Research & Education

TechGIS is a creative software and tech service company that specializes in delivering innovative technological solutions by leveraging Artificial Intelligence, GIS, and advanced hardware. They focus on driving smarter decision-making and operational efficiency across multiple industries. Their services include developing custom AI tools for automating workflows, harnessing geospatial intelligence through maps and satellite data, and creating AI-driven digital marketing campaigns. TechGIS also offers web design and development services, ensuring a comprehensive digital transformation for businesses. They emphasize custom-built solutions, aligning with UN Sustainable Development Goals, and have a proven track record of successfully completing projects for government and private sectors.

Atomic Canyon is an AI search platform specifically designed for the nuclear energy sector, aiming to modernize operations and enhance efficiency through advanced AI. The platform utilizes the Nuclear Regulatory Commission's (NRC’s) database and supercomputing resources to understand and process nuclear terminology with unmatched precision. It offers Neutron, an intelligent NRC-trained solution that efficiently searches billions of pages of nuclear documentation, optimizes workflows, and provides an intuitive interface. Atomic Canyon is leading the first commercial deployment of on-site generative AI at a U.S. nuclear power plant in partnership with PG&E’s Diablo Canyon Power Plant, powered by NVIDIA’s advanced computing platform. Its secure AI solution transforms document search and retrieval, improving safety, reliability, and efficiency for nuclear power plants.

The Beijing Academy of Artificial Intelligence (BAAI) is a leading non-profit research institution dedicated to pushing the boundaries of AI. BAAI focuses on core technologies and original innovation, aiming to foster advancements across AI development policies, academic thought, theoretical foundations, top talent, and industrial ecosystems. The academy is known for its 'Wudao' series, 'Wujie' series, and various large models including large language models (BGE, Tele-FLM), multimodal large models (Emu, OmniGen, EVA, Painter, SegGPT, See3D, Bunny, VideoXL), life large models (Brainμ, OpenComplex, real-time twin heart computing model, C. elegans), and embodied large models. BAAI also develops open-source technology systems like FlagData, FlagOpen, FlagOS, and FlagEval, and actively builds an AI talent ecosystem through initiatives like the BAAI Scholars program and the BAAI Conference.

BEYOND GENOMiX is a Swiss deeptech startup specializing in the analysis of aging hallmarks to advance the diagnosis of age-associated diseases and facilitate drug discovery. The platform utilizes a comprehensive genomics pipeline to explore molecular patterns linked to telomere and senescence pathways. With world-leading high-throughput technology for telomere analysis and AI-powered senescence biomarker analysis, BEYOND GENOMiX identifies new patterns in age-related diseases. Their proprietary machine learning platform integrates multi-omics data from decades of clinical studies, providing actionable insights for therapeutics and diagnostics by performing end-to-end analysis of telomeres, senescence, and key genetic variants.

PyTorch is an open-source machine learning framework hosted by the Linux Foundation, designed to facilitate the transition from research prototyping to production deployment. It offers a user-friendly front-end, distributed training capabilities, and a rich ecosystem of tools and libraries. Key features include TorchScript for seamless transitions between eager and graph modes, TorchServe for deploying models at scale, and native support for distributed training. PyTorch also provides experimental mobile deployment workflows for iOS and Android, robust ecosystem tools for computer vision and NLP, and native ONNX export. It features a C++ front-end for high-performance applications and strong cloud platform support for frictionless development and scaling.

Rural Senses, founded at the University of Cambridge in 2019, offers a comprehensive AI platform designed for social and environmental impact measurement and management. The platform enables organizations to enhance their impact through data-driven insights, offering solutions for qualitative data collection on a quantitative scale, AI-powered data processing and analysis, and impact data visualization and management. Key features include voice-based mobile data collection, any-language transcription, natural language processing, and an AI-powered conversational assistant called "Ask Ngesa" for interacting with large volumes of impact data. It caters to NGOs, Foundations, and For-Profit Companies, providing customized impact solutions, including human-centric impact evaluation and AI-enhanced impact prediction.

Proxima, formerly known as VantAI, is an advanced AI-powered platform dedicated to revolutionizing drug discovery by decoding and designing the interfaces of life. The platform's mission is to make protein interactions programmable, focusing on inducers, modulators, and blockers. It features an integrated discovery platform built with three complementary, phase-shifting technologies designed to unlock the full potential of the proximity modulator modality. Proxima actively works with industry leaders and has recently announced significant collaborations and funding rounds, including an $80 million seed round. The company also hosts a lecture series on Generative AI in Drug Discovery, showcasing its commitment to advancing scientific understanding and application in the field.

