Research & Education

Bilateral AI is an Austrian Cluster of Excellence dedicated to advancing artificial intelligence by integrating symbolic and sub-symbolic AI. This project aims to overcome the limitations of current narrow AI systems, which are typically focused on specific tasks like object or speech recognition. By combining symbolic AI's logical rules with sub-symbolic AI's (like ChatGPT) data-driven learning, Bilateral AI seeks to develop 'Broad AI' capable of diverse applications and human-like reasoning. The initiative emphasizes creating AI that is not only fast and expandable but also safe, trustworthy, and understandable for everyday use. It involves cutting-edge research modules focusing on reasoning, learning, adaptability, and efficiency, and actively seeks to foster the next generation of AI researchers.

daily-paper-computer-vision is an open-source GitHub repository dedicated to curating and organizing academic papers in the fields of computer vision, deep learning, and machine learning. The repository is updated daily, offering a timely resource for researchers and enthusiasts to stay abreast of the latest advancements. It compiles papers from major conferences and journals, including CVPR, NIPS, ICLR, ECCV, and AAAI, often providing links to both the papers and their associated codebases. This makes it an invaluable resource for academic research, literature reviews, and tracking developments in AI subfields such as object detection, semantic segmentation, Transformer models, and large language models.

Awesome-LLM-Learning is a comprehensive open-source repository designed to guide individuals through the intricacies of Large Language Models (LLMs). It offers foundational knowledge in deep learning and natural language processing, essential for understanding LLMs. The resource delves into core LLM concepts, including training frameworks like Megatron-lm and DeepSpeed, parameter-efficient fine-tuning (PEFT), classic open-source LLMs, RLHF, CoT/ToT, and SFT training. Additionally, it covers LLM inference techniques such as Huggingface parameters and KVCache, and explores applications like LangChain. The repository also features a section dedicated to cutting-edge research, recommending relevant papers and blogs to keep learners updated with the latest advancements in the field. It's an invaluable resource for both newcomers and experienced professionals looking to deepen their understanding and practical skills in LLM development.

Cerebro is an AI-powered knowledge management platform designed to streamline the organization and enhancement of digital content. It leverages artificial intelligence to improve information retrieval and facilitate knowledge sharing across organizations. While specific features are not detailed on the provided website, the core purpose revolves around creating a more efficient and accessible knowledge base. The tool is likely aimed at businesses and teams looking to centralize their information, reduce redundancy, and ensure that relevant data is easily discoverable by employees. Its AI capabilities suggest advanced functionalities for content analysis, categorization, and intelligent search, making it a valuable asset for modern knowledge-driven environments.

Inclusive Growth Chain (IGC) is a technology company focused on driving impact through advanced technologies such as Blockchain, Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT). The company specializes in implementing blockchain-enabled services across critical sectors including financial inclusion, healthcare, women empowerment, education, and environmental sciences. IGC has a proven track record, highlighted by its success in winning international blockchain hackathons, demonstrating its expertise and innovative approach in applying these technologies for social good. While specific features are not detailed on the current website, its core mission revolves around leveraging cutting-edge tech to address societal challenges and foster inclusive growth.

Google SGE (Search Generative Experience) is an innovative AI-powered feature integrated into Google Search, designed to transform how users interact with search results. It utilizes advanced machine learning and natural language processing capabilities to provide contextual and comprehensive answers directly within the search interface. Instead of just listing links, SGE synthesizes information from multiple sources to present users with a concise summary, aiming to offer a more direct and efficient way to find information. This experimental feature, part of Google Labs, represents Google's ongoing efforts to integrate AI into its core products, offering a glimpse into the future of search.

Data-Science-EBooks is an open-source repository offering a comprehensive collection of high-quality ebooks focused on Data Science, Machine Learning, and Artificial Intelligence. This resource is designed to cater to both beginners looking to establish foundational knowledge and advanced learners seeking to deepen their expertise. The repository covers a wide array of topics including AI, Agentic AI, Basics of Data Science, Data Engineering & Pipeline, Data Science Cheatsheets, Deep Learning, Generative AI, MLOps, Machine Learning, Math for Data Science, NLP, Software Engineering, and System Design. It serves as an excellent resource for anyone looking to enhance their understanding and skills in these rapidly evolving fields.

