Sunday, May 7, 2017

Open Source Artificial Intelligence & Machine Learning Solutions

Artificial Intelligence (AI), Machine Learning (ML), Robots, and the Internet of Things (IoT) will help solve some of the major challenges the world is currently facing in healthcare, transportation, finance, defense, manufacturing. However, there are also some major issues and risks that come with these technologies.

This article attempts to provide a quick, high level overview of Artificial Intelligence (AI) and Machine Learning (ML) technologies and their potential to massively impact and disrupt civilization as we know it today. Let’s start with a definition of these two new, related technologies.

  • Artificial Intelligence (AI) - Refers to intelligence exhibited by machines. In computer science, the term "artificial intelligence" is applied when a machine mimics cognitive functions generally associated with human minds, such as ‘learning’ and ‘problem solving’.
  • Machine Learning (ML) - Machine learning is considered a subset of the field of Artificial Intelligence (AI). It generally refers to ‘smart’ machines that have the ability to learn without being explicitly programmed by humans.

Artificial Intelligence (AI) is one of the hottest areas of technology research and development. Major corporations like IBM, Google, Microsoft, Facebook and Amazon are investing heavily in this area and are buying up startups that have made progress in areas like machine learning and neural networks. - Datamation

Open Source’ AI & ML Solutions

The ‘Open Sourcesoftware development methodology and business model is at the heart of the rapid evolution and innovation of Artificial Intelligence (AI) and Machine Learning (ML) technologies and solutions.

Based on a review of recent articles on software, the following are brief profiles on some of the best of the currently available ‘open source’ AI and ML solutions that we all ought to know a little more about as they begin to flow into industry, e.g. manufacturing, finance, healthcare, defense.
  • TensorFlow - An open source software library for ‘machine intelligence’ originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence R&D organization.

  • Accord.NET is a .NET machine learning (ML) framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building usable production-grade applications.
  • Amazon Machine Learning (AML) provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology.
  • Apache Check out some of the more notable Apache AI & ML Projects, such as Mahout, Prediction, Spark MLlib, and Singa.
  • Caffe was the brainchild of Yangqing Jia who is now the lead engineer for the Facebook AI platform. Caffe is the first mainstream industry-grade ‘deep learning’ toolkit. The Facebook team is now working on Caffe 2.
  • CNTK is Microsoft’s open source ‘deep learning’ cognitive toolkit that is available on GitHub.
  • H2O is the world’s leading open source ‘deep learning’ AI platform. H2O is used by over 80,000 data scientists and more than 9,000 organizations around the world.
  • OpenAI is a non-profit AI research organization associated with business magnate Elon Musk. The organization strives to ‘freely collaborate’ with other institutions and researchers by making its AI and ML patents and research ‘open’ to the public.
  • Shogun is a collaborative free and open source ‘machine learning’ toolbox written in C++.
  • Torch is a scientific computing framework offering wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language called LuaJIT.

Key Issues

Artificial Intelligence (AI)
and Machine Learning (ML) technologies are already being deployed in many industries, e.g. finance, healthcare, manufacturing, transportation, defense. However, some of the key issues that need to be more fully addressed over the coming decade before these systems are widely deployed include:

  • Ethics - The moral behavior being programmed by humans into robots and other 'smart' AI systems, e.g. Roboethics.
  • Privacy & SecurityWhen AI systems are turned loose to monitor your personal information, who it is being shared with and how they are using it must be better addressed and understood.
  • Legal Issues – What is the legal standing of intelligent machines of the future and who is responsible for the actions they may take that could harm you.

The Bank of England has predicted that intelligent machines might take over 80 million US and 15 million British jobs, respectively over the next 10 to 20 years. Think of what this means for you and your livelihood.

If you are concerned and want to learn more about AI and ML technologies and their potential to ‘rock your world’, you might want to check out the following items:

Conclusion & Next Steps

As you begin to delve deeper into the key issues raised above, many other questions begin to arise that actually touch on the future of mankind as we know it. Many of these issues and questions have not yet begun to be discussed and addressed by many of our leaders in the public and private sector. That should be of concern to us all. Fortunately, the collaborative ‘open source’ approach being used to develop these new technologies has brought tens of thousands of our best minds to bear on these issues.

WARNING: Stephen Hawking has said the development of full Artificial Intelligence (AI) could spell the end of the human race – and Elton Musk agreed.

Have you begun to think about Artificial Intelligence and ‘Smart’ Machines? How do you think they will impact you and the lives of your children? Share your constructive thoughts with our readers.

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