and grow, such as games, puzzles, and activities. The platform is designed to be easy to use and accessible to all families, regardless of their income or background.

CreateApp.ai is an AI-powered app development platform that allows users to develop apps in days, not months. It is trusted by leading companies and startup incubators. CreateApp.ai's first step towards its vision is CreatePrototype.ai, which allows users to describe their idea in plain English and build an app prototype in minutes. CreateApp.ai is coming soon, and users can sign up for early access. With CreateApp.ai, users can develop apps in plain English, without any tech knowledge required. CreateApp.ai takes care of everything, from app design and development to app maintenance. CreateApp.ai is the easiest way to build apps.

Skillsoft is an online learning platform that provides a variety of courses and programs to help employees develop their skills and knowledge. The platform uses AI to personalize the learning experience for each user, and it offers a variety of features to help users track their progress and achieve their goals. Skillsoft is used by over 12,000 organizations worldwide, and it has been shown to improve employee engagement, productivity, and retention.

Figma is a collaborative interface design tool that allows design and development teams to work together seamlessly. It offers features such as design and prototyping in one place, collaboration with a digital whiteboard, translating designs into code, creating presentations, and exploring AI features. Figma helps streamline the product development process by providing tools for design systems, prototyping, UX design, web design, wireframing, and more. It aims to bring design and development teams together to build great products efficiently.

CodeSignal is an AI-powered platform that helps users discover and develop in-demand skills. It offers skills assessments and AI-powered learning tools to help individuals and teams level up their skills. The platform provides solutions for talent acquisition, technical interviewing, skill development, and more. With features like pre-screening, interview assessments, and personalized learning, CodeSignal aims to help users advance their careers and build high-performing teams.

Reform is a modern logistics software development platform that provides pre-built modules and AI capabilities to help teams build logistics applications quickly and efficiently. It offers features such as document AI for automating data capture, universal TMS integrations for seamless connectivity, embeddable customer dashboards for real-time data visibility, and more.

WrapFast is a SwiftUI boilerplate that helps developers create AI wrappers and iOS apps quickly and easily. It provides pre-written code for common tasks such as authentication, onboarding, in-app purchases, paywalls, securing API keys, cloud database, analytics, settings, and collecting user feedback. WrapFast is designed to save developers time and effort, allowing them to focus on building their core features. It is suitable for both experienced iOS developers and beginners who are new to the platform.

NineRec is a benchmark dataset suite for evaluating transferable recommendation models. It provides datasets for pre-training and transfer learning in recommender systems, focusing on multimodal and foundation model tasks. The dataset includes user-item interactions, item texts in multiple languages, item URLs, and raw images. Researchers can use NineRec to develop more effective and efficient methods for pre-training recommendation models beyond end-to-end training. The dataset is accompanied by code for dataset preparation, training, and testing in PyTorch environment.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

LLM-Merging is a repository containing starter code for the LLM-Merging competition. It provides a platform for efficiently building LLMs through merging methods. Users can develop new merging methods by creating new files in the specified directory and extending existing classes. The repository includes instructions for setting up the environment, developing new merging methods, testing the methods on specific datasets, and submitting solutions for evaluation. It aims to facilitate the development and evaluation of merging methods for LLMs.

MindNLP is an open-source NLP library based on MindSpore. It provides a platform for solving natural language processing tasks, containing many common approaches in NLP. It can help researchers and developers to construct and train models more conveniently and rapidly. Key features of MindNLP include: * Comprehensive data processing: Several classical NLP datasets are packaged into a friendly module for easy use, such as Multi30k, SQuAD, CoNLL, etc. * Friendly NLP model toolset: MindNLP provides various configurable components. It is friendly to customize models using MindNLP. * Easy-to-use engine: MindNLP simplified complicated training process in MindSpore. It supports Trainer and Evaluator interfaces to train and evaluate models easily. MindNLP supports a wide range of NLP tasks, including: * Language modeling * Machine translation * Question answering * Sentiment analysis * Sequence labeling * Summarization MindNLP also supports industry-leading Large Language Models (LLMs), including Llama, GLM, RWKV, etc. For support related to large language models, including pre-training, fine-tuning, and inference demo examples, you can find them in the "llm" directory. To install MindNLP, you can either install it from Pypi, download the daily build wheel, or install it from source. The installation instructions are provided in the documentation. MindNLP is released under the Apache 2.0 license. If you find this project useful in your research, please consider citing the following paper: @misc{mindnlp2022, title={{MindNLP}: a MindSpore NLP library}, author={MindNLP Contributors}, howpublished = {\url{https://github.com/mindlab-ai/mindnlp}}, year={2022} }

CompressAI-Vision is a tool that helps you develop, test, and evaluate compression models with standardized tests in the context of compression methods optimized for machine tasks algorithms such as Neural-Network (NN)-based detectors. It currently focuses on two types of pipeline: Video compression for remote inference (`compressai-remote-inference`), which corresponds to the MPEG "Video Coding for Machines" (VCM) activity. Split inference (`compressai-split-inference`), which includes an evaluation framework for compressing intermediate features produced in the context of split models. The software supports all the pipelines considered in the related MPEG activity: "Feature Compression for Machines" (FCM).