LearnPrompt offers a comprehensive and permanently free open-source curriculum focused on AIGC (AI-Generated Content) technologies. The platform provides in-depth courses covering essential topics such as Prompt Engineering, ChatGPT, Midjourney, Runway, and Stable Diffusion. Beyond core generative AI, it expands into specialized areas like AI digital humans, AI voice and music generation, and the fine-tuning of large language models. With its latest v4.0 update, LearnPrompt features a new UI, multi-language support, a comments section, daily updates, and contribution options, making it a dynamic resource for anyone looking to master AIGC without cost. The platform is continuously updated with new content and features, including case studies and tutorials for advanced applications.

Deep_and_Machine_Learning_Projects is an open-source GitHub repository containing a diverse collection of machine and deep learning projects. This resource provides readily available code and data files, enabling users to explore and implement practical applications of artificial intelligence. Each project within the repository is designed to be a standalone example, allowing individuals to understand specific use cases and integrate them into their own real-life scenarios. It serves as an excellent learning resource for those looking to gain hands-on experience in AI development, offering a practical approach to mastering machine and deep learning concepts through direct implementation.

FineTuningLLMs is the official repository for the book "A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face." This resource offers comprehensive guidance and practical code examples for fine-tuning large language models. It covers essential concepts such as quantization, low-rank adapters (LoRA), and dataset formatting templates. The repository features Jupyter notebooks that can be easily run on Google Colab with GPU support, making it accessible for hands-on learning. It delves into topics like loading quantized models, fine-tuning with SFTTrainer, and deploying models locally using formats like GGUF with Ollama or llama.cpp. The guide is designed for an intermediate-level audience, assuming a foundational understanding of deep learning concepts.

Backdoor AI offers a service providing unblocked access to ChatGPT, powered by GPT-4, tailored for academic use. This tool is designed to assist students with their schoolwork, enabling them to chat with GPT-4 to efficiently answer questions and complete assignments. Its core features include unblocked access to ChatGPT and GPT-4 powered assistance for educational tasks. The primary use case revolves around answering schoolwork questions using the advanced capabilities of GPT-4, making it a valuable resource for students seeking AI support for their studies. Access to the service is obtained by contacting the provided email address.

Strikingo is an AI-powered education platform designed to transform learning by offering personalized experiences for both educators and learners. The platform leverages artificial intelligence to adapt to individual learning styles and paces, aiming to save educators valuable time in content creation and lesson planning. It focuses on delivering measurable results, ensuring that learning outcomes are tracked and improved. Strikingo supports a smart learning environment, making education more efficient and effective for a global audience. Its core mission is to enhance educational processes through intelligent, adaptive technology.

Solvee is an AI-powered homework helper specifically designed to assist students with their academic needs. It provides tutoring functionalities and smart study tools to enhance learning and comprehension. The platform focuses on supporting students in completing their homework effectively and offers general educational assistance. While the website content is currently limited, the tool's core purpose is to leverage artificial intelligence to provide a supportive learning environment for students, helping them achieve academic success through guided assistance and intelligent study resources.

ML-Tutorial-Experiment is an open-source GitHub repository dedicated to providing comprehensive coding tutorials for machine learning. It aims to help users learn to code machine learning models through practical examples and experiments. The resource covers a wide array of topics, including building convolutional neural networks with TensorFlow, understanding and implementing Generative Adversarial Networks (GANs), exploring CapsNet architecture, and delving into RNNs and CNNs for sequence modeling. It also features tutorials on Transformer-based neural machine translation and foundational concepts like linear algebra, probability, Python basics, and NumPy. The project emphasizes reproducible code and aims to curate high-quality, error-free articles for developers and researchers.

TheBloke Wizard Vicuna 13B Uncensored HF is an AI chatbot hosted as a Hugging Face Space. This tool offers an uncensored version of the Wizard Vicuna 13B model, allowing users to engage in conversational AI interactions without typical content restrictions. While the live website currently indicates a runtime error, suggesting it may not be fully operational at this moment, the intention is to provide a platform for direct interaction with this specific large language model. It is designed for those interested in exploring the capabilities of uncensored AI models within a readily accessible web environment.

Nested Knowledge, Inc. offers an AI-powered software platform designed to revolutionize systematic literature review and meta-analysis. The tool provides comprehensive capabilities for researchers, including advanced search functionalities, efficient screening processes, and robust data extraction tools. It also features powerful visualization insights to help users understand complex data more clearly. By automating and assisting in these critical research stages, Nested Knowledge aims to significantly accelerate the research workflow, enabling the creation of updatable syntheses of evidence and enhancing the overall efficiency and quality of academic research.

