Downloadable AI typically refers to artificial intelligence software or models that can be downloaded and installed locally on a user's device or server. This contrasts with AI that operates exclusively in the cloud or on remote servers accessed via the internet.

Here are some key aspects of downloadable AI:

* Local Installation: Users download AI software or models onto their devices, such as computers, smartphones, or servers.

* Offline Capabilities: Once downloaded, the AI can operate without requiring a continuous internet connection. This is particularly useful in scenarios where internet access may be limited or unreliable.

* Customization: Users may have more flexibility to customize and modify downloadable AI to suit specific needs or integrate it into existing systems.

* Privacy and Security: Some users prefer downloadable AI because it allows them to keep data and processes within their own controlled environment, potentially offering greater privacy and security.

* Pre-trained Models: AI models trained on specific tasks (like image recognition or natural language processing) that can be downloaded and used locally.

* Development Frameworks: AI development kits and frameworks (like TensorFlow or PyTorch) that can be installed on local machines for building and training custom AI models.

* AI Applications: Software applications incorporating AI functionalities that are downloaded and run on devices.

Overall, downloadable AI provides flexibility and control over how AI technologies are deployed and utilized, catering to a wide range of applications and user requirements. Here are 50 examples of downloadable AI technologies, frameworks, libraries, and applications listed alphabetically:

* AllenNLP
* Apache Mahout
* Apache SINGA
* Apache SystemML
* Apple Core ML
* Baidu EasyDL
* Caffe
* Caffe2
* Chainer
* Clarifai
* CNTK (Microsoft Cognitive Toolkit)
* DeepDetect
* Deeplearning4j
* Dlib
* Dopamine
* FastAI
* Gensim
* Google Cloud AutoML
* H2O.ai
* IBM Watson Machine Learning
* Intel nGraph
* Kaldi
* Keras
* LightGBM
* Mahout
* MLlib (Apache Spark)
* MXNet
* Neural Designer
* NLTK (Natural Language Toolkit)
* NVIDIA Deep Learning SDK
* OpenAI Gym
* OpenCV
* OpenNLP
* OpenNN
* OpenVINO
* PaddlePaddle
* Pandas
* PyBrain
* PyTorch
* RapidMiner
* Scikit-learn
* Shogun
* Singa
* Spark MLlib
* Stanford CoreNLP
* TensorFlow
* Theano
* Torch
* Weka
* XGBoost

This list includes a variety of downloadable AI technologies (which may or may not be downloadable when you read this,) libraries, frameworks, and platforms that cover different aspects of machine learning, deep learning, natural language processing, computer vision, and more.

These examples encompass a wide range of AI libraries, frameworks, platforms, and tools that can be downloaded and used for various machine learning, deep learning, and AI-related tasks.