Search Results for "self learning ai"
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Showing 19 open source projects for "self learning ai"
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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LearnOpenCV
C++ and Python Examples
...The repository supports beginners and advanced practitioners by offering reproducible code that demonstrates real-world computer vision techniques. Many examples integrate popular frameworks like PyTorch, OpenCV, and ONNX to reflect modern AI workflows. Overall, LearnOpenCV functions as a comprehensive applied learning hub for developers building expertise in computer vision and AI. -
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Cactus
Low-latency AI inference engine optimized for mobile devices
Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing large models to run within the constraints of mobile hardware. ... -
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FLUX.2-klein-4B
Flux 2 image generation model pure C inference
FLUX.2-klein-4B is a compact, high-performance C library implementation of the Flux optimization algorithm — an iterative approach for solving large-scale optimization problems common in scientific computing, machine learning, and numerical simulation. Written with a strong emphasis on simplicity, correctness, and performance, it abstracts the core logic of flux-based optimization into a minimal C API that can be embedded in broader applications without pulling in heavy dependencies. Because... -
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Databend
Cloud-native open source data warehouse for analytics and AI queries
...Databend supports SQL-based workflows and enables real-time data ingestion, transformation, and analysis through streaming and task orchestration features. With its cloud-native design and distributed architecture, Databend can run both as a self-hosted system or within managed environments to power data analytics, AI workloads, and large-scale data. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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fairseq2
FAIR Sequence Modeling Toolkit 2
fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. -
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LLMFarm
llama and other large language models on iOS and MacOS offline
...It emphasizes modularity, allowing users to integrate different models, backends, or tools depending on their needs and hardware capabilities. LLMFarm is particularly useful for developers and researchers experimenting with local AI systems, as it lowers the barrier to entry for running and testing models without extensive setup. It also supports optimization techniques to improve performance on limited hardware, making it viable for smaller-scale deployments. -
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SynaptaOS
Synapta OS is a preconfigured educational Linux distribution with AI
🌐 Synapta OS Synapta OS is an educational Linux distribution preconfigured with local Artificial Intelligence (AI) capabilities. It is designed for schools and remote areas where Internet connectivity is limited or unavailable, offering access to AI-based learning and digital tools offline. Version 1.4.6 -
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Amoeba
Linux Command Line Learning Program
Amoeba is a Linux command-line learning program that observes and adapts to the Linux command line storing learned strings and their usage data. It enhances command-line proficiency by capturing command outputs, adapting string lengths, and periodically saving knowledge. Sandboxing is essential for security, and optionally a virtual machine would further isolates it from the host system. Contributions and improvements are encouraged via the GitHub repository. -
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MuJoCo-py
mujoco-py allows using MuJoCo from Python 3
mujoco-py is a Python wrapper for MuJoCo, a high-performance physics engine widely used in robotics, reinforcement learning, and AI research. It allows developers and researchers to run detailed rigid body simulations with contacts directly from Python, making MuJoCo easier to integrate into machine learning workflows. The library is compatible with MuJoCo version 2.1 and supports Linux and macOS, while Windows support has been deprecated. It provides utilities for loading models, running simulations, and accessing simulation states in real time, along with visualization tools for rendering environments. ... -
Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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DeepMind Lab
A customizable 3D platform for agent-based AI research
DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. DeepMind Lab provides a suite of challenging 3D navigation and puzzle-solving tasks for learning agents. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning. If you use DeepMind Lab in your research and would like to cite the DeepMind Lab environment, we suggest you cite the DeepMind Lab paper. To... -
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EVEAI is a Deep Learning Library based on python Keras and Tensorflow. EVEAI dll allows embedding inference images from keras models into user-written applications. Under Windows, the EVEAI training Tool provides services to train user specific image datasets and EVEAI dll provides services to existing Windows applications which support inference images. Please visit https://github.com/Hommoner/EVEAI for more information.
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DarkForestGo
DarkForest, the Facebook Go engine
darkforestGo is an early deep-reinforcement-learning Go engine that combined a convolutional policy/value network with Monte Carlo Tree Search (MCTS) to play the full 19×19 game at a strong amateur level. The system couples fast GPU policy inference with CPU or GPU-assisted tree search so priors from the network guide exploration while search refines local tactics. Training pipelines mix supervised learning from human professional games and self-play fine-tuning, allowing the model to learn opening patterns and endgame tactics beyond simple pattern libraries. ... -
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Grenade
Deep Learning in Haskell
Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only... -
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Tic Tac Toe (Autonomous) Dhaval Kadia
Experience AI ( Computer Plays with You ) !
SmartPrediction-ENGINE inside Enhanced with Artificial Intelligence Based upon Game Theory Still This is in BETA Phase -
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SimpleAiBot
A simple chat bot project for educational purposes! (OS X Only)
SimpleAiBot is created for educational purposes but it can grow out to something much bigger, however still educational. This project exists so other people can actually look at the code of a working chat bot and learn from it or even improve SimpleAiBot! If you're looking for this: this is it! Also don't hesitate to join and improve SimpleAiBot, better make your changes public and usable to everyone then experimenting on your own. PS: More experienced AI developers are also welcome to... -
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A packet dissector driven by machine learning algorithms. You train it to recognize specific types of packets by showing it examples and counterexamples of some packet type, and it will figure out which bits in the packet define it as the type you seek.
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Vehikel is a learning environment for behavior based control of mobile robots. A little bit artificial intelligence based on a domain specific language for the c't Bot.
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Wa (word analysis) engine is a engine implementing common IA algorithms such as in-depth tree search using alpha-beta.
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EveAI processes the data assuming that it has already been read by a sensor. Theoretically this should give it reflex behavior. Now the end product should be a self conscious machine future plans are to include the field of robotics.
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