NeuralBox by NeuralCam is an AI-powered visual second brain designed to help users remember anything through photos. Users can easily capture photos, screenshots, and documents, and the tool's advanced AI indexes both objects (semantic image search) and text content (OCR) within them. This allows for effortless retrieval using simple descriptions, eliminating the need for complex organization or tagging. NeuralBox also offers visually similar image browsing, mirroring how the human brain organizes information. It provides efficient on-device and cloud storage, helping to unclutter main photo galleries by housing 'utility photos' like receipts or inspirational designs. The tool supports multiple capture methods, including a lock screen widget and automatic screenshot import, ensuring users can quickly save anything that catches their eye.

Non-overwhelming-machine-learning is an open-source project hosted on GitHub, offering a carefully curated list of machine learning resources specifically designed for beginners. The primary goal is to provide a "non-overwhelming" introduction to the field, guiding users through a chronological learning path. It assumes foundational knowledge in probability, multivariable calculus, and optimization, ensuring that learners have the necessary prerequisites before diving into more complex topics. The resource list includes introductory courses like "Intro to Machine Learning UD120," "Deep Learning @ Udacity," and specialized courses on convolutional neural networks and natural language processing. This structured approach helps beginners build a solid understanding without feeling overwhelmed by the vastness of machine learning.

ResearchBunny simplifies academic research by converting dense papers into bite-sized audio summaries available in over 18 languages. This platform is designed for students, researchers, and lifelong learners, enabling them to consume complex information while on the go. Key features include customizable playback options for speed, length (3, 6, or 9 minutes), and depth levels from Beginner to Advanced. Users can also create AI-powered research podcast playlists, ask 'Bunny' questions about papers, and receive tailored recommendations. ResearchBunny also provides 'RB Pages' to turn research into shareable, rich experiences and offers widgets for engaging audiences on personal research sites.

TensorFlow-and-DeepLearning-Tutorial is an open-source repository offering a collection of deep learning tutorials. Originally taught as an online course in 2016, it provides foundational knowledge in TensorFlow, fully connected neural networks, and convolutional neural networks. The resource also delves into Natural Language Processing concepts. Written primarily in Python and Jupyter Notebook, it serves as a valuable educational tool for individuals looking to understand and implement deep learning techniques.

Early Stage Co specializes in providing tailored AI solutions to drive innovation and growth for businesses. They offer a comprehensive suite of services including new product innovation, where they bring ideas to life with a team of engineers, designers, and product managers. Their AI consultancy helps businesses harness the power of artificial intelligence to achieve their goals, with a focus on improving bottom lines and reaching new customers. Additionally, Early Stage Co provides robust software development services, covering the full project lifecycle from conception to implementation, with flexible outsourcing models. They also excel in AI, ML, and data analytics, offering cloud AI services and bespoke strategies to unlock data's true potential.

FlashPaper is an AI writing tool designed to support students and researchers in academic writing tasks. It offers features for generating graduation theses within ten minutes, creating outlines, and paraphrasing text. The tool also includes functionalities for plagiarism detection, text rewriting, and citation generation. FlashPaper aims to simplify the academic writing process by providing AI-powered assistance for various stages, from initial topic generation and literature review to final paper refinement and formatting. It supports tasks like generating opening reports and literature reviews, making it a comprehensive aid for academic work.

transformers_tasks is an open-source project on GitHub that integrates various NLP algorithms using the powerful Hugging Face transformers library. It offers implementations for a wide range of tasks, including text matching (PointWise, DSSM, Sentence Bert, SimCSE), information extraction (UIE), prompt tasks (PET, p-tuning), and text classification (BERT-CLS). The project also delves into advanced areas like Reinforcement Learning from Human Feedback (RLHF) for language models, text generation (T5-Based models), and large language model (LLM) applications and training. It provides a flexible framework for researchers and developers to train and fine-tune models using their own datasets.

Transvribe was an AI-powered tool that enabled users to interact with YouTube videos by asking questions. It aimed to make learning from YouTube content more productive by leveraging AI embeddings to understand video content. Users could paste a YouTube URL and then query the video, effectively turning video content into an interactive knowledge base. However, due to significant changes in YouTube's internal API, which now requires session-specific authentication tokens and stricter validation, Transvribe is no longer functional. The developer has made the full codebase available on GitHub for those interested in exploring or potentially finding a solution to the new API restrictions.