The LabVIEW Deep Learning Module is a core component of Graiphic's SOTA software suite, providing a comprehensive AI development ecosystem. This module is designed to streamline the entire lifecycle of deep learning models, from initial development and training to integration and deployment. It offers seamless compatibility with popular deep learning frameworks such as PyTorch, TensorFlow, and Keras, leveraging the ONNX Runtime standard for interoperability. The module supports various hardware accelerators, including GPUs and FPGAs, to maximize performance across different platforms. Its integration within the LabVIEW environment allows engineers and researchers to develop industrial-grade AI pipelines with a graphical interface, making advanced AI accessible for applications in robotics, mobility, logistics, finance, and healthcare.

Happy Transformer is a Python library designed to make fine-tuning and performing inference with NLP Transformer models straightforward. It supports a range of natural language processing tasks including text generation, text classification, and question answering. The library is open-source and provides a user-friendly interface for developers and data scientists to integrate powerful AI capabilities into their applications. With upcoming version 4.0.0, it promises a complete rewrite with many new features, though users are advised to set their version to <4.0.0 for current stability. Happy Transformer is ideal for those looking to leverage transformer models without extensive setup, offering tutorials and examples for various use cases.

Mamba-Chat is a groundbreaking chat language model that leverages a state-space model architecture, distinguishing it from traditional transformer-based LLMs. Developed by redotvideo, it is based on Albert Gu's and Tri Dao's Mamba work and offers training and fine-tuning capabilities. The model, specifically Mamba-2.8B, has been fine-tuned on 16,000 samples from the HuggingFaceH4/ultrachat_200k dataset. This open-source project provides developers with the necessary code to run a CLI chatbot, a Gradio app, and fine-tune the base Mamba model, making it an excellent resource for experimenting with novel LLM architectures.

The MATLAB-Deep-Learning-Model-Hub is an open-source repository on GitHub offering a comprehensive collection of pretrained deep learning models specifically designed for use within the MATLAB environment. It covers a wide array of applications including computer vision tasks such as image classification, object detection, semantic segmentation, instance segmentation, image translation, pose estimation, 3D reconstruction, and video classification. Beyond vision, it also includes models for natural language processing (Transformers), audio analysis (embeddings, sound classification, pitch estimation, speech-to-text), and Lidar point cloud processing. This hub is ideal for researchers and developers looking to accelerate their deep learning projects by utilizing pre-trained models and applying transfer learning techniques.

Modern Computer Vision with PyTorch is an open-source code repository published by Packt, accompanying a book of the same name. It offers a hands-on approach to solving over 50 computer vision problems using PyTorch 1.x on real-world datasets. The repository includes code examples for training neural networks from scratch, implementing 2D and 3D multi-object detection and segmentation, generating digits and DeepFakes with autoencoders and GANs, and manipulating images using various GAN architectures. It also covers combining computer vision with natural language processing for OCR, image captioning, and object detection, and with reinforcement learning for building agents. The resource is ideal for beginners to PyTorch and intermediate-level machine learning practitioners.

spaCy is a powerful, open-source library for advanced Natural Language Processing (NLP) in Python and Cython. Designed for production use, it incorporates the latest research and provides pre-trained pipelines for over 70 languages, enabling tokenization and training. Key features include state-of-the-art speed, neural network models for tasks like tagging, parsing, named entity recognition, and text classification, as well as multi-task learning with transformers like BERT. It boasts a robust training system, easy model packaging, deployment, and workflow management, making it suitable for industrial-strength applications. spaCy is released under the MIT license, offering a comprehensive solution for developers and researchers working with NLP.

Blubridge operates as an independent AI research laboratory, dedicated to engineering advanced deep learning systems from foundational principles. The company specializes in providing enterprise-grade AI models, robust infrastructure, and comprehensive deployment solutions tailored for various business needs. Their expertise spans optimizing tokenization methods and refining AI systems to suit diverse applications, ensuring high performance and scalability. Blubridge focuses on modeling Artificial Intelligence Systems and their practical applications, offering cutting-edge solutions for organizations looking to leverage frontier AI research.

