Research & Education

BLUMEx is an AI-led advisory firm specializing in securing non-dilutive government financing, including grants, subsidies, and low-interest loans, for SMEs, non-profits, and municipalities across Canada. Their core innovation is the Context Engine, an AI-powered knowledge system built for each client. This engine ingests organizational data like financials, projects, and meeting transcripts, then connects to LLMs to generate grant applications, model economic impact, and provide financial projections. Unlike traditional consulting, the Context Engine retains organizational intelligence, compounding in value over time. BLUMEx offers full-stack delivery, from program discovery and eligibility assessment to application writing, financial modeling, and submission, with a success-based pricing model.

llm-universe offers a comprehensive tutorial for beginner developers interested in large language model (LLM) application development. The project is designed to be highly practical, guiding users through the creation of a personal knowledge base assistant on an Alibaba Cloud server. It covers essential topics such as LLM introductions, API calling methods for various models (including GPT, Baidu Wenxin, iFlytek Spark, and Zhipu AI), knowledge base construction, and building RAG (Retrieval Augmented Generation) applications. The tutorial emphasizes hands-on learning, simplifying complex concepts and focusing on core skills needed to develop LLM-powered applications, making it accessible even for those without a strong AI or algorithm background.

OS Ninja provides an intelligent way to explore and learn open-source projects by generating AI-powered learning paths for any repository. It decodes complex codebases and creates structured tutorials, diagrams, and documentation that evolve with the code. Users can search for open-source projects or request new ones to be added. The platform performs deep research on entire codebases, which can take up to 24 hours, to generate high-fidelity learning paths. It caters to various learning styles, including Socratic questioning, Feynman technique, and traditional book format. OS Ninja also offers curated collections of open-source repositories across categories like Generative AI, Data, Robotics, Game Engines, Crypto & Web3, and Machine Learning, making it a comprehensive resource for developers looking to master new codebases.

Dhitva Technologies offers a comprehensive learning ecosystem that integrates Virtual Reality with AI analytics to significantly enhance educational outcomes. The platform is designed to improve retention rates by 80% and accelerate learning speed by 4x, as supported by global research. Dhitva stands out by combining high-fidelity VR simulations with a proprietary AI Chat Bot that provides real-time guidance and feedback. This AI analyzes student gaze and decisions, offering instant corrections and generating adaptive scenarios so no two learning sessions are the same. The platform is compatible with Meta Quest, HTC Vive, and standard web browsers, making it accessible for modern educational institutions.

Studiolo is an innovative AI tool designed to facilitate rapid and personalized learning experiences. Users can select any topic, from 'Korean Cooking Fundamentals' to 'Intro to Machine Learning,' and the platform aims for them to remember it within 45 minutes. It allows for the augmentation of learning inquiries with local assets, enabling a truly customized educational path. Studiolo also offers options to define expertise levels, current depth of understanding, and session lengths, ranging from 5 to 45 minutes. For those unsure what to learn, a chat feature helps guide the user, making it accessible for a wide range of learners seeking efficient knowledge acquisition.

AIGC_Interview is a GitHub repository designed as a comprehensive guide for individuals seeking jobs in the AIGC (AI-Generated Content) field. It compiles essential resources such as interview experiences, fundamental knowledge, and prompt engineering techniques. The repository covers critical topics like ChatGPT, Stable Diffusion, Prompt, Embedding, and Fine-tuning, offering insights into what job seekers need to know for AIGC-related positions. It aims to assist users in preparing for interviews, understanding industry trends, and navigating the job market, particularly for roles like prompt engineers and AI algorithm specialists. The project also encourages community contributions, including sharing job opportunities and interview experiences.

Awesome-ChatGPT-prompts-ZH_CN is a GitHub repository dedicated to providing a diverse collection of Chinese prompts for ChatGPT and other large language models like Claude. It offers creative methods to customize AI behavior, such as transforming ChatGPT into a 'cat-girl' persona for role-playing scenarios. The repository also includes techniques for bypassing certain AI content restrictions and limitations, with specific instructions for ChatGPT and NewBing. It features tools for exporting conversations, bypassing WAF errors, and enhancing the AI's mathematical capabilities. The project is open-source, encouraging community contributions and providing updates on new bypass methods and prompt engineering techniques.

