Research & Education

squeezeDet is an open-source project providing a TensorFlow implementation of SqueezeDet, a convolutional neural network specifically designed for real-time object detection. This tool is particularly optimized for autonomous driving applications, emphasizing a unified, small, and low-power architecture. It allows users to train and evaluate object detection models using datasets like KITTI, supporting various network backbones such as SqueezeNet, ResNet50, and VGG16. The repository includes scripts for installation, demo execution, training, and validation, making it a comprehensive resource for researchers and developers working on efficient object detection in resource-constrained environments.

spark-py-notebooks is a comprehensive collection of IPython/Jupyter notebooks designed to educate users on various Apache Spark concepts using Python (pySpark). The tutorials range from fundamental to advanced topics, focusing on Big Data Analysis and Machine Learning. Users can learn about RDD creation, basic RDD operations like map, filter, and collect, sampling, set operations, and data aggregations. The collection also delves into working with key/value pair RDDs and introduces MLlib for basic statistics, exploratory data analysis, logistic regression, and decision trees. Additionally, it covers Spark SQL for structured processing with DataFrames and includes applications like building a movie recommendation web service.

SAMMY Labs offers a deterministic and interpretable AI solution for legal and compliance needs. It transforms regulatory statutes and internal operating procedures into powerful legal engines. These engines are designed to audit accounts, generate regulator-ready reports, and ensure continuous system compliance. Key features include the ability to train SAMMY with internal knowledge, create personalized SAMMY Guides for customer support in various platforms like Slack and email, and robust analytics to understand user responses and improve product offerings. The tool also integrates directly with Slack for quick guide creation and sharing. SAMMY Labs aims to provide a living brain that achieves human-level understanding of a company's products and processes.

BioSketch is a free, user-friendly drag-and-drop tool specifically designed for scientists and researchers to create high-quality scientific illustrations. It simplifies the process of building publication-ready figures by providing an extensive library of biomedical icons. Users can easily assemble complex diagrams and visuals without needing advanced graphic design skills. The platform aims to empower the scientific community to produce stunning and accurate visual representations of their research, enhancing communication and impact in academic publications and presentations.

NearGuru, a product of Vidhyalink Technologies, is a hyperlocal education platform designed to simplify how students discover quality learning guidance. It connects students with verified tutors and coaching centers in their vicinity, catering to various needs, goals, and budgets. The platform offers a wide range of courses, including boards, competitive exams, co-curricular activities, skill-based learning, and college courses. Key features include tracking learning journeys, monitoring performance, managing expenses, and access to 100% verified centers and certified tutors. NearGuru aims to empower students with quality education through expert-led learning, personalized guidance, and flexible scheduling options.

Sloth is an open-source tool specifically designed for labeling image and video data, primarily catering to the needs of computer vision research. It enables researchers and data scientists to efficiently annotate visual data, which is crucial for training machine learning models. The tool supports various annotation tasks, making it a versatile solution for creating high-quality labeled datasets. Its open-source nature means it can be freely used and adapted by the community, fostering collaboration and customization in computer vision projects. Sloth aims to simplify the often complex and time-consuming process of data annotation, facilitating the development of robust AI applications.

Bade Achhe Lagte Hain is a delightful brain training application specifically designed for Indian elders. This tool focuses on enhancing cognitive health by offering engaging and simple brain games. Users can sharpen their memory and math skills, with content available in both Hindi and English, making it accessible to a wider audience. The app aims to prevent cognitive decline and is designed to be free and easy to use, providing a joyful experience for senior citizens. It serves as a valuable resource for families looking to support their elders in maintaining mental sharpness and overall well-being.

Setup-NVIDIA-GPU-for-Deep-Learning is a comprehensive, open-source guide designed to assist users in setting up their NVIDIA GPUs for deep learning tasks. It outlines a clear, step-by-step process, starting with the installation of the latest NVIDIA GPU drivers. The guide then proceeds to cover essential software components such as Visual Studio with C++ support, Anaconda/Miniconda for package management, the CUDA Toolkit, and cuDNN. Finally, it provides instructions for installing PyTorch and includes a script to test the GPU setup, ensuring all components are correctly configured for optimal deep learning performance. This resource is invaluable for deep learning practitioners and AI researchers looking to streamline their development environment setup.

VitalMinute AI is a powerful meeting assistant designed for professionals and teams, enabling users to record any meeting and instantly receive structured minutes within 60 seconds. A key differentiator is its privacy-first approach, offering an On-Device Mode for complete data isolation where audio never leaves the phone, and designed for HIPAA compliance with strict encryption. The tool also boasts offline functionality, processing sessions locally without internet access for maximum security. It supports over 100 languages, providing perfectly structured summaries globally. VitalMinute can generate various formats, including Clinical SOAP Notes, Class Study Guides, and Meeting Highlights, making it versatile for different professional needs. It operates on a simple pay-as-you-go pricing model with credits that never expire, avoiding subscriptions or hidden fees.

