Popular GitHub Repositories for Cognitive Deception

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

Reliable LLM Memory for AI Applications and AI Agents

Simple and Distributed Machine Learning

A secure low code honeypot framework, leveraging AI for System Virtualization.

List of language agents based on paper "Cognitive Architectures for Language Agents"

Microsoft Text-to-Speech API sample code in several languages, part of Cognitive Services.

Chat and Ask on your own data. Accelerator to quickly upload your own enterprise data and use OpenAI services to chat to that uploaded data and ask questions

A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.

Azure OpenAI (demos, documentation, accelerators).

Language, Knowledge, Cognition

workshop materials to build intelligent solutions on Open AI

AAAI 2024 Papers: Explore a comprehensive collection of innovative research papers presented at one of the premier artificial intelligence conferences. Seamlessly integrate code implementations for better understanding. ? experience the forefront of progress in artificial intelligence with this repository!

Source code and dataset for ACL 2019 paper "Cognitive Graph for Multi-Hop Reading Comprehension at Scale"

Vision AI Solution Accelerator

Project Page For "Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement"

? Research Framework for Single and Multi-Players ? Multi-Arms Bandits (MAB) Algorithms, implementing all the state-of-the-art algorithms for single-player (UCB, KL-UCB, Thompson...) and multi-player (MusicalChair, MEGA, rhoRand, MCTop/RandTopM etc).. Available on PyPI: https://pypi.org/project/SMPyBandits/ and documentation on

Code Examples used by the Quickstarts in the Cognitive Services Documentation

An easy to use C# deep learning library with CUDA/OpenCL support

Make Azure natural TTS voices accessible to any SAPI 5-compatible application.

An awesome repository & A comprehensive survey on interpretability of LLM attention heads.