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Centre for Artificial Intelligence Research (CAIR) photo

cair Goto Github PK

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Name: Centre for Artificial Intelligence Research (CAIR)

Type: Organization

Bio: CAIR is a centre for research excellence on artificial intelligence at the University of Agder. We attack unsolved problems, seeking superintelligence.

Location: Grimstad, Norway

Blog: https://cair.uia.no/

Cair Platform

This package providies you with three components to manage the content on your website:

  • Platform: A dynamic active record implementation. Allowing you to configure your data structure at runtime.
  • Access: A restful JSON API used by the admin panel or by your application.
  • Panel: The admin panel for filling in your data.

Installation

Via composer.

{
    "require": {
        "cair/cair": "0.1.*",
        "stack/builder": "1.0.*",
        "stack/url-map": "1.0.*"
    }
}

composer update

And bower.

bower install cair-panel

Usage

// Create your application in $app.

Cair\Platform\Provider::setConfig([
  'resources' => [
		'posts' => [
			'attributes' => ['title', 'content'],
			'rules' => [
				'title' => ['required', 'min' => 3],
				'content' => ['required']
			],
			'types' => [
				'title' => 'text',
				'content' => 'textarea',
			]
		]
	],
	'scripts' => [
		"panel/dist/js/cair.js"
	]
]);

$stack = new Stack\Builder;

$stack->push('Stack\UrlMap', [
    '/admin' => require(__DIR__.'/src/Cair/Panel/start.php'),
    '/api' => require(__DIR__.'/src/Cair/Access/start.php'),
]);

$app = $stack->resolve($app);

$request = Request::createFromGlobals();

$app->handle($request)->send();

Centre for Artificial Intelligence Research (CAIR)'s Projects

nix-tts icon nix-tts

🐤 Nix-TTS: An Incredibly Lightweight End-to-End Text-to-Speech Model via Non End-to-End Distillation

patchformer icon patchformer

PatchFormer - Improved dense predictions using implicit representation learning

pytsetlinmachine icon pytsetlinmachine

Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, clause indexing, and literal budget

pytsetlinmachineparallel icon pytsetlinmachineparallel

Multi-threaded implementation of the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features and multigranularity.

pyvnc icon pyvnc

VNC Client Library for Python

ray-bugfix icon ray-bugfix

A workaround to issues with Rllib, given it does not work for your current gym environment. CarRacing-v0 is one of these.

tm-xor-proof icon tm-xor-proof

#tsetlin-machine #machine-learning #game-theory #propositional-logic #pattern-recognition #bandit-learning #frequent-pattern-mining #learning-automata

tmu icon tmu

Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.

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