On the Artificial Intelligence Front, Open Source