Best AI tools for< Improve Techniques >

Leexi is an AI-powered meeting tool that helps users transcribe, analyze, and summarize calls and meetings. It uses generative AI to automate note-taking, report writing, and propose next steps, saving users time and improving productivity. Leexi offers features such as automated note-taking, tailored summaries, time-saving capabilities, express setup, facilitated collaboration, contextualized call summaries, and in-depth analysis. The application is suitable for various industries and professions, including sales, consulting, customer success, recruitment, finance, journalism, marketing, and real estate.

Kittl is an online graphic design platform that provides users with a variety of tools and resources to create stunning designs. With Kittl, users can access a library of templates, fonts, illustrations, and other design elements to create custom designs for a variety of purposes, including logos, t-shirts, posters, and social media graphics. Kittl also offers a number of AI-powered tools, such as an AI text-to-vector generator and an AI image generator, that can help users create unique and eye-catching designs.

AudioForgeAI is an AI-powered online platform that offers advanced audio editing and enhancement tools. Users can easily upload their audio files and apply various editing techniques to improve the quality and clarity of the sound. The platform is designed to be user-friendly and intuitive, making it suitable for both beginners and experienced audio professionals. With AudioForgeAI, users can enhance audio recordings, remove background noise, adjust volume levels, and apply various effects to create high-quality audio content.

Mebot is an AI-powered application designed to help users enhance their memory and cognitive skills. By leveraging artificial intelligence technology, Mebot provides personalized memory training exercises and techniques to improve memory retention and recall. Users can track their progress, set reminders, and receive tailored recommendations to optimize their memory performance. With Mebot, users can enjoy a fun and engaging way to boost their memory capabilities and overall cognitive function.

Focusdoro is a productivity application designed to help users manage their tasks and time effectively. It offers features such as task management, time tracking, analytics, and habit tracking. Users can organize their work, monitor productivity, gain insights into work patterns, and boost concentration using proven time-blocking techniques. Focusdoro aims to empower users to achieve more in less time by eliminating distractions and providing smart reminders.

Robo Rat is an AI-powered tool designed for business document digitization. It offers a smart and affordable resume parsing API that supports over 50 languages, enabling quick conversion of resumes into actionable data. The tool aims to simplify the hiring process by providing speed and accuracy in parsing resumes. With advanced AI capabilities, Robo Rat delivers highly accurate and intelligent resume parsing solutions, making it a valuable asset for businesses of all sizes.

This website is an AI tool that helps senior developers analyze AI tech debt. AI tech debt is the technical debt that accumulates when AI systems are developed and deployed. It can be difficult to identify and quantify AI tech debt, but it can have a significant impact on the performance and reliability of AI systems. This tool uses a variety of techniques to analyze AI tech debt, including static analysis, dynamic analysis, and machine learning. It can help senior developers to identify and quantify AI tech debt, and to develop strategies to reduce it.

Sensae is an AI-powered biofeedback platform that uses data-driven techniques to enhance personal well-being. It integrates physiology and psychology using haptic biofeedback to help people reconnect with their inner emotions. Sensae's technology provides deep insights into the body and mind, uncovering hidden emotional patterns and revealing the complex web of human behavior and thinking. The platform offers a range of modules, including advanced bio-monitoring, stress assessment, heart rate variability assessment, and psychometric testing. Sensae's proprietary wearable device provides haptic biofeedback, creating a direct feedback loop that ensures the effectiveness of both stimuli and interventions.

Athina AI is a platform that provides research and guides for building safe and reliable AI products. It helps thousands of AI engineers in building safer products by offering tutorials, research papers, and evaluation techniques related to large language models. The platform focuses on safety, prompt engineering, hallucinations, and evaluation of AI models.

Abacus.AI is the world's first AI platform where AI, not humans, build Applied AI agents and systems at scale. Using generative AI and other novel neural net techniques, AI can build LLM apps, gen AI agents, and predictive applied AI systems at scale.

StackBuddy is an AI-powered blogging, SEO, and affiliate marketing platform that offers comprehensive tools and resources for individuals looking to build and grow their online presence. The platform covers a wide range of topics including blogging, SEO, social media marketing, web hosting, entrepreneurship, and technology. Users can access guides, reviews, deals, and learn how to make passive income online. StackBuddy is designed to help users optimize their online strategies and stay updated with the latest trends in the digital space.

Dating Photo AI is an AI-powered application designed to enhance your dating profile by generating photos that look like you, helping you get more matches on dating platforms. The application uses advanced AI techniques to analyze and optimize your photos, ensuring they reflect your true self and attract potential matches. With a user-friendly interface and a satisfaction guarantee, Dating Photo AI offers a cost-efficient alternative to traditional photoshoots, making it easier for singles to showcase their best selves online.

