Let’s take a look at a few free and open source AI tools that anyone can use.
No matter how original your idea is in the open source space, it’s always wise to see if someone else has done it already. For organizations and individuals interested in leveraging the power of the growing Artificial Intelligence, Artificial Intelligence(AI), many of the best tools are not only free and open source, but also, in many cases, tested and proven.
AI is a high priority among leading companies and nonprofits, and these companies and organizations open source valuable tools. The following are examples of free and open source AI tools that anyone can use.
Acumos AI is a platform and open source framework that makes it easy to build, share and distribute AI applications. It specifies the infrastructure stacks and components needed to run a generic AI environment “out of the box.” This allows data scientists and model trainers to focus on their core competencies instead of wasting time on endless customizations, modeling, and training an AI implementation.
Acumos is part of the LF Deep Learning Foundation, an organization within the Linux Foundation that supports open source innovation in artificial intelligence, machine learning, and deep learning. The goal is to make these big new technologies available to developers and data scientists, including those with limited experience with deep learning and AI. The LF Deep Learning Foundation recently approved a project lifecycle and contribution process, and it is now accepting proposals for project contributions.
Facebook has open-source its central machine learning system, which is designed to do some large-scale AI tasks, as well as a range of other AI technologies. This tool is part of a proven platform used by their company. Facebook has also opened source a deep learning and AI framework called Caffe2.
When it comes to Caffe. Yahoo also releases its own key AI software under an open source license. CaffeOnSpark is based on deep learning, a branch of artificial intelligence that is useful in helping machines recognize human speech, or the content of photos and videos. Similarly, IBM’s machine learning program SystemML is freely shared and modified through the Apache software foundation.
Google has spent several years developing its own TensorFlow software framework to support its AI software and other predictive and analytical programs. TensorFlow is the engine behind some of Google’s tools that you probably already use, including Google Photos and language recognition used in the Google App.
Google has open-source two AIY suites that make it easy for individuals to use AI, focusing on computer vision and voice assistants. These two kits encapsulate all the components used into one box. The suite is currently available at Target in the US, and it’s based on the open source Raspberry PI platform — there’s growing evidence that a lot is happening at the intersection of open source and AI.
I’ve written about Ho.AI before, and it has a place in machine learning and artificial intelligence because its main tools are free and open source. You can get the main H2O platform and Sparkling Water, which works with Apache Spark, just download them. These tools are licensed under the Apache 2.0 license, a very flexible open source license that allows you to run them even on Amazon Web Services (AWS) and other clusters for a few hundred dollars.
“Our goal is to democratize AI so that every person and organization can achieve more,” said Satya Nadella, CEO of Microsoft. Therefore, Microsoft continues to iterate on its Microsoft Cognitive Toolkit(CNTK). It is an open source software framework that competes with TensorFlow and Caffe. Cognitive Toolkit works on 64-bit Windows and Linux platforms.
“Cognitive Toolkit enables enterprise-level, production-system-level AI by allowing users to create, train, and evaluate their own neural networks,” the Cognitive Toolkit team reports. These neural networks can scale efficiently across multiple Gpus and multiple machines in large data sets.”