Showing 20 open source projects for "artificial evolution"

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  • 1
    AIBuildAI

    AIBuildAI

    An AI agent that automatically builds AI models

    AI-Build-AI is an open-source framework focused on enabling autonomous systems that can design, generate, and improve AI applications with minimal human intervention. The project explores recursive AI development, where models are used not only as tools but as builders capable of constructing other AI systems, workflows, or components. It provides a structured environment for orchestrating agents that can plan, execute, and refine tasks such as code generation, system design, and iterative...
    Downloads: 2 This Week
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  • 2
    Wan Move

    Wan Move

    Motion-controllable Video Generation via Latent Trajectory Guidance

    Wan Move is an open-source research codebase for motion-controllable video generation that focuses on enabling fine-grained control of motion within generative video models. It is designed to guide the temporal evolution of visual content by leveraging latent trajectory guidance, allowing users to manipulate how objects move over time without modifying the underlying generative architecture. By representing motion information as dense point trajectories and integrating them into the latent...
    Downloads: 2 This Week
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  • 3
    ShoppingAgent

    ShoppingAgent

    Custom Chinese chatbot with Seq2Seq, GPT, and agent features

    ShoppingAgent is an open source Chinese conversational AI system that allows users to build and train their own chatbot using custom datasets. It provides multiple implementations of chatbot architectures, including traditional Seq2Seq models as well as newer GPT-style approaches, reflecting the evolution of conversational AI techniques. ShoppingAgent is structured to support experimentation across different deep learning frameworks such as TensorFlow, PyTorch, and MindSpore, giving...
    Downloads: 3 This Week
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  • 4
    Aden Hive

    Aden Hive

    Outcome driven agent development framework that evolves

    Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can...
    Downloads: 1 This Week
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  • 5
    EvoAgentX

    EvoAgentX

    Self-evolving AI agent framework for automated workflows

    EvoAgentX is an open source framework for building, evaluating, and continuously improving LLM-based agents and multi-agent workflows. It moves beyond static pipelines by introducing a self-evolving system where agents are automatically generated, tested, and optimised through iterative feedback. Developers can define goals in natural language, while the framework handles workflow creation, execution, and refinement. Its modular architecture supports layered components for agents, workflows,...
    Downloads: 4 This Week
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  • 6
    OpenSage

    OpenSage

    An agent framework that enables AI to create their own agent

    OpenSage is an emerging open-source AI agent development framework designed to automate the creation, orchestration, and evolution of intelligent agents through a self-programming paradigm. Unlike traditional agent frameworks that require developers to manually define workflows, tools, and structures, OpenSage introduces a system where large language models can dynamically generate their own agent architectures, including sub-agents, toolchains, and execution strategies. The framework is...
    Downloads: 0 This Week
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  • 7
    AtomAI

    AtomAI

    Deep and Machine Learning for Microscopy

    AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless...
    Downloads: 0 This Week
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  • 8
    PDP Astronomical Image Framework

    PDP Astronomical Image Framework

    Quantum Cosmology & Astrophysics Unified Suite (QCAUS)

    A collection of four interconnected open‑source projects that explore the quantum nature of the universe – from the early cosmos to extreme astrophysical environments. 📸 Live Demo The application is deployed on Streamlit Cloud: Live App test now: https://w7xsyujq7jzxrftum8xzcj.streamlit.app/ QCI AstroEntangle Refiner – FDM soliton physics & image processing Magnetar QED Explorer – Magnetar fields, dark photons & vacuum QED Primordial Photon–DarkPhoton Entanglement –...
    Downloads: 0 This Week
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  • 9
    Style Aligned

    Style Aligned

    Official code for Style Aligned Image Generation via Shared Attention

    StyleAligned is a diffusion-model editing technique and codebase that preserves the visual “style” of an original image while applying new semantic edits driven by text. Instead of fully re-generating an image—and risking changes to lighting, texture, or rendering choices—the method aligns internal features across denoising steps so the target edit inherits the source style. This alignment acts like a constraint on the model’s evolution, steering composition, palette, and brushwork even as...
    Downloads: 0 This Week
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  • 10
    ConvNeXt V2

