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Lists of open-source artificial intelligence software

Lists of open-source artificial intelligence software is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Lists of open-source artificial intelligence software rather than just read about it. In short: These lists include projects which release their software under open-source licenses and are related to artificial intelligence projects. These include software libraries, frameworks, platforms, and tools used for machine learning, deep learning, natural language processing, computer vision, reinforcement learning, artificial general intelligence, and more.

Key takeaways

  • Lists of open-source artificial intelligence software belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Lists of open-source artificial intelligence software to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Lists of open-source artificial intelligence software from memory before moving on to harder problems.

Reference excerpt

These lists include projects which release their software under open-source licenses and are related to artificial intelligence projects. These include software libraries, frameworks, platforms, and tools used for machine learning, deep learning, natural language processing, computer vision, reinforcement learning, artificial general intelligence, and more.

Agentic AI

Auto-GPT — experimental open-source autonomous GPT-based agent Hermes Agent — self-improving AI agent developed by Nous Research OpenClaw — autonomous task-executing AI agent

Agentic AI frameworks CrewAI — framework for building and orchestrating multi-agent AI systems LangChain — framework for building applications and agents powered by large language models Theia AI — framework for integrating AI capabilities and agents into integrated development environments (IDEs).

AI-assisted software development Codex CLI – AI coding agent and command-line interface developed by OpenAI. Cline – AI coding agent for IDEs and the command line. DeepSeek Coder – large language model designed for code generation and AI-assisted software development. goose – AI coding agent for the desktop and command line. Grok Build – SpaceXAI's terminal-based AI coding agent. OpenCode OpenHands — AI software development agent Zed – source-code editor with integrated AI-assisted development and agentic coding features.

AI hardware and inference acceleration

LLM inference and serving frameworks llama.cpp — library that can perform inference on various LLMs such as Llama, Mistral, Gemma, DeepSeek or Qwen. SGLang – framework for structured generation and high-performance LLM inference and serving vLLM – high-throughput inference engine for large language models using techniques such as PagedAttention Ollama – a software platform that enables easy deployment and interaction with many large language models locally.

Model formats and optimization toolkits ONNX – Open Neural Network Exchange format for interoperability between AI frameworks OpenVINO – Intel's toolkit for optimizing deep learning models for edge devices TensorRT-LLM — Nvidia toolkit for optimizing and deploying large language models on GPUs

Artificial neural networks

EDLUT – event-driven neural network simulator for large-scale spiking networks Emergent – cognitive modeling platform implementing neural networks Encog – machine learning framework for Java and C# supporting neural networks JOONE – Java-based neural network framework with modular architecture for learning tasks Nengo – Python library for building and simulating large-scale neural systems Neuroph – lightweight Java framework for creating neural networks OpenNN – C++ library for designing, training, and deploying neural networks SNNS – Stuttgart Neural Network Simulator, supports feedforward and recurrent neural networks

Convolutional neural networks (CNNs) AlexNet — pioneering CNN for image classification, won the 2012 ImageNet competition VGGNet — deep CNN known for its simplicity and use of 3x3 convolution filters Inception — CNN architecture using parallel convolutional layers of different sizes

State-space models Mamba – selective state-space model architecture for efficient sequence modeling

Chatbots

LAION OpenAssistant Mycroft

Cognitive architectures and AGI platforms

ACT-R – cognitive architecture for modeling human cognition and developing cognitive agents. CLARION – Connectionist Learning with Adaptive Rule Induction On-line, hybrid connectionist/symbolic cognitive architecture. OpenCog – project that aims to build an open source artificial intelligence framework Soar – cognitive architecture for decision-making and learning in intelligent agents

Computer vision and image processing

AForge.NET – computer vision, artificial intelligence, and robotics library for the .NET framework Dlib – C++ library for computer vision and image processing OpenCV — library of programming functions mainly for real-time computer vision Point Cloud Library – library for point cloud processing Tesseract – optical character recognition

Deep learning frameworks

BigDL – distributed deep learning library for Apache Spark Caffe – deep learning framework focused on speed and modularity Deeplearning4j – Java library for deep learning algorithms on the Java virtual machine DeepSpeed – deep learning optimization library developed by Microsoft fastai – deep learning library built on top of PyTorch Fast Artificial Neural Network (FANN) – C library for feedforward neural networks Horovod – distributed deep learning framework for TensorFlow, Keras, and PyTorch Keras – Python library for artificial neural networks Microsoft Cognitive Toolkit – deep learning framework developed by Microsoft Research MXNet – deep learning framework for training and deploying deep neural networks Neuroph – object-oriented artificial neural network framework written in Java OpenNN – artificial neural network library written in C++ PlaidML – deep learning backend for neural networks and tensor computations PyTorch – deep learning framework developed by Meta AI PyTorch Lightning – high-level framework built on top of PyTorch for organizing and scaling deep learning models TensorFlow – end-to-end open-source platform for machine learning and deep learning developed by Google Brain Torch – scientific computing framework with support for machine learning and deep learning algorithms

Machine learning or data mining

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Lists of open-source artificial intelligence software

Start with the simplest possible case. Write down what Lists of open-source artificial intelligence software claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Lists of open-source artificial intelligence software before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Lists of open-source artificial intelligence software ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Lists of open-source artificial intelligence software

In research
Lists of open-source artificial intelligence software appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Lists of open-source artificial intelligence software in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Lists of open-source artificial intelligence software is common in secondary-school and first-year university syllabi. It links to neighbouring topics Artificial intelligence, Free and open-source software, Free software, so understanding it makes those chapters shorter.
In everyday life
Look for Lists of open-source artificial intelligence software outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Lists of open-source artificial intelligence software in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Lists of open-source artificial intelligence software means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Lists of open-source artificial intelligence software out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Lists of open-source artificial intelligence software in simple terms?

These lists include projects which release their software under open-source licenses and are related to artificial intelligence projects. These include software libraries, frameworks, platforms, and tools used for machine learning, deep learning, natural language processing, computer vision, reinfo…

Why does Lists of open-source artificial intelligence software matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Lists of open-source artificial intelligence software?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Lists of open-source artificial intelligence software.

Tags

  • Artificial intelligence
  • Free and open-source software
  • Free software
  • Lists of software
  • Neural network software
  • Open-source artificial intelligence

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