OpenRedTeaming is a repository focused on red teaming for generative models, specifically large language models (LLMs). The repository provides a comprehensive survey on potential attacks on GenAI and robust safeguards. It covers attack strategies, evaluation metrics, benchmarks, and defensive approaches. The repository also implements over 30 auto red teaming methods. It includes surveys, taxonomies, attack strategies, and risks related to LLMs. The goal is to understand vulnerabilities and develop defenses against adversarial attacks on large language models.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

PaddleScience is a scientific computing suite developed based on the deep learning framework PaddlePaddle. It utilizes the learning ability of deep neural networks and the automatic (higher-order) differentiation mechanism of PaddlePaddle to solve problems in physics, chemistry, meteorology, and other fields. It supports three solving methods: physics mechanism-driven, data-driven, and mathematical fusion, and provides basic APIs and detailed documentation for users to use and further develop.

Combine the power of LLMs with Django's productivity to build intelligent applications. Let AI Assistants call methods from Django's side and do anything your users need! Use AI Tool Calling and RAG with Django to easily build state of the art AI Assistants.

The Intel® Geti™ SDK is a python package that enables teams to rapidly develop AI models by easing the complexities of model development and enhancing collaboration between teams. It provides tools to interact with an Intel® Geti™ server via the REST API, allowing for project creation, downloading, uploading, deploying for local inference with OpenVINO, setting project and model configuration, launching and monitoring training jobs, and media upload and prediction. The SDK also includes tutorial-style Jupyter notebooks demonstrating its usage.

The Octopus-v4 project aims to build the world's largest graph of language models, integrating specialized models and training Octopus models to connect nodes efficiently. The project focuses on identifying, training, and connecting specialized models. The repository includes scripts for running the Octopus v4 model, methods for managing the graph, training code for specialized models, and inference code. Environment setup instructions are provided for Linux with NVIDIA GPU. The Octopus v4 model helps users find suitable models for tasks and reformats queries for effective processing. The project leverages Language Large Models for various domains and provides benchmark results. Users are encouraged to train and add specialized models following recommended procedures.

Superplatform is a microservices platform focused on distributed AI management and development. It enables users to self-host AI models, build backendless AI apps, develop microservices-based AI applications, and deploy third-party AI apps easily. The platform supports running open-source AI models privately, building apps leveraging AI models, and utilizing a microservices-based communal backend for diverse projects.

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

Slack Machine is a simple, yet powerful and extendable Slack bot framework. More than just a bot, Slack Machine is a framework that helps you develop your Slack workspace into a ChatOps powerhouse. Slack Machine is built with an intuitive plugin system that lets you build bots quickly, but also allows for easy code organization.

Pearl is a production-ready Reinforcement Learning AI agent library open-sourced by the Applied Reinforcement Learning team at Meta. It enables researchers and practitioners to develop Reinforcement Learning AI agents that prioritize cumulative long-term feedback over immediate feedback and can adapt to environments with limited observability, sparse feedback, and high stochasticity. Pearl offers a diverse set of unique features for production environments, including dynamic action spaces, offline learning, intelligent neural exploration, safe decision making, history summarization, and data augmentation.

COMFYUI LLM PARTY is a node library designed for LLM workflow development in ComfyUI, an extremely minimalist UI interface primarily used for AI drawing and SD model-based workflows. The project aims to provide a complete set of nodes for constructing LLM workflows, enabling users to easily integrate them into existing SD workflows. It features various functionalities such as API integration, local large model integration, RAG support, code interpreters, online queries, conditional statements, looping links for large models, persona mask attachment, and tool invocations for weather lookup, time lookup, knowledge base, code execution, web search, and single-page search. Users can rapidly develop web applications using API + Streamlit and utilize LLM as a tool node. Additionally, the project includes an omnipotent interpreter node that allows the large model to perform any task, with recommendations to use the 'show_text' node for display output.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

AIRS is a collection of open-source software tools, datasets, and benchmarks focused on Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. The goal is to develop and maintain an integrated, open, reproducible, and sustainable set of resources to advance the field of AI for Science. The current resources include tools for Quantum Mechanics, Density Functional Theory, Small Molecules, Protein Science, Materials Science, Molecular Interactions, and Partial Differential Equations.

Provides concise HPLC troubleshooting and method development advice

Provides concise GC troubleshooting and method development advice that is easy to implement.

I'm the Mixed Methods Design Decision Tool, offering guidance on mixed methods research designs, their implementation, and effective communication in studies.

Expert Growth Hacker using Reforge methods for client strategy

Informative and health-focused expert on lead testing methods and tools.

Expert in engaging, interactive training methods and activities.

I am an oracle of futures, inspired by Jim Dator's methods.

Assess your company's real appetite for new technologies or new ways of working methods

Expert on hydrogen production systems and the hydrogen economy.

English teacher for lesson planning and research

推荐课题主题、研究内容、研究方法、研究创新点、研究计划和预期成果等信息，生成符合省部级格式要求和逻辑结构的课题标书。

Educational advisor on schooling and learning methodologies

Focused adviser on carbon project methodologies and markets.

This GPT Helps to Brainstorm Immersive Experience Ideas Using the TISECT Method

Your Architectural Pathway Guide. Expert in TOGAF methodology, offering guidance on principles, techniques, and processes.

Virtual psychologist using the 5 Whys method for self-exploration.

A facilitator for understanding concepts using a simplified Concept Attainment Method.

I help create fantasy worlds according to the CREATION method.

Leveraging the power of models like VisionaryGeniusAI, GaiaAI, ACALLM, GannAI, and many more, I will generate answers that go beyond standard replies, instead offering a unique blend of insights and perspectives drawn from multiple domains and methodologies.

An Innovation & R&D Management advisor who can help you turn ideas into new value creation using over 60 methodologies and tools. Attributed to Yann Rousselot-Pailley https://www.linkedin.com/in/yannrousselot/