    ConvNeXt V2

    Code release for ConvNeXt V2 model

    ConvNeXt V2 is an evolution of the ConvNeXt architecture that co-designs convolutional networks alongside self-supervised learning. The V2 version introduces a fully convolutional masked autoencoder (FCMAE) framework where parts of the image are masked and the network reconstructs the missing content, marrying convolutional inductive bias with powerful pretraining. A key innovation is a new Global Response Normalization (GRN) layer added to the ConvNeXt backbone, which enhances feature...
    Downloads: 5 This Week
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  • 11
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical...
    Downloads: 0 This Week
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  • 12
    DomE

    DomE

    Implements a reference architecture for creating information systems

    ...Thus, an alternative to the traditional software production processes is proposed, which involves several stages and different actors, sometimes demanding a lot of time and money without obtaining the expected result. With software engineering techniques, self-adaptive systems, and artificial intelligence, it is possible, the integration between design time and execution time.
    Downloads: 0 This Week
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  • 13
    Ad-papers

    Ad-papers

    Papers on Computational Advertising

    The Ad-papers repository is a curated collection of influential research papers focused on the fields of advertising technology, recommendation systems, and applied machine learning in online platforms. The repository organizes academic and industry papers that explore how machine learning algorithms can be used to improve ad targeting, user modeling, click-through rate prediction, and personalized recommendation systems. These papers represent key developments in large-scale industrial...
    Downloads: 0 This Week
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  • 14
    A Machine Learning Course with Python

    A Machine Learning Course with Python

    A course about machine learning with Python

    ...In this project you will learn what is the definition of Machine Learning? When it started and what is the trending evolution? What are the Machine Learning categories and subcategories? What are the mostly used Machine Learning algorithms and how to implement them?
    Downloads: 0 This Week
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  • 15
    DetectAndTrack

    DetectAndTrack

    The implementation of an algorithm presented in the CVPR18 paper

    DetectAndTrack is the reference implementation for the CVPR 2018 paper “Detect-and-Track: Efficient Pose Estimation in Videos,” focusing on human keypoint detection and tracking across video frames. The system combines per-frame pose detection with a tracking mechanism to maintain identities over time, enabling efficient multi-person pose estimation in video. Code and instructions are organized to replicate paper results and to serve as a starting point for researchers working on pose in...
    Downloads: 0 This Week
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  • 16
    Evoversum
    This project has been moved to https://bitbucket.org/pbazant/evoversum/src/master/ . Evoversum is a fast Darwinian evolution simulator. The program simulates a 2D world populated with "animals" which struggle for food, reproduce and may also eat each other. The subject of evolution is their behavior, which may become quite complex. There is an updated video tutorial at http://www.youtube.com/watch?v=nPkZvyVDWJU !
    Downloads: 0 This Week
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  • 17
    This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.
    Downloads: 0 This Week
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  • 18
    Ouroborus is an artificial life framework for mobile agents on a background of cellular automata. It can be used to teach and research topics such as population genetics, ecology and evolution. The demo includes a curses view and live Csound audio.
    Downloads: 0 This Week
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  • 19
    We experiment with Evolution of Artifical Neural Networks, combining the two fields of Evolutionary Computation and ANNs. Our methods are applied to a variety of interesting problems. To learn more, click on "Home Page", "Mail", or "Files".
    Downloads: 0 This Week
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  • 20
    Mistral Small 4

    Mistral Small 4

    Model that fuses instruct, reasoning and agentic skills

    The Mistral Small 4 collection is a set of open-weight large language models developed by Mistral AI that aim to unify multiple capabilities, including instruction following, reasoning, and coding, within a single efficient architecture. These models are part of the broader Mistral Small family, which is designed to deliver strong performance across a wide range of everyday AI tasks while maintaining relatively low latency and efficient deployment requirements. The collection reflects an...
    Downloads: 0 This Week
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