Search Results for "brain"
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Showing 43 open source projects for "brain"
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TRIBE v2
A multimodal model for brain response prediction
...This combined representation is mapped onto the cortical surface to predict fMRI responses across thousands of brain regions. TRIBE v2 allows researchers to simulate and analyze brain activity without requiring direct human experiments. Overall, it provides a powerful tool for studying perception, cognition, and multimodal processing in the brain. -
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second-brain-ai-assistant-course
Learn to build your Second Brain AI assistant with LLMs
The Second Brain AI Assistant Course is an open-source educational project designed to teach developers how to build a personal AI assistant that interacts with a user’s knowledge base. The course provides a structured curriculum that walks learners through the architecture and implementation of a production-ready AI system powered by large language models. -
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Quivr
Your Second Brain supercharged by Generative AI
Quivr, your second brain, utilizes the power of GenerativeAI to store and retrieve unstructured information. Think of it as Obsidian, but turbocharged with AI capabilities. -
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Khoj
An AI personal assistant for your digital brain
...You can build faster and better by using Khoj to search and reason across all your data sources. Khoj learns from your notes and documents to function as an extension of your brain. So that you can stay focused on doing what matters. Khoj started with the founding principle that a personal assistant be understandable, accessible and hackable. This means you can always customize and self-host your Khoj on your own machines. -
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Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector stores for fine-grained chunks, chapter summaries, and book quotes to support nuanced queries. At query time, it anonymizes entities, creates a high-level plan, de-anonymizes and expands that plan into concrete retrieval or reasoning tasks, and executes them in sequence while continuously revising the plan. ... -
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The Pope Bot
Autonomous AI agent that you can configure and build
...It’s designed so that every action taken by the agent is logged as a git commit, giving users complete visibility into what the agent did, why it did it, and when, which makes actions auditable and reversible. The framework treats the repository itself as the agent’s “brain,” and GitHub Actions serve as the compute layer, enabling tasks to run securely without exposing sensitive API keys to the underlying AI. The system integrates with messaging platforms like Telegram, where users can interact with the bot, trigger actions, or receive notifications, and supports scheduling and automation through patterns of request handling. -
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Pal
A personal context-agent that learns how you work
Pal is an open-source AI personal agent built within the Agno ecosystem that functions as an intelligent digital assistant designed to learn from user activity over time. The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information. Instead of acting as a simple chatbot, Pal continuously builds a structured database of a user’s knowledge and context so it can answer questions, recall information, and assist with future tasks more effectively. ... -
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LingBot-VLA
A Pragmatic VLA Foundation Model
LingBot-VLA is an open-source Vision-Language-Action (VLA) foundational AI model designed to serve as a general “brain” for real-world robotic manipulation by grounding multimodal perception and language into actionable motions. It has been pretrained on tens of thousands of hours of real robotic interaction data across multiple robot platforms, which enables it to generalize well to diverse morphologies and tasks without needing extensive retraining on each new bot. -
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MCP Shrimp Task Manager
Shrimp Task Manager is a task tool built for AI Agents
...It ships with a web/GUI experience and works smoothly inside MCP-capable IDEs, making it useful as both a personal organizer and a programmable task substrate for software projects. Stars, registry listings, and docs point to active usage across the MCP community. The result is a practical “task brain” that agents can query and evolve over time. -
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MaxKB
Open-source platform for building enterprise-grade agents
MaxKB (Max Knowledge Brain) is an open-source platform for building enterprise-grade AI agents with strong knowledge retrieval, RAG pipelines, and workflow orchestration. It focuses on practical deployments such as customer support, internal knowledge bases, research assistants, and education, bundling tools for data ingestion, chunking, embedding, retrieval, and answer synthesis. -
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snntorch
Deep and online learning with spiking neural networks in Python
...Spiking neural networks are biologically inspired models that communicate through discrete spike events rather than continuous activation values, making them closer to how neurons operate in the brain. The library extends PyTorch’s tensor computation capabilities to support gradient-based learning for networks composed of spiking neurons. This allows researchers to train spiking neural models using familiar deep learning workflows while taking advantage of GPU acceleration and automatic differentiation. snnTorch provides implementations of common spiking neuron models, surrogate gradient training methods, and utilities for handling temporal neural dynamics. ... -
