Coding & Development

Data Wizards is an AI consulting firm specializing in helping corporates and ambitious SMEs unlock their business potential through expert AI solutions. They provide comprehensive services including AI strategy development, AI solution and development, and AI education. Data Wizards builds high-performing AI solutions to overcome challenges, streamline operations, and identify new growth opportunities. Their expertise spans various industries such as Automotive, Retail, Pharmaceutical, Manufacturing, Insurance, Financial, Logistics, Energy, Healthcare, Telecommunications, Media, SMEs, Security, Commodity, and Food, offering tailored applications like predictive maintenance, sales forecasts, customer churn analysis, and fraud detection.

ShortGPT is a Chrome extension designed to enhance the ChatGPT experience by delivering faster and more concise responses. Users can easily integrate this tool into their browser by downloading and installing the extension. Once activated, ShortGPT modifies ChatGPT's output, making it more efficient and to-the-point. This is particularly useful for users who require quick summaries or streamlined information without lengthy explanations. The extension aims to improve productivity by reducing the time spent sifting through verbose AI-generated content, providing a more direct interaction with ChatGPT.

Magic is an open-source, enterprise-grade AI agent platform designed to address the challenges of deploying AI at scale within organizations. It offers a comprehensive suite of tools including a generalist AI agent, a robust workflow engine, integrated instant messaging, and an online collaborative office system. Magic focuses on security, control, and direct business outcomes, enabling autonomous 24/7 operation. It tackles issues like data fragmentation, unpredictable API costs, data security risks, and the need for human approval for high-risk actions. The platform allows for the creation of digital employees by encapsulating internal systems and domain expertise, transforming AI output into finished deliverables like PPTs, dashboards, and Excel files. Magic is built to scale from solo founders to large enterprises, providing granular cost control, human-in-the-loop oversight, and team-wide collaboration features, all while being compatible with Anthropic and OpenClaw Skills ecosystems.

N-BEATS is a neural-network based model designed for univariate time series forecasting, open-sourced by ServiceNow Research and originally developed at Element AI. This repository provides a PyTorch implementation of the N-BEATS algorithm, allowing users to reproduce the experimental results detailed in the associated research paper. It includes model architecture, dataset loaders for various datasets used in the paper, and experimental configurations for both generic and interpretable models. The project emphasizes reproducibility and provides instructions for setting up the environment using Docker, running experiments on CPU or GPU, and analyzing results via Jupyter notebooks. It's a valuable resource for researchers and data scientists working with time series forecasting.

The TensorFlow Model Optimization Toolkit is a comprehensive suite of tools designed to optimize machine learning models for efficient deployment and execution. It supports popular frameworks like Keras and TensorFlow, offering techniques such as quantization and pruning for sparse weights. This toolkit is suitable for both novice and advanced users looking to improve model performance and reduce resource consumption. It provides stable Python APIs and extensive documentation, including tutorials and API references, available on the TensorFlow website. The project encourages community contributions and adheres to TensorFlow's code of conduct, with dedicated maintainers for subpackages like clustering, quantization, and sparsity.

PseudoEditor offers a free online integrated development environment (IDE) specifically designed for writing and compiling pseudocode. It aims to simplify the process of writing pseudocode by providing features such as dynamic syntax highlighting for keywords, functions, and data types, as well as autocomplete functionality. The platform includes an advanced pseudocode compiler that allows users to test and verify their pseudocode with instant execution. Users can save their projects to the cloud by creating a free account, enabling access and editing from any device. PseudoEditor supports various pseudocode variations and styles, including major exam board specifications like AQA, OCR, CIE, Edexcel, and IB, with toggleable syntax rules. A Pro version is available, offering an AI Tutor, intelligent code generators, and code converters to languages like Python and C++, along with an ad-free experience.

Stock-trading-ml is an open-source stock trading bot designed to leverage machine learning for making stock price predictions. This tool allows users to train their own models, edit model architectures, and customize dataset preprocessing. It supports Python 3.5+ and relies on libraries such as alpha_vantage, pandas, numpy, sklearn, keras, tensorflow, and matplotlib. Users can save stock price history to CSV files, train models using either basic or technical indicator approaches, and then apply a trading algorithm based on the newly saved model. The project is available on GitHub under the GPL-3.0 license, making it accessible for developers and data scientists interested in algorithmic trading.

