Best AI tools for< Solve Design Problems >

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.

Intervu is an AI-powered interview platform that helps users prepare for system design interviews. It offers unlimited True-to-Life system design interviews with AI, enriched with comprehensive feedback, to help users conquer system design challenges.

Iambic Therapeutics is a cutting-edge AI-driven drug discovery platform that tackles the most challenging design problems in drug discovery, addressing unmet patient need. Its physics-based AI algorithms drive a high-throughput experimental platform, converting new molecular designs to new biological insights each week. Iambic's platform optimizes target product profiles, exploring multiple profiles in parallel to ensure that molecules are designed to solve the right problems in disease biology. It also optimizes drug candidates, deeply exploring chemical space to reveal novel mechanisms of action and deliver diverse high-quality leads.

Problembo is a platform that leverages AI and other advanced technologies to provide user-friendly tools for solving everyday problems and fostering creativity. It offers a range of services that simplify tasks and enhance productivity, including neural network for word drawing, AI-powered interior design, background removal from images, AI-powered chat, image editing, and image description. Problembo aims to make complex technologies accessible and affordable, empowering users to bring their ideas to life without the need for technical expertise or high costs.

Interview Solver is a desktop application that acts as your copilot during coding interviews, providing instant solutions to LeetCode problems and system design questions. It features screengrabbing capabilities, one-shot solutions, query selected text functionality, global hotkeys, and syntax highlighting for all major languages. Interview Solver is designed to give you an AI advantage during live interviews, helping you land your dream job.

Ideator is an AI-powered tool that helps designers and innovators generate creative ideas. It allows users to input a feature or interaction and then generates different variations of how it could be used, while keeping its main job the same. Ideator is still under development, but it has the potential to be a valuable tool for designers and innovators who are looking for new and creative ways to solve problems.

Interview Monkey is an AI tool designed to help software engineering candidates ace technical interviews. It offers real-time problem-solving capabilities for coding and system design questions, supporting over 10 coding languages. The tool operates discreetly during screenshare sessions, provides solutions without typing, and is tailored for various interview types. Interview Monkey aims to boost candidates' confidence, increase hiring chances, and upgrade their roles and salaries in the competitive job market.

GPTStore.AI is a platform that showcases a variety of GPTs (Generative Pre-trained Transformers) for different purposes, such as search engines, AI assistants, math solvers, image generators, content writers, and more. Users can explore and discover GPTs developed by various creators to assist them in tasks ranging from generating images to writing tailored content. The platform aims to provide a curated collection of GPTs to help users find the best tools for their specific needs.

NeuroSYS is an AI and IT solutions provider that offers services in Artificial Intelligence, Software Development, Digital Innovation, Product Design, and other related areas. The company specializes in leveraging AI to boost efficiency, drive digital innovation, and design better products for various industries. NeuroSYS also provides services in software development, digital transformation, augmented reality, and data science, among others. With a focus on AI technologies like Machine Learning, Deep Learning, and Large Language Models automation, NeuroSYS aims to support businesses in achieving growth and automation of processes.

Startify is an AI-powered application designed to assist startup founders in overcoming challenges and accessing expert insights. It offers comprehensive solutions through a user-friendly interface, allowing users to gather relevant information from standard and latest research effortlessly. With a mobile-friendly design, Startify serves as a personal advisor to help entrepreneurs work smarter and achieve success. The application aims to streamline the startup process by providing instant access to expert insights and solutions, ultimately saving time and enhancing productivity.

AIEasy.life is an AI tools platform designed to empower daily life with intelligent AI solutions. The platform offers a curated directory of various AI tools across categories such as text & writing, image, video, voice, business, marketing, chatbot, design & art, life assistant, 3D, education, productivity, and other development learning AI applications. Users can access tools like MyMathSolver.ai for solving complex math problems, Vozo AI for video content creation, Grammarly for enhancing writing, and many more. AIEasy.life aims to simplify tasks and enhance productivity through the use of advanced AI technology.

Khanmigo is an AI-powered teaching assistant and tutor developed by Khan Academy, a trusted education nonprofit. It offers personalized learning experiences for teachers, learners, and parents across various subjects such as math, science, coding, and humanities. Khanmigo aims to revolutionize education by providing on-demand support, engaging content, and ethical design focused on safety and learning. With features tailored for educators and students, Khanmigo simplifies workflows, challenges critical thinking, and guides learners to discover answers independently.

Apex Vision AI is an AI-powered homework helper that provides instant answers and assistance to college students. It utilizes advanced machine learning algorithms to generate accurate answers for multiple-choice homework and quizzes, saving students time and boosting their confidence. The extension seamlessly integrates into the user's browser, offering real-time answers with a click or keyboard shortcut. Its user-friendly interface and intuitive design make it easy for students to use, helping them study smarter and not harder.

VibePrompts is an online marketplace where users can buy and sell prompts for various AI models and tools. The platform offers a wide range of prompts tailored to different niches, including art and illustrations, logos and icons, graphics and design, productivity and writing, marketing and business, photography, games and 3D. Users can browse through the collection of prompts, select and customize them to fit their specific requirements, and then activate and engage them in their desired application or platform.