This GitHub repository, ChatGPT-Prompt-Engineering-for-Developers-in-Chinese, offers unofficial Chinese and English subtitles for the popular "ChatGPT Prompt Engineering for Developers" course. It aims to make the technical content accessible to a broader audience, particularly Chinese-speaking developers. The repository includes core bilingual subtitles, as well as separate English and Chinese subtitle files, along with course notebooks. This resource is invaluable for those looking to master prompt engineering for ChatGPT, covering best practices, sentiment classification, text summarization, email writing, translation, and building chatbots. It also provides insights into GPT API development, allowing users to extend their learning into building impressive applications.

machine-learning-deep-learning-notes provides a comprehensive learning path and knowledge summary for machine learning and deep learning, designed for modern AI development. It advocates a "practice first, then theory" approach, encouraging users to build projects and then delve into underlying principles as needed. The resource covers core concepts in mathematics, Python libraries like NumPy and Pandas, and practical applications of machine learning algorithms. It also delves into deep learning frameworks such as PyTorch and TensorFlow, with a strong focus on large language models (LLMs), multimodal AI, and AI agents. The guide includes structured learning paths for beginners and advanced users, emphasizing rapid skill acquisition and practical project building.

LLMBook-zh.github.io is an open-source project providing a comprehensive Chinese textbook titled "大语言模型" (Large Language Models). Authored by Zhao Xin, Li Junyi, Zhou Kun, Tang Tianyi, and Wen Jirong, this book aims to popularize and disseminate the latest advancements in large model technology. It offers a systematic framework and roadmap for LLM technologies, making it ideal for beginners with a background in deep learning. The project includes PDF courseware, code snippets on GitHub, and related teaching videos on Bilibili, serving as a valuable resource for both academic study and practical application. The content covers essential topics such as pre-training, fine-tuning, alignment, and prompt engineering, drawing from the authors' extensive research and practical experience in developing large models.

LLMs_interview_notes is an open-source repository designed to help algorithm engineers prepare for interviews related to Large Language Models (LLMs). The resource compiles learning notes and materials based on personal interview experiences, covering a wide array of LLM topics. It includes detailed sections on LLM fundamentals, advanced attention mechanisms, transformer operations, loss functions, similarity functions, generative LLMs, fine-tuning strategies, LangChain, and Retrieval-Augmented Generation (RAG). This comprehensive collection aims to provide a structured approach to understanding and answering common interview questions in the rapidly evolving field of LLMs.

llm-cookbook is an open-source project offering a comprehensive, developer-focused introduction to Large Language Models (LLMs). It translates, reproduces, and optimizes content from Andrew Ng's LLM course series, making it highly accessible for Chinese developers. The curriculum spans essential topics from Prompt Engineering to RAG development and model fine-tuning, guiding learners through practical applications. It includes both foundational 'required' courses for core skills and 'elective' courses for specialized areas like Gradio for AI application building, evaluating generative AI, and advanced RAG techniques. The project also provides translated code examples, online reading materials, and PDF downloads, with a focus on adapting content for the Chinese linguistic context.

Prompt-tutorial is a GitHub-based open-source resource dedicated to teaching prompt engineering for large language models (LLMs). It offers a structured series of lessons covering fundamental principles, advanced strategies, and common limitations in prompt creation. The tutorial emphasizes clear and explicit instructions, structured output requirements, and iterative prompt optimization. It includes practical examples for tasks like text summarization, inference, language translation, and content generation, making it suitable for individuals looking to enhance their skills in interacting with LLMs without requiring a technical background.

TautMore is an EdTech platform designed for K-12 schools, providing a comprehensive, one-stop solution for educational needs. The platform leverages advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Virtual Reality (VR) to create highly personalized learning experiences for students. Beyond technology, TautMore integrates principles of learner psychology to optimize educational outcomes. It combines essential school management functionalities, including a Learning Management System (LMS), Enterprise Resource Planning (ERP), and supply chain management services, into a single platform. Additionally, TautMore extends its offerings to include live classes and various extracurricular activities, aiming to provide a holistic educational environment.

tensorflow-nlp-tutorial is an open-source Deep Learning NLP repository built on TensorFlow 2.0+. It offers a comprehensive collection of tutorials covering various aspects of Natural Language Processing, from fundamental text preprocessing techniques to advanced models like Topic Models, BERT, GPT, and Large Language Models (LLMs). The repository details downstream tasks for these modern models, providing practical examples for students and developers. Each tutorial file includes a Colab link, enabling users to practice directly in a browser without needing a local Python installation. The content is based on an extensive 1,200-page e-Book, ensuring a strong theoretical foundation alongside practical application. Updates include recent additions for RAG, LLM, and VLM fine-tuning.

PyTorch-Tutorial-2nd is a comprehensive, open-source tutorial designed for individuals ranging from beginners to experienced deep learning engineers. It systematically covers PyTorch fundamentals, including environment setup, data handling, model building, optimization, and visualization. The tutorial delves into practical applications across computer vision (image classification, segmentation, object detection, GANs, Diffusion models), natural language processing (RNN, LSTM, Transformer, BERT, GPT models for text classification, machine translation), and large language models (Qwen, ChatGLM, Baichuan, Yi, GPT Academic). Furthermore, it provides in-depth guidance on industrial deployment, covering ONNX and TensorRT principles, model quantization (PTQ, QAT), and acceleration techniques, enabling users to master PyTorch for real-world project implementation.

