A collection of all known Alfred3 workflows

Collective Knowledge workflow for Caffe to automate installation across diverse platforms and to collaboratively evaluate and optimize Caffe-based workloads across diverse hardware, software and data sets (compilers, libraries, tools, models, inputs):

Virtual Reality Software Library

Collective Knowledge components for TensorFlow (code, data sets, models, packages, workflows):

CK repository with components and automation actions to enable portable workflows across diverse platforms including Linux, Windows, MacOS and Android. It includes software detection plugins and meta packages (code, data sets, models, scripts, etc) with the possibility of multiple versions to co-exist in a user or system environment.

CK automation actions to let users implement portable, customizable and reusable program workflows for reproducible, collaborative and multi-objective benchmarking, optimization and SW/HW co-design:

Collective Knowledge extension with unified and customizable benchmarks (with extensible JSON meta information) to be easily integrated with customizable and portable Collective Knowledge workflows. You can easily compile and run these benchmarks using different compilers, environments, hardware and OS (Linux, MacOS, Windows, Android). More info:

Collective Knowledge repository with actions to unify the access to different predictive analytics engines (scipy, R, DNN) from software, command line and web-services via CK JSON API:

Collective Knowledge crowd-tuning extension to let users crowdsource their experiments (using portable Collective Knowledge workflows) such as performance benchmarking, auto tuning and machine learning across diverse platforms with Linux, Windows, MacOS and Android provided by volunteers. Demo of DNN crowd-benchmarking and crowd-tuning:

Integration of Caffe2 to Collective Knowledge workflow framework to provide unified CK JSON API for AI (customized builds across diverse libraries and hardware, unified AI API, collaborative experiments, performance optimization and model/data set tuning):

Collective Knowledge web extension to browse CK repositories, visualize interactive graphs and articles, render CK-based websites, implement simple web services with JSON API (for example to crowdsource experiments or unify access to DNN). Demos of interactive articles, graphs and crowdsourced experiments:

Meta information about platforms participating in experiment crowdsourcing using Collective Knowledge Framework (OS,CPU,GPU,GPGPU,NN...):

Collective Knowledge extension to automate Docker "build","run" and "push" functions and packge CK repositories for collaborative and reproducible research:

Standalone, thin and portable server to let users participate in experiment crowdsourcing using Windows devices via Collective Knowledge Framework:

Crowdsourcing video experiments (such as collaborative benchmarking and optimization of DNN algorithms) using Collective Knowledge Framework across diverse Android devices provided by volunteers. Results are continuously aggregated in the open repository:

U.S. Healthcare Transparency Data. Supplemental data for the CMS/HHS price transparency rules.

Collective Knowledge packages to build development versions of compilers (LLVM, GCC, etc) and use them in customizable and portable CK research workflows:

A chronological tracking of lies perpetrated against humanity.

Public data sets and their properties in the Collective Knowledge Format with JSON API and JSON meta information to be easily pluggable to customizable and reproducible CK experimental workflows (such as collaborative program analysis and optimization):

Collective Knowledge extension to crowdsource bug detection in OpenCL compilers using CLSmith tool from Imperial College London