MindPeace AI is an AI-powered platform that serves as a personal mental wellbeing companion, offering therapeutic techniques to guide users towards self-reflection, relaxation, and emotional balance. It provides tools, exercises, and gentle reminders in a convenient, stigma-free environment. The platform is designed to complement traditional therapy by providing on-demand support, but it does not replace human therapists. MindPeace AI prioritizes privacy and safety, ensuring that conversations are private and personal information is never shared with third parties.

Coschool is an AI-powered assistant designed to help teachers save time and improve their teaching. With Coschool, teachers can access a variety of tools and resources to help them plan lessons, create assignments, grade papers, and communicate with students and parents. Coschool also provides teachers with personalized recommendations and support to help them improve their teaching skills.

IXICO is a precision analytics company specializing in intelligent insights in neuroscience. They offer a range of services for drug development analytics, imaging operations, and post-marketing consultancy. With a focus on technology and innovation, IXICO provides expertise in imaging biomarkers, radiological reads, volumetric MRI, PET & SPECT, and advanced MRI. Their TrialTracker platform and Assessa tool utilize innovation and AI for disease modeling and analysis. IXICO supports biopharmaceutical companies in CNS clinical research with cutting-edge neuroimaging techniques and AI technology.

Sourcely is an AI-powered academic search assistant designed to help students and researchers find, summarize, and add credible academic sources efficiently. With access to over 200 million research papers and advanced search filters, Sourcely streamlines the research process by simplifying source discovery, providing targeted citations, offering free PDF downloads, organizing citations in a personal library, generating credible summaries, and exporting references in various formats. It aims to save time, enhance the quality of work, and improve academic writing by automating the search for appropriate citations.

Heli Naik offers online watercolor classes for individuals looking to learn and improve their watercolor painting skills. With a focus on creating a fun and encouraging learning environment, Heli Naik provides monthly membership classes, single-subject classes, and top-rated classes for artists of all skill levels. The classes include step-by-step tutorials, access to various techniques, and a new theme or subject to paint in each session. Join now to unleash your creativity and explore the beauty and versatility of watercolor painting.

SkillAI is an AI-powered skill development platform designed for future-ready professionals. It offers personalized learning paths generated using AI for any skill, helping users plan their success. The platform enables users to discover and share learning paths within a community, stay updated with new skills, and track their learning progress. SkillAI aims to provide a structured way for individuals to enhance their skills and knowledge in various domains.

Kayyo is a personal MMA trainer application that offers interactive lessons for beginners and experts. It provides challenges, personalized feedback, and a variety of games to enhance punching and kicking prowess. With AI personal trainers, Kayyo transforms workouts into dynamic and entertaining sessions that adapt to the user's pace. The app aims to help users master their moves, engage in virtual fights, and improve their overall fitness performance. Kayyo is free to use and currently focuses on building its features for martial arts enthusiasts.

Prompt Engineering is a discipline focused on developing and optimizing prompts to efficiently utilize language models (LMs) for various applications and research topics. It involves skills to understand the capabilities and limitations of large language models, improving their performance on tasks like question answering and arithmetic reasoning. Prompt engineering is essential for designing robust prompting techniques that interact with LLMs and other tools, enhancing safety and building new capabilities by augmenting LLMs with domain knowledge and external tools.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

optillm is an OpenAI API compatible optimizing inference proxy implementing state-of-the-art techniques to enhance accuracy and performance of LLMs, focusing on reasoning over coding, logical, and mathematical queries. By leveraging additional compute at inference time, it surpasses frontier models across diverse tasks.

This repository is a comprehensive guide for individuals looking to start and improve their skills in Large Language Models (LLMs) without an advanced background in the field. It provides free resources, online courses, books, articles, and practical tips to become an expert in machine learning. The guide covers topics such as terminology, transformers, prompting, retrieval augmented generation (RAG), and more. It also includes recommendations for podcasts, YouTube videos, and communities to stay updated with the latest news in AI and LLMs.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

This practical free hands-on course focuses on Large Language models and their applications, providing a hands-on experience using models from OpenAI and the Hugging Face library. The course is divided into three major sections: Techniques and Libraries, Projects, and Enterprise Solutions. It covers topics such as Chatbots, Code Generation, Vector databases, LangChain, Fine Tuning, PEFT Fine Tuning, Soft Prompt tuning, LoRA, QLoRA, Evaluate Models, Knowledge Distillation, and more. Each section contains chapters with lessons supported by notebooks and articles. The course aims to help users build projects and explore enterprise solutions using Large Language Models.