Machine-Learning-in-Action is an open-source GitHub repository offering practical code implementations for various machine learning algorithms, all based on the popular book "Machine Learning in Action." Developed in Python 3, this resource is designed to help users understand and apply machine learning concepts through hands-on examples. The repository includes code for algorithms such as K-Nearest Neighbors, Decision Trees, Naive Bayes, Logistic Regression, Support Vector Machines, AdaBoost, and different regression techniques. It also provides datasets to accompany the code, making it a comprehensive learning resource for students and developers looking to deepen their understanding of machine learning.

ShallowCodeResearch is a coding research assistant designed to generate secure Python code. It takes user requests and context to produce functional code, with a strong emphasis on security. The tool actively prevents the use of dangerous functions and modules, ensuring the generated code is safe for deployment. Additionally, it incorporates print statements within the code to enhance readability and aid in understanding its execution flow. This makes it a valuable resource for developers and researchers looking for secure and understandable Python code solutions.

Reproducible-Deep-Compressive-Sensing is a comprehensive collection of source code dedicated to deep learning-based compressive sensing (DCS). This repository categorizes and provides access to numerous research works, offering links to their respective source code, PDF papers, and DOIs. The collection is organized based on key characteristics such as sampling matrix type (frame-based/block-based), sampling scale (single scale, multi-scale), and the deep learning platform used. It also includes code for image and video reconstruction, as well as other related applications. This resource is invaluable for researchers and developers looking to explore, reproduce, or build upon existing deep learning models in compressive sensing.

NotCentralised is a software development company dedicated to transforming complex technologies, including AI and Web3, into simple yet powerful solutions. Their core mission is to enhance work efficiency and provide deeper insights for businesses. They specialize in developing unique solutions tailored to specific challenges, rather than offering one-size-fits-all products. While the website doesn't detail specific AI tools or platforms, it emphasizes their approach to solving problems differently through advanced technological integration. They aim to help organizations streamline operations and gain a competitive edge by leveraging cutting-edge AI and Web3 capabilities.

ROSA (Robot Operating System Agent) is an AI Agent developed by NASA JPL, designed to facilitate interaction with ROS1- and ROS2-based robotics systems through natural language queries. Built on the Langchain framework, ROSA empowers robot developers to inspect, diagnose, understand, and operate robots more efficiently. It supports custom agent creation, allowing for adaptation to various robots and environments, and offers features like identifying topics with publishers but no subscribers. The tool includes a TurtleSim demo for controlling a simulated robot and is actively developing an IsaacSim extension for direct integration and control within the simulation environment.

My Zodiac AI Relationship App is a mobile application designed to provide personalized astrological insights using artificial intelligence. It assists users in understanding their personality through detailed natal charts and offers daily horoscopes. The app also aims to guide users in navigating their personal growth and connections by providing deep relationship compatibility analysis based on cosmic wisdom. This tool is intended to help individuals gain a better understanding of themselves and their relationships through the lens of astrology and AI.

Productbox is a specialized software engineering studio focused on building secure, robust, and HIPAA-compliant digital health products. They provide end-to-end software development services, enabling clients to address the complex challenges of healthcare. Their offerings include product conceptualization, design, and development, ensuring solutions meet business needs beyond just technical requirements. Productbox also excels in architecture and design, system integration, and ongoing technical support. With a strong emphasis on AI/ML, they leverage cutting-edge technologies to create disruptive web and mobile applications, committed to delivering equitable and affordable healthcare solutions through robust and scalable digital platforms.

PyTriton is a Flask/FastAPI-like framework designed to streamline the use of NVIDIA's Triton Inference Server within Python environments. It allows developers to serve machine learning models with ease, supporting direct deployment from Python. Key features include native Python support for exposing any Python function as an HTTP/gRPC API, framework-agnostic operation compatible with PyTorch, TensorFlow, or JAX, and performance optimizations like dynamic batching, response caching, and model pipelining. The tool also provides decorators for handling batching and pre-processing, high-level model clients for HTTP/gRPC requests, and alpha support for streaming partial responses.

RQ-VAE-Recommender offers a PyTorch implementation of a generative retrieval model, specifically designed for recommender systems. The model operates in two stages: first, it maps items in a corpus to a tuple of semantic IDs by training an RQ-VAE. Second, it tokenizes sequences of these semantic IDs using a frozen RQ-VAE and then trains a transformer-based model to predict the next IDs in the sequence. This approach is based on the research presented in "Recommender Systems with Generative Retrieval." It supports various datasets, including Amazon Reviews (Beauty, Sports, Toys), MovieLens 1M, and MovieLens 32M, and provides both RQ-VAE and decoder-only retrieval model training scripts. Pre-trained checkpoints are available on Hugging Face for Amazon Beauty.

