Search Results for "artificial" - Page 34
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Showing 8130 open source projects for "artificial"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Torch-TensorRT is a compiler for PyTorch/TorchScript, targeting NVIDIA GPUs via NVIDIA’s TensorRT Deep Learning Optimizer and Runtime. Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate... -
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Determined
Determined, deep learning training platform
The fastest and easiest way to build deep learning models. Distributed training without changing your model code. Determined takes care of provisioning machines, networking, data loading, and fault tolerance. Build more accurate models faster with scalable hyperparameter search, seamlessly orchestrated by Determined. Use state-of-the-art algorithms and explore results with our hyperparameter search visualizations. Interpret your experiment results using the Determined UI and TensorBoard, and... -
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Prompt Master
A Claude skill that writes the accurate prompts for any AI tool
Prompt Master is a repository focused on organizing, managing, and optimizing prompts for AI systems, particularly large language models. It provides a structured way to store and reuse prompts, making it easier to maintain consistency and improve performance across different applications. The project emphasizes clarity and organization, allowing users to categorize prompts by use case, domain, or functionality. It also supports experimentation, enabling users to refine prompts and compare... -
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ScreenPipe
AI app store powered by 24/7 desktop history. open source
Screenpipe is an AI app store powered by continuous desktop history recording. It operates entirely locally, offering developers a platform to build, distribute, and monetize AI applications that leverage comprehensive contextual data from users' desktop activities. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MCP Server Simulator iOS IDB
Enables LLMs to interact with iOS simulators
The MCP Server Simulator for iOS IDB provides a bridge between Large Language Models (LLMs) and iOS simulators, offering comprehensive control through natural language commands. It enables operations such as launching apps, interacting with the UI, and retrieving device information, enhancing the capabilities of AI-driven development tools. -
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DevoxxGenie
DevoxxGenie is a plugin for IntelliJ IDEA that uses local LLM's
Devoxx Genie is a fully Java-based LLM Code Assistant plugin for IntelliJ IDEA, designed to integrate with local LLM providers such as Ollama, LMStudio, GPT4All, Llama.cpp, and Exo but also cloud-based LLMs such as OpenAI, Anthropic, Mistral, Groq, Gemini, DeepInfra, DeepSeek, OpenRouter and Azure OpenAI. -
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Large Language Models (LLMs)
Connect MATLAB to LLM APIs, including OpenAI® Chat Completions
This repository enables MATLAB to connect with large language models (LLMs) such as OpenAI's ChatGPT, DALL-E, Azure OpenAI, and Ollama, integrating their natural language processing and image generation capabilities directly within MATLAB environments. It facilitates creating chatbots, summarizing text, and image generation, among other tasks. -
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Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
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Lance
Modern columnar data format for ML and LLMs implemented in Rust
Lance is a columnar data format that is easy and fast to version, query and train on. It’s designed to be used with images, videos, 3D point clouds, audio and of course tabular data. It supports any POSIX file systems, and cloud storage like AWS S3 and Google Cloud Storage. -
One Monitoring Tool for IT, OT and Cloud | Free TrialModern infrastructure spans data centers, cloud platforms and factory floors, and every blind spot between them is a risk. PRTG supports SNMP, WMI, SSH and other standard protocols to monitor IT, OT and hybrid environments through one customizable dashboard. Build the views your team needs, from network health to application performance, without switching tools. Try PRTG free for 30 days now.