LLM Zoomcamp is a free online course focusing on real-life applications of Large Language Models (LLMs). Over 10 weeks, participants will learn to build an AI bot capable of answering questions based on a knowledge base. The course covers topics such as LLMs, RAG, open-source LLMs, vector databases, orchestration, monitoring, and advanced RAG systems. Pre-requisites include comfort with programming, Python, and the command line, with no prior exposure to AI or ML required. The course features a pre-course workshop and is led by instructors Alexey Grigorev and Magdalena Kuhn, with support from sponsors and partners.

Pandrator is a GUI tool for generating audiobooks and dubbing using voice cloning and AI. It transforms text, PDF, EPUB, and SRT files into spoken audio in multiple languages. It leverages XTTS, Silero, and VoiceCraft models for text-to-speech conversion and voice cloning, with additional features like LLM-based text preprocessing and NISQA for audio quality evaluation. The tool aims to be user-friendly with a one-click installer and a graphical interface.

Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates tasks such as data cleaning, preprocessing, and complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless. It aims to expedite the data analysis process, making it accessible to all, regardless of their expertise in data analysis. The tool is built to empower users to process data and achieve high-quality visualizations with unparalleled efficiency, and to execute high-performance modeling with the best strategies. Future enhancements include Natural Language Processing (NLP), neural networks, and object detection utilizing YOLO, broadening its capabilities to meet diverse data analysis needs.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

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.

Advanced RAG Techniques is a comprehensive collection of cutting-edge Retrieval-Augmented Generation (RAG) tutorials aimed at enhancing the accuracy, efficiency, and contextual richness of RAG systems. The repository serves as a hub for state-of-the-art RAG enhancements, comprehensive documentation, practical implementation guidelines, and regular updates with the latest advancements. It covers a wide range of techniques from foundational RAG methods to advanced retrieval methods, iterative and adaptive techniques, evaluation processes, explainability and transparency features, and advanced architectures integrating knowledge graphs and recursive processing.

Mortal (凡夫) is a free and open source AI for Japanese mahjong, powered by deep reinforcement learning. It provides a comprehensive solution for playing Japanese mahjong with AI assistance. The project focuses on utilizing deep reinforcement learning techniques to enhance gameplay and decision-making in Japanese mahjong. Mortal offers a user-friendly interface and detailed documentation to assist users in understanding and utilizing the AI effectively. The project is actively maintained and welcomes contributions from the community to further improve the AI's capabilities and performance.

This repository contains a collection of sample applications and Jupyter Notebooks for hands-on experience with Pinecone vector databases and common AI patterns, tools, and algorithms. It includes production-ready examples for review and support, as well as learning-optimized examples for exploring AI techniques and building applications. Users can contribute, provide feedback, and collaborate to improve the resource.

This repository contains a collection of research papers related to watermarking techniques for text and images, specifically focusing on large language models (LLMs). The papers cover various aspects of watermarking LLM-generated content, including robustness, statistical understanding, topic-based watermarks, quality-detection trade-offs, dual watermarks, watermark collision, and more. Researchers have explored different methods and frameworks for watermarking LLMs to protect intellectual property, detect machine-generated text, improve generation quality, and evaluate watermarking techniques. The repository serves as a valuable resource for those interested in the field of watermarking for LLMs.

AIMET is a library that provides advanced model quantization and compression techniques for trained neural network models. It provides features that have been proven to improve run-time performance of deep learning neural network models with lower compute and memory requirements and minimal impact to task accuracy. AIMET is designed to work with PyTorch, TensorFlow and ONNX models. We also host the AIMET Model Zoo - a collection of popular neural network models optimized for 8-bit inference. We also provide recipes for users to quantize floating point models using AIMET.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

fAIr is an open AI-assisted mapping service developed by the Humanitarian OpenStreetMap Team (HOT) to improve mapping efficiency and accuracy for humanitarian purposes. It uses AI models, specifically computer vision techniques, to detect objects like buildings, roads, waterways, and trees from satellite and UAV imagery. The service allows OSM community members to create and train their own AI models for mapping in their region of interest and ensures models are relevant to local communities. Constant feedback loop with local communities helps eliminate model biases and improve model accuracy.

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Offers exercises and techniques to improve memory retention and cognitive functions.

Learn to write impeccable essays with APA standards. Use natural language processing techniques, structure your arguments, and master APA format. Improve your writing professionally

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I'm Back Propagation, here to help you understand and apply back propagation techniques to your AI models.

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