Stanford-CS-221-Artificial-Intelligence is a comprehensive resource offering VIP cheatsheets for Stanford's CS 221 Artificial Intelligence course. This repository aims to consolidate all crucial notions covered in the course, including cheatsheets for each artificial intelligence field and an ultimate compilation of concepts. The material is accessible on a dedicated website, ensuring readability across various devices. Authored by Afshine Amidi and Shervine Amidi, it serves as an invaluable study aid for students and anyone interested in understanding core AI principles. The cheatsheets are available in English, French, and Turkish, making it accessible to a broader audience.

tf-gnn-samples is a GitHub repository offering TensorFlow implementations of various Graph Neural Network (GNN) architectures. It serves as the code release for an article introducing GNNs with feature-wise linear modulation (GNN-FiLM). The repository includes implementations for Gated Graph Neural Networks (GGNN), Relational Graph Convolutional Networks (RGCN), Relational Graph Attention Networks (RGAT), Relational Graph Isomorphism Networks (RGIN), GNN-Edge-MLP, and Relational Graph Dynamic Convolution Networks (RGDCN). It provides scripts for training and evaluating models on tasks such as citation networks (Cora, Pubmed, Citeseer), protein-protein interaction (PPI), quantum chemistry prediction (QM9), and variable misuse detection (VarMisuse). The code allows users to reproduce experimental results presented in the accompanying research paper, making it a valuable resource for researchers and developers working with GNNs.

A-dapt brings Emotion AI into LegalTech, providing lawyers with human-centered tools for scalable, privacy-first witness preparation and emotionally intelligent litigation training. Its TestMyWitness platform uses Emotional AI to prepare confident and credible witnesses by focusing on people, not paperwork. Key features include viewer emotion analysis, real-time emotional feedback during witness preparation, dynamic emotion labels, and "move the dot" coaching to improve composure. The platform also offers a transcript and annotation workspace with auto-generated Q&A, emotion tags, and sharable notes for follow-up coaching. It flags risk signals like hostility or low confidence, supporting legal teams in enhancing witness credibility before court or interviews. The system is designed for privacy, reduced bias, and eco-friendliness.

Abzu is a biotechnology company leveraging explainable AI to innovate in the field of RNA therapeutics. The company specializes in developing best-in-class RNA drugs, including siRNAs, ASOs, and anti-miRs, for significant medical needs. Their AI-guided design platform, powered by the QLattice®, allows for the in silico exploration and prioritization of vast sequence spaces, evaluating over 100,000 design variants to predict efficacy and developability properties. This approach significantly reduces experimental cycles, lowers costs, and shortens the time to candidate selection. Abzu also focuses on RNA-based delivery systems, developing targeted aptamers for cell-specific uptake of therapeutic RNA, offering a modular platform for precision delivery beyond the liver. The team combines deep RNA biology, AI-driven design, and drug development experience to create a closed learning loop where data refines models and models improve molecules.

Additive Catchments is dedicated to restoring river health by providing advanced infrastructure for water quality monitoring. The platform utilizes sensor networks to deliver real-time data, offering transparent insights and actionable intelligence crucial for effective water management. It aims to give rivers a voice by integrating environmental data, civic infrastructure, and pollution monitoring to create a comprehensive river health index. This tool is designed to support water governance and catchment management, enabling stakeholders to make informed decisions and build a sustainable future where rivers, communities, and society can thrive.

vec2text is an open-source library providing utilities for decoding deep representations, such as sentence embeddings, back into text. It enables users to train various architectures that reconstruct text sequences from embeddings and also run pre-trained models. The library supports both direct inversion from embeddings and inversion of text strings, with options to refine results through multiple steps and increased search space. It is particularly useful for researchers and developers working with text embeddings and language models, offering functionalities like interpolation of embeddings and detailed guidance on training custom inversion and corrector models.

ttt-rl is a reinforcement learning example implemented in C, designed to teach the basics of reinforcement learning through a tic-tac-toe game. The neural network learns to play against a random adversary from scratch, without any pre-existing knowledge of the game. It uses a simple architecture with a single hidden layer and is contained in under 400 lines of C code, with no external libraries. This project is particularly valuable for programmers, especially young programmers, who want to understand new fields through small, self-contained, and well-commented C programs. It demonstrates how RL can learn complex behaviors from basic reward signals.