Agent-ui is a modern chat interface designed for interacting with AI agents, built using Next.js, Tailwind CSS, and TypeScript. It offers seamless integration with local and live AgentOS instances through the Agno platform. Key features include a clean chat interface with real-time streaming, support for visualizing agent tool calls and their results, and the ability to display agent reasoning steps when available. It also handles multi-modality content like images, video, and audio, and provides references used by the agent. The UI is customizable with Tailwind CSS, and it's built on a modern stack including shadcn/ui and Framer Motion. Users can easily connect to their AgentOS instances, configure endpoints, and set up authentication.

Applying_EANNs is a 2D Unity simulation designed to showcase how cars can learn to navigate various courses. The cars are controlled by a feedforward neural network, whose weights are optimized using a modified genetic algorithm. This project provides a practical demonstration of evolutionary artificial neural networks in a simulated environment. Users can tinker with simulation parameters in the Unity Editor or run the built executable with default settings. The neural network architecture includes an input layer, two hidden layers, and an output layer, with its training managed by a customizable genetic algorithm. The user interface displays real-time data for the best performing car, including neural network output, evaluation value, and a generation counter, along with a visual representation of the neural network's weights.

awesome-vision-language-pretraining-papers is a curated collection of recent advancements in Vision and Language PreTrained Models (VL-PTMs). Maintained by WANG Yue, this GitHub repository provides an organized list of academic papers covering image-based, video-based, and speech-based VL-PTMs. It categorizes papers into areas like Representation Learning, Task-specific applications, and Analysis, offering direct links to papers and their associated code where available. The resource also includes sections for other transformer-based multimodal networks and additional relevant surveys and reading lists, making it an invaluable resource for researchers and practitioners looking to stay updated on the latest developments in multimodal AI.

AI.io specializes in 'white box' AI solutions, which combine black box AI processing with tailored applications to deliver explainable and actionable insights. The platform is designed for enterprise clients in sectors like healthcare, entertainment, and travel, aiming to augment human intelligence and improve decision-making. By focusing on propensity modeling, ad targeting, predictive analysis, and lead scoring, AI.io helps businesses achieve better conversion rates, increased revenues, and reduced expenses. Its approach emphasizes useful and understandable results, ensuring privacy protection and accountability in AI applications.

Freeplay is an ops platform designed for AI engineering teams, offering a comprehensive workflow to build, test, observe, and iterate on AI products. It integrates observability, evaluations, and testing into a continuous improvement loop, allowing teams to understand agent performance and quickly iterate. Key features include tracing completions, tool calls, and agent steps, instant log search, automatic traffic categorization, and turning production logs into test cases. The platform supports custom evaluations, prompt management, and AI feature reviews, ensuring confidence in shipping AI products. Freeplay is trusted by leading AI teams and offers enterprise-grade security, flexible deployment options, and expert support from AI engineers.

Fujitsu AutoML is an automated machine learning platform hosted on Hugging Face Spaces, designed to streamline the process of model development and data analysis. This open-source tool allows users to create and display interactive web applications by providing their code, which then generates a web interface for interaction. It is particularly useful for those looking to leverage AutoML capabilities in a collaborative and accessible environment. The platform operates under the Apache 2.0 license, making it a free and flexible option for data scientists and machine learning engineers to experiment with and deploy AI models.

Moonlite AI delivers high-performance AI infrastructure designed for enterprise-grade performance and compliance, specifically targeting demanding AI workloads such as computational research, distributed model training, and large-scale data processing. The platform offers the flexibility to deploy infrastructure within existing data center facilities or in Moonlite's own facilities, combining bare-metal performance with cloud-native simplicity. Key features include purpose-built compute infrastructure optimized for parallel processing and distributed workloads, high-performance networking with RDMA and InfiniBand, and tiered storage solutions. Moonlite also emphasizes compliance by design, with built-in network isolation, enterprise controls, and certifications like SOC 2, ISO 27001, and ISO 42001, ensuring regulatory requirements are met.

Aival offers independent Quality Assurance systems designed for healthcare organizations to evaluate and monitor AI products. Its vendor- and platform-neutral software allows hospitals to objectively assess and compare AI solutions using their local data. This ensures that AI tools work effectively and safely for patients, building trust in their adoption. Aival also provides continuous monitoring of AI product performance to guarantee ongoing reliability once in use, helping teams make informed procurement decisions and maintain the benefits of AI over time. The Aival Analysis Lab suite can be installed on-site to standardize AI assurance processes.