Leetcode Wizard is a desktop application designed to assist users in coding interviews by providing solutions for any Leetcode problem, known or unknown. It aims to help users achieve success in coding interviews, particularly at top tech companies like FAANG. The application uses AI to analyze coding problems, suggest algorithms, generate code output, and provide a complexity analysis. Leetcode Wizard is built with a privacy-first mindset, ensuring undetectable operation during coding interviews.

idmark is an AI tool designed to help entrepreneurs solve their problems by delegating and automating tasks using various AI applications. The platform aims to provide users with more free time, better sleep, increased productivity, and overall happiness by leveraging the power of artificial intelligence. With features like productivity tools for marketing, design, sales, and product management, idmark offers a comprehensive solution for streamlining business operations and enhancing efficiency. Users can access the platform on both computers and mobile devices, making productivity management accessible anytime, anywhere. The tool is user-friendly and comes with a 7-day unconditional money-back guarantee, ensuring a risk-free experience for users.

Imandra is a company that provides automated logical reasoning for Large Language Models (LLMs). Imandra's technology allows LLMs to build mental models and reason about them, unlocking the potential of generative AI for industries where correctness and compliance matter. Imandra's platform is used by leading financial firms, the US Air Force, and DARPA.

The Institute for Protein Design is a research institute at the University of Washington that uses computational design to create new proteins that solve modern challenges in medicine, technology, and sustainability. The institute's research focuses on developing new protein therapeutics, vaccines, drug delivery systems, biological devices, self-assembling nanomaterials, and bioactive peptides. The institute also has a strong commitment to responsible AI development and has developed a set of principles to guide its use of AI in research.

The AI Maze Generator is an online tool that allows users to create, solve, and download random maze puzzles in various sizes and colors. It utilizes the recursive backtracking algorithm to design mazes and the A* search algorithm to find the shortest path. Users can customize maze specifications like wall thickness, columns, rows, maze entries, and bias. The tool offers a user-friendly interface for maze creation and solving, providing a fun and engaging experience for maze enthusiasts.

Datasparq is a specialist AI & data firm that designs, builds, and runs high-impact AI & data solutions. They help businesses at every stage of their AI journey, from value discovery to managing AI solutions. Datasparq combines data science, data engineering, product thinking, and design to deliver valuable, operational AI solutions quickly. Their focus is on creating AI tools that drive business improvements, efficiency, and effectiveness through data platforms, analytics, and machine learning.

LLM4EDA is a repository dedicated to showcasing the emerging progress in utilizing Large Language Models for Electronic Design Automation. The repository includes resources, papers, and tools that leverage LLMs to solve problems in EDA. It covers a wide range of applications such as knowledge acquisition, code generation, code analysis, verification, and large circuit models. The goal is to provide a comprehensive understanding of how LLMs can revolutionize the EDA industry by offering innovative solutions and new interaction paradigms.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

ChatDev IDE is a tool for building your AI agent, Whether it's NPCs in games or powerful agent tools, you can design what you want for this platform. It accelerates prompt engineering through **JavaScript Support** that allows implementing complex prompting techniques.

The Enterprise Azure OpenAI Hub is a comprehensive repository designed to guide users through the world of Generative AI on the Azure platform. It offers a structured learning experience to accelerate the transition from concept to production in an Enterprise context. The hub empowers users to explore various use cases with Azure services, ensuring security and compliance. It provides real-world examples and playbooks for practical insights into solving complex problems and developing cutting-edge AI solutions. The repository also serves as a library of proven patterns, aligning with industry standards and promoting best practices for secure and compliant AI development.

APIPark is an open-source AI Gateway and Developer Portal that enables users to easily manage, integrate, and deploy AI and API services. It provides robust API management features, including creation, monitoring, and access control, to help developers efficiently and securely develop and manage their APIs. The platform aims to solve challenges such as connecting to powerful AI models, managing complex AI & API call relationships, overseeing API creation and security, simplifying fault detection and troubleshooting, and enhancing the visibility and valuation of data assets.

This repository contains an assistant proposal for the Semantic Kernel, allowing the usage of assistants without relying on OpenAI Assistant APIs. It runs locally planners and plugins for the assistants, providing scenarios like Assistant with Semantic Kernel plugins, Multi-Assistant conversation, and AutoGen conversation. The Semantic Kernel is a lightweight SDK enabling integration of AI Large Language Models with conventional programming languages, offering functions like semantic functions, native functions, and embeddings-based memory. Users can bring their own model for the assistants and host them locally. The repository includes installation instructions, usage examples, and information on creating new conversation threads with the assistant.

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

LLM Reasoners is a library that enables LLMs to conduct complex reasoning, with advanced reasoning algorithms. It approaches multi-step reasoning as planning and searches for the optimal reasoning chain, which achieves the best balance of exploration vs exploitation with the idea of "World Model" and "Reward". Given any reasoning problem, simply define the reward function and an optional world model (explained below), and let LLM reasoners take care of the rest, including Reasoning Algorithms, Visualization, LLM calling, and more!