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mTRF-Toolbox
A MATLAB package for modelling multivariate stimulus-response data
...It can be used to model the functional relationship between neuronal populations and dynamic sensory inputs such as natural scenes and sounds, or build neural decoders for reconstructing stimulus features and developing real-time applications such as brain-computer interfaces (BCIs). Toolbox Paper: http://dx.doi.org/10.3389/fnhum.2016.00604 Methods Paper: https://doi.org/10.3389/fnins.2021.705621 -
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
...It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. The project also releases several fully anonymized public MRI datasets, including knee, brain, and prostate scans. -
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wukong-robot
Chinese voice dialogue robot/smart speaker project
wukong-robot is a Chinese voice assistant / smart speaker project built to let makers and hackers design highly customizable voice-controlled devices. It combines wake-word detection, automatic speech recognition, natural language understanding, and text-to-speech into a single framework aimed at the Chinese-speaking ecosystem. The project is positioned as a simple, flexible, and elegant platform that can run on devices like Raspberry Pi and other Linux-based boards, making it suitable for... -
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T81 558
Applications of Deep Neural Networks
...Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. ... -
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HealthFusion
AI Disease Detections System
HealthFusion has identified a critical business problem, which is the lack of accessibility and timely detection of multiple diseases. The traditional approach of detecting diseases is time-consuming, expensive, and not accessible to everyone, especially in remote areas. This problem can lead to delayed diagnosis and treatment, which can have serious consequences for patients. The proposed solution, HealthFusion, is novel and practical as it offers a comprehensive solution to detect... -
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Trax
Deep learning with clear code and speed
Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively used and maintained in the Google Brain team. Run a pre-trained Transformer, create a translator in a few lines of code. Features and resources, API docs, where to talk to us, how to open an issue and more. Walkthrough, how Trax works, how to make new models and train on your own data. Trax includes basic models (like ResNet, LSTM, Transformer) and RL algorithms (like REINFORCE, A2C, PPO). ... -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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Tensor2Tensor
Library of deep learning models and datasets
...Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. T2T was developed by researchers and engineers in the Google Brain team and a community of users. It is now deprecated, we keep it running and welcome bug-fixes, but encourage users to use the successor library Trax. -
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...Autochord , themeonly, learn (automatic chord learning from played data) functions added to recorder/player .( auto adds/replace chords to any music melody ). can record and export to midifiles. included brainpiano_chung a version with neural network brain autochord trial. (it really adds chords) included brainpiano2_chung version with custom neural network music generator . amazing brainpiano3_chung added quantize trial added to recorder
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myOCR_chung
my OCR and neural network brain in freebasic
myOCR brain chung is a small highly accurate OCR char recognition and Ann neural network brain example written in freebasic . -
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mctc4bmi
Matrix and Tensor Completion for Background Model Initialization
MCTC4BMI (Multimodal Compressed Sensing and Tensor Decomposition for Brain-Machine Interfaces) is a MATLAB toolbox designed to process and analyze EEG data. It applies compressed sensing and tensor decomposition techniques to improve brain-machine interface (BMI) performance. -
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SmartRoom
Smart services for assistance to conferences, meetings, lectures
...The project applies the advanced Smart-M3 SDK and inherits the FRUCT groundwork on SmartConference and SmartScribo systems. SmartRoom uses computational, sensing, and human interface devices. Participants use available services, such as presentations, agenda, brain storms, collective decisions. Some services are common - outcome is shown to everyone in the room; some services are personal - accessed individually via mobile end-user devices. The project is done by FRUCT Lab at the IT-park of Petrozavodsk State University (PetrSU), Russia. -
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...The peculiarity of this system is that the digital network created using radionic* technology that provides interaction between human and computer thinking. This digital network of the brain obtained by the interaction of the operator with the software, on the basis of generating random sequences at pomotsi quark-neuronal cluster. Thus, in part, this artificial neural network is a replica of the brain.
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smartblob
tiny code, html webcam game or plug brain in each blob, java server
You play a 2d blob that reshapes to grab bend bounce and swing on objects floating in midair (like a platformer game), except acrobaticly your view spins when your blob does. I'm planning a huge multiplayer world, some blobs played by people holding a bendable loop game controller (tape a 1 meter cut of thick extension cord into a loop) in front of webcam and bend it to bend your blob on screen, and other blobs controlled by AI. This is a game for general AI research in a fun way people can...