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Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch? -
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MindsDB
Making Enterprise Data Intelligent and Responsive for AI
MindsDB is an AI data solution that enables humans, AI, agents, and applications to query data in natural language and SQL, and get highly accurate answers across disparate data sources and types. MindsDB connects to diverse data sources and applications, and unifies petabyte-scale structured and unstructured data. Powered by an industry-first cognitive engine that can operate anywhere (on-prem, VPC, serverless), it empowers both humans and AI with highly informed decision-making... -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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Rasa
Open source machine learning framework to automate text conversations
Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build contextual assistants on Facebook Messenger, Slack, Google Hangouts, Webex Teams, Microsoft Bot Framework, Rocket.Chat, Mattermost, Telegram, and Twilio or on your own custom conversational channels. Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forths. In order for a human to have a meaningful exchange with a... -
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SAM 3
Code for running inference and finetuning with SAM 3 model
SAM 3 (Segment Anything Model 3) is a unified foundation model for promptable segmentation in both images and videos, capable of detecting, segmenting, and tracking objects. It accepts both text prompts (open-vocabulary concepts like “red car” or “goalkeeper in white”) and visual prompts (points, boxes, masks) and returns high-quality masks, boxes, and scores for the requested concepts. Compared with SAM 2, SAM 3 introduces the ability to exhaustively segment all instances of an... -
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Atomic Agents
Building AI agents, atomically
The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability. The framework provides a set of tools and agents that can be combined to create powerful applications. It is built on top of Instructor and leverages the power of Pydantic for data and schema validation and serialization. All logic and control flows are... -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs. -
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rwkv.cpp
INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model
Besides the usual FP32, it supports FP16, quantized INT4, INT5 and INT8 inference. This project is focused on CPU, but cuBLAS is also supported. RWKV is a novel large language model architecture, with the largest model in the family having 14B parameters. In contrast to Transformer with O(n^2) attention, RWKV requires only state from the previous step to calculate logits. This makes RWKV very CPU-friendly on large context lengths. -
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PaddlePaddle
PArallel Distributed Deep LEarning: Machine Learning Framework
PaddlePaddle is an open source deep learning industrial platform with advanced technologies and a rich set of features that make innovation and application of deep learning easier. It is the only independent R&D deep learning platform in China, and has been widely adopted in various sectors including manufacturing, agriculture and enterprise service. PaddlePaddle covers core deep learning frameworks, basic model libraries, end-to-end development kits and more, with support for both... -
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No AI slop
Removes 20+ patterns of AI slop from any piece of writing
No AI Slop is an open-source editing skill that identifies and removes more than 20 recurring patterns associated with generic AI writing. It targets formulaic contrasts, throat-clearing openings, false insight setups, dramatic fragments, vague attribution, inflated importance, and other recognizable habits. The skill improves clarity, grammar, sentence structure, active voice, and the use of concrete details without flattening the writer’s personal voice. It can also analyze a passage for... -
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VectorChord
Scalable, fast, and disk-friendly vector search in Postgres
VectorChord is an open-source vector database built for local and edge deployment. It supports efficient vector indexing and retrieval using ANN (approximate nearest neighbor) algorithms and is optimized for integration with LLM and AI applications. VectorChord is lightweight and can be embedded in a variety of environments for fast semantic search. -
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Box MCP Server
A Box model context protocol server to search, read and access files
Box MCP Server is a Model Context Protocol (MCP) server designed to facilitate searching, reading, and accessing files stored on the Box cloud storage platform. It enables seamless integration with Box, allowing for efficient file management and retrieval through MCP-compatible clients. -
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MCP Claude Code
MCP implementation of Claude Code capabilities and more
The MCP Claude Code server implements Claude Code-like functionality, allowing AI assistants to directly execute instructions for modifying and improving project files. It leverages the Model Context Protocol for seamless integration with various MCP clients. -
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Rust Docs MCP Server
Prevents outdated Rust code suggestions from AI assistants
The Rust Docs MCP Server fetches documentation for specified Rust crates, generates embeddings for the content, and provides an MCP tool to answer questions about the crate based on the documentation context. -
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MCP Server Playwright
MCP server for browser automation using Playwright
An MCP (Model Context Protocol) server that leverages Playwright to provide browser automation capabilities, enabling large language models (LLMs) to interact with web pages, take screenshots, and execute JavaScript within a real browser environment. -
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RL Games
RL implementations
rl_games is a high-performance reinforcement learning framework optimized for GPU-based training, particularly in environments like robotics and continuous control tasks. It supports advanced algorithms and is built with PyTorch.