Prompt-Engineering-Guide-zh-CN is an open-source, continuously updated guide to prompt engineering, specifically tailored for Chinese speakers. It serves as a comprehensive resource for understanding and optimizing prompts for large language models (LLMs). The guide covers various aspects of prompt engineering, including introductory concepts, basic and advanced prompting techniques, applications, and specific guidance for ChatGPT. It also compiles relevant papers, lectures, notebooks, and tools, making it an invaluable resource for researchers and developers looking to enhance their understanding and application of LLMs.

WriteGPT is an open-source AI framework developed by Turing's Cat, primarily focused on generating argumentative essays. Built upon the GPT-2 model, it leverages advanced OCR and NLP techniques to produce human-like text. The tool is specifically finetuned for high school essays, particularly argumentative styles, and can generate articles that often meet passing grades. It integrates various modules including EAST for text detection, CRNN for text recognition, BERT for text summarization, and GPT-2 for text generation. WriteGPT is intended for academic exchange and popular science, offering features like end-to-end generation from exam paper recognition to answer sheet output, and an online text generation demo via Colab. While it aims for human-like output, the developers note that not all generated essays are perfect, and some may only barely pass or even fail.

Foundations-of-LLMs is an open-source book designed for readers interested in large language models, providing a systematic explanation of foundational knowledge and cutting-edge techniques. The author team is committed to monthly updates, incorporating suggestions from the open-source community and experts, aiming to create an easy-to-read, rigorous, and in-depth LLM textbook. Each chapter is accompanied by a relevant Paper List to track the latest advancements. The first edition covers traditional language models, LLM architecture evolution, prompt engineering, parameter-efficient fine-tuning, model editing, and retrieval-augmented generation. The book uses animal-themed examples to illustrate specific technologies, making complex concepts more accessible.

LexiLex is an AI-powered language learning tool designed to transform any text into personalized educational material. Users can input text by typing, taking photos of documents, or dictating by voice, or even generate content from a brief topic description. The platform then analyzes the text, providing translations and transcriptions for phrases, and allows users to study the original text or text with contextual translations. It features smart flashcards that adapt to individual progress, helping users memorize new words and phrases effectively. LexiLex aims to make language learning accessible and efficient by leveraging personalized content.

Naseem is an innovative learning management system (LMS) that leverages the power of Artificial Intelligence, Neuroscience, and Learning Science to create a highly personalized educational environment. Designed to adapt to individual learning styles and needs, Naseem offers a dynamic platform for students. While specific features are not detailed on the provided website content, the core offering revolves around an intelligent system that likely supports adaptive learning paths, content delivery, and progress tracking. This approach aims to optimize learning outcomes by understanding how the brain learns and applying AI to tailor the educational journey.

Ask Muslim AI is a digital platform designed to provide users with answers to their daily questions, drawing directly from the teachings of the Quran. This AI-powered tool aims to offer religious guidance and information on Islamic principles in an accessible format. It focuses on delivering ethical and safe content while prioritizing user privacy. The platform is built to support multilingual access, making its resources available to a broader audience seeking insights rooted in Islamic scripture. It serves as a conversational AI agent for those looking for faith-based answers.

Lhy_Machine_Learning serves as a comprehensive open-source repository for machine learning course materials and assignments from Professor Li Hongyi's spring courses spanning 2021, 2022, and 2023. Hosted on GitHub, this resource offers lecture slides, videos, and practical assignments covering fundamental concepts to advanced topics like Diffusion Models, Large Language Models, and Generative AI. It includes direct links to course videos, lecture notes, and homework assignments, often with accompanying code and platforms like Kaggle or JudgeBoi for submission. The repository is actively maintained with regular updates on topics and assignments, making it an invaluable resource for students and researchers looking to deepen their understanding of machine learning.

HuggingLLM is an open-source project dedicated to making Large Language Models (LLMs) accessible and understandable for a broad audience, including those without a deep NLP or algorithm background. The project aims to introduce the principles, usage, and applications of ChatGPT and other LLMs, enabling users to leverage these powerful AI tools to create their own AI products and services. It provides detailed learning guides, practical examples, and code implementations focusing on how to use LLM APIs for various tasks such as QA, text classification, and text generation. The project emphasizes adapting to the rapidly evolving AI landscape and encourages hands-on practice with both international and domestic LLM APIs like GLM and Qwen. It's designed for learners with some programming experience who want to apply LLMs to solve real-world problems.