AI run entirely on your local infrastructure

To ensure that all data remains internal and is never shared with a third party, you can use open-source AI tools and frameworks that can be run entirely on your local infrastructure. Here are some AI tools and platforms that meet this criterion:

Machine Learning Frameworks

1. TensorFlow:
   • Open-source framework developed by Google.
   • Supports a variety of machine learning and deep learning tasks.
   • Can be run on local servers or internal cloud infrastructure.
   • Website: TensorFlow
2. PyTorch:
   • Open-source machine learning framework developed by Facebook's AI Research lab.
   • Widely used for deep learning applications.
   • Can be run entirely on local hardware.
   • Website: PyTorch

Generative AI Models

1. GPT-Neo/GPT-J by EleutherAI:
   • Open-source alternatives to OpenAI's GPT-3.
   • Models can be downloaded and run on local servers.
   • Suitable for text generation tasks.
   • GitHub: GPT-Neo, GPT-J
2. BERT:
   • Bidirectional Encoder Representations from Transformers.
   • Pre-trained models available that can be fine-tuned for various NLP tasks.
   • Can be run locally.
   • GitHub: BERT
3. Hugging Face Transformers:
   • Library providing thousands of pre-trained models for NLP, vision, and more.
   • Models can be downloaded and used locally without sending data externally.
   • Website: Hugging Face

Data Processing and Analysis

1. Scikit-learn:
   • Open-source machine learning library for Python.
   • Includes simple and efficient tools for data mining and data analysis.
   • Can be run entirely on local infrastructure.
   • Website: Scikit-learn
2. Apache Spark:
   • Open-source unified analytics engine for large-scale data processing.
   • Can be run on local servers or a private cluster.
   • Website: Apache Spark

Computer Vision

1. OpenCV:
   • Open-source computer vision and machine learning software library.
   • Provides a common infrastructure for computer vision applications.
   • Can be run entirely on local machines.
   • Website: OpenCV
2. YOLO (You Only Look Once):
   • Real-time object detection system.
   • Models and code can be run on local servers.
   • GitHub: YOLO

Deployment and Containerization

1. Docker:
   • Platform for developing, shipping, and running applications inside containers.
   • Ensures the application runs in the same environment.
   • Can be used to deploy AI models locally.
   • Website: Docker
2. Kubernetes:
   • Open-source system for automating deployment, scaling, and management of containerized applications.
   • Can be used to manage AI workloads on local or private cloud infrastructure.
   • Website: Kubernetes

This blog post is a work in progress.. if you have something that you would like to add please contact me I would love to include it. - Tom
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