TorchDrug is a robust, PyTorch-based machine learning platform specifically designed for drug discovery. It simplifies the implementation of graph operations in a PyTorchic style with GPU support, making it accessible even for practitioners with minimal drug discovery knowledge. The platform facilitates rapid prototyping of machine learning research by providing a wide range of common datasets and building blocks. Users can easily work with graph-structured data and molecules, extracting properties without deep domain expertise. TorchDrug also accelerates training and inference across multiple CPUs or GPUs, offering seamless scalability for complex experiments. It supports integration with Weights & Biases for experiment tracking and management.

Tensorflow-triplet-loss offers a robust implementation of triplet loss within the TensorFlow framework, specifically designed for metric learning tasks. It includes online triplet mining capabilities, which are crucial for training models that learn meaningful embeddings. The repository provides two main versions: "batch all" and "batch hard" triplet loss, allowing flexibility in how triplets are selected and processed. The code structure is adapted from CS230 assignments and is accompanied by tutorials, making it accessible for developers and researchers. It supports both CPU and GPU installations and includes scripts for training on datasets like MNIST, visualizing embeddings, and hyperparameter searching. This tool is ideal for those looking to implement or experiment with triplet loss for tasks such as face recognition or person re-identification.

Brightseed is a continuous innovation platform designed for health and life sciences companies. It unifies deep science, cutting-edge AI, and the world’s largest proprietary bioactive dataset to streamline the discovery, validation, and commercialization of new products. The platform helps teams identify and prioritize promising opportunities earlier, reducing guesswork and increasing confidence before significant investments are made. By replacing fragmented R&D workflows with a unified system, Brightseed accelerates progress from discovery to decision, leading to faster cycles, quicker time to market, and a higher probability of success for innovations. It empowers teams to deliver more successful innovations, faster, fueling sustainable growth and long-term differentiation.

Aikreate is an AI literacy platform designed to help middle and high school students understand artificial intelligence through active creation and experimentation. Instead of passively consuming AI, students build AI literacy by engaging in hands-on projects, games, and guided challenges. The platform offers two main products: the Kreate App for families, providing an interactive learning experience for at-home use, and Kreate Academy for schools and teachers, which delivers a classroom-ready AI curriculum. Developed by experienced educators and professors with affiliations to MIT and Babson College, Aikreate focuses on teaching how AI works, its limits, and its impact, fostering critical thinking and ethical understanding in young learners.

Braintain is an AI flashcard app designed to help users learn and retain information through visual anchors and spaced repetition. It offers "BrainPods," which are pre-packed flashcard collections with AI-generated images to make concepts stick. Users can also create their own custom flashcards and add images. The app incorporates a spaced repetition algorithm (SM-2) that schedules card reviews at optimal intervals based on user ratings, ensuring knowledge is moved into long-term memory. Available for free on iOS and Android, Braintain is ideal for language learners, students, and anyone looking to improve their memory and study habits.

X2Paddle is a deep learning model conversion tool developed under the PaddlePaddle ecosystem, designed to help users of other deep learning frameworks quickly migrate their models and projects to PaddlePaddle. It supports the conversion of prediction models from major frameworks like Caffe, TensorFlow, ONNX, and PyTorch. Additionally, X2Paddle facilitates the migration of entire PyTorch training projects, including both training and prediction code, to the PaddlePaddle framework. The tool offers detailed API comparison documentation to reduce the time and effort developers spend on migrating models. It boasts support for a wide range of models, covering over 130 PyTorch OPs, 90 ONNX OPs, 90 TensorFlow OPs, and 30 Caffe OPs, making it a comprehensive solution for model migration.

Cypher AI offers intelligent digital infrastructure tailored for modern biology and life science R&D. It addresses the need for real-time adaptable systems by generating experimental designs, managing sample tracking, and integrating instruments. The platform also orchestrates analysis pipelines and CRO (Contract Research Organization) activities on demand, streamlining complex research processes. This allows scientists to accelerate discovery and innovation by providing a comprehensive solution for managing and executing biological research, from initial design to final analysis.

Text2Human is an official PyTorch implementation for text-driven controllable human image generation, as presented in the SIGGRAPH 2022 paper. This open-source tool enables users to create human images by providing text descriptions that specify clothing shapes and textures. It includes a comprehensive framework for training and sampling, utilizing a large-scale, high-quality DeepFashion-MultiModal Dataset with rich multi-modal annotations. Researchers and developers can leverage its capabilities for tasks like generating images from parsing maps or human poses, and it offers a user interface for interactive text-to-human image generation. The project also provides pretrained models and detailed installation instructions, making it a valuable resource for AI research in computer graphics.