Momenta is a leading autonomous driving technology company focused on developing AI solutions for vehicles. They employ a unique scalable path combining a data-driven approach with iterating algorithms, referred to as their "flywheel approach." Their product strategy includes both mass-production-ready highly autonomous driving solutions, such as Mpilot and MSD for L2 to L2++ assisted driving features, and scalable robo-taxi services targeting full autonomy. These solutions are designed to enhance the safety, convenience, and efficiency of mobility, adapting across different vehicle models and market segments. Momenta's offerings aim to transform urban mobility by providing seamless, reliable, and comfortable rides in complex urban environments.

The Biomedical AI Lab at the University of North Texas is dedicated to leveraging machine learning to make significant advancements in medicine. Their core focus involves using wearable device analytics to assist clinicians in the treatment of various mobility disorders, alongside a broader application of AI to enhance health outcomes across different populations. The lab conducts research in areas such as Parkinson's Disease, incomplete spinal cord injury, transfemoral amputees, and cerebral palsy toddlers. Their applications include activity recognition, fall detection, real-time response systems, assessing activity quality, and posture recognition. They employ advanced ML techniques like predictive and unsupervised models, deep learning (CNN/RNN, Transformer architectures, autoencoders), Kubernetes/Docker orchestration, and Hidden Markov Models.

PyPOTS (pronounced "Pie Pots") is a comprehensive Python toolkit designed for machine and deep learning on partially-observed time series data. It addresses the common issue of missing values in real-world time series by offering a wide array of state-of-the-art neural network models for tasks such as imputation, classification, clustering, forecasting, and anomaly detection. The library is built to simplify complex data analysis, allowing engineers and researchers to focus on core problems rather than data preprocessing. PyPOTS integrates with an ecosystem of tools like TSDB for dataset loading, PyGrinder for simulating missing data patterns, and BenchPOTS for standardized performance evaluation. It also supports hyperparameter optimization for all neural network models, making it a robust solution for scientific analysis of incomplete industrial and irregularly-sampled multivariate time series.

Beam ATG, also known as Beam, offers an advanced credit decisioning platform leveraging open finance methodologies and artificial intelligence. The tool is designed to streamline loan applications, clarify eligibility, and enhance the overall lending experience, particularly for African communities. Key features include the ability to increase conversion rates, boost loan volume, and significantly decrease administrative costs through automation and machine learning. Beam also focuses on mitigating bad debt risk with advanced algorithms and data analytics, promoting responsible lending. It provides powerful and easy-to-use APIs to unify consistent data and automate credit analysis, navigating the complex African credit landscape.

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.

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.

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.

OccamzRazor is at the forefront of innovative drug discovery, leveraging advanced digital science and machine learning methods to accelerate the understanding and treatment of brain aging. The platform's primary focus is on Parkinson's disease, aiming to map out the complexities of the condition to develop effective cures. By applying sophisticated AI techniques, OccamzRazor seeks to enhance the efficiency and success rates of pharmaceutical research and development, moving beyond traditional approaches to unlock new therapeutic possibilities. This tool is designed for researchers and scientists in the pharmaceutical and biotech sectors who are dedicated to tackling neurodegenerative diseases.

GNNs-for-NLP is a comprehensive resource offering code examples and tutorial materials for applying Graph Neural Networks (GNNs) to Natural Language Processing (NLP) tasks. Originating from presentations at EMNLP 2019 and CODS-COMAD 2020, this GitHub repository provides practical implementations using PyTorch 1.x and TensorFlow 1.x, compatible with Python 3.x. It features simplified GCN model implementations, extensions for relation extraction and word embeddings, and additional resources like theoretical write-ups and recent GNN papers. This tool is ideal for researchers and students looking to understand and implement graph-based deep learning methods in NLP.

PharmaBug serves as a comprehensive global pharmaceutical directory, enhanced with advanced AI-powered discovery tools. The platform is specifically designed to accelerate research and development within the pharmaceutical industry. It offers a suite of tools aimed at streamlining critical processes such as target identification, lead optimization, and virtual screening. By leveraging artificial intelligence, PharmaBug facilitates faster and more efficient R&D cycles, helping researchers and companies bring new pharmaceutical solutions to market more quickly. Its focus on AI capabilities positions it as a valuable resource for those looking to innovate and optimize their drug discovery pipelines.