LLM-as-HH is a codebase that accompanies the paper ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution. It introduces Language Hyper-Heuristics (LHHs) that leverage LLMs for heuristic generation with minimal manual intervention and open-ended heuristic spaces. Reflective Evolution (ReEvo) is presented as a searching framework that emulates the reflective design approach of human experts while surpassing human capabilities with scalable LLM inference, Internet-scale domain knowledge, and powerful evolutionary search. The tool can improve various algorithms on problems like Traveling Salesman Problem, Capacitated Vehicle Routing Problem, Orienteering Problem, Multiple Knapsack Problems, Bin Packing Problem, and Decap Placement Problem in both black-box and white-box settings.

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.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

GOLEM is an open-source AI framework focused on optimization and learning of structured graph-based models using meta-heuristic methods. It emphasizes the potential of meta-heuristics in complex problem spaces where gradient-based methods are not suitable, and the importance of structured models in various problem domains. The framework offers features like structured model optimization, metaheuristic methods, multi-objective optimization, constrained optimization, extensibility, interpretability, and reproducibility. It can be applied to optimization problems represented as directed graphs with defined fitness functions. GOLEM has applications in areas like AutoML, Bayesian network structure search, differential equation discovery, geometric design, and neural architecture search. The project structure includes packages for core functionalities, adapters, graph representation, optimizers, genetic algorithms, utilities, serialization, visualization, examples, and testing. Contributions are welcome, and the project is supported by ITMO University's Research Center Strong Artificial Intelligence in Industry.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

AI Gallery is a showcase site built using React and Nextjs for static site generation, featuring interactive visualizations of classic algorithms, classic games implementation, and various interesting widgets. The project utilizes AI assistance from Claude 3.5 and GPT-4 to create components and enhance the development process. It aims to continually add more components with AI assistance, providing a platform for contributors to leverage AI in frontend development.

Commonplace Bot is a modern representation of the commonplace book, leveraging modern technological advancements in computation, data storage, machine learning, and networking. It aims to capture, engage, and share knowledge by providing a platform for users to collect ideas, quotes, and information, organize them efficiently, engage with the data through various strategies and triggers, and transform the data into new mediums for sharing. The tool utilizes embeddings and cached transformations for efficient data storage and retrieval, flips traditional engagement rules by engaging with the user, and enables users to alchemize raw data into new forms like art prompts. Commonplace Bot offers a unique approach to knowledge management and creative expression.

This repository contains the training and inference code needed to replicate the winning solution to the AI Mathematical Olympiad - Progress Prize 1. It consists of fine-tuning DeepSeekMath-Base 7B, high-quality training datasets, a self-consistency decoding algorithm, and carefully chosen validation sets. The training methodology involves Chain of Thought (CoT) and Tool Integrated Reasoning (TIR) training stages. Two datasets, NuminaMath-CoT and NuminaMath-TIR, were used to fine-tune the models. The models were trained using open-source libraries like TRL, PyTorch, vLLM, and DeepSpeed. Post-training quantization to 8-bit precision was done to improve performance on Kaggle's T4 GPUs. The project structure includes scripts for training, quantization, and inference, along with necessary installation instructions and hardware/software specifications.

Awesome Generative AI is a curated list of modern Generative Artificial Intelligence projects and services. Generative AI technology creates original content like images, sounds, and texts using machine learning algorithms trained on large data sets. It can produce unique and realistic outputs such as photorealistic images, digital art, music, and writing. The repo covers a wide range of applications in art, entertainment, marketing, academia, and computer science.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

Friendly, casual coach for design skills & growth, avoiding negativity and bias.

Solve problems at front-end applications development - AI 100% PRO - 500+ Guides trainer

An expert C# engineer to help you solve and debug problems together.

Biomimicry as a way of life.

I help create and run productive design thinking sessions.

I will help you create brilliant products, services and experiences.

Nature’s Greatest Hits from a 3.9-Billion-Year-Old Lab

Expert in designing engaging and effective Design Thinking workshops.

A helpful coach for guiding teams through Design Sprints with a touch of sass.

Product Engineer helps find inventive solutions to engineering problems.

Solves Numericals in Physics, provides ideas to design an Internal Assessment (Physics Projects) and Extended Essays for IBDP Curriculum

Expert in programming, system admin, and design - OZ

A virtual Doraemon solving problems with imaginative gadgets.

Expert in Design Thinking for innovation and leadership

Expert design mentor, responding in the input language.

Your go-to guide for home renovation, design, and DIY advice.

Ask me anything about facilitaton and workshop design

A UX guru offering insights and resources in user experience and design.

Professioneller, lockerer Ingenieursexperte, nutzt Fachwörter mit Erklärungen und löst Aufgaben

An mechanical engineering tutor, aiding with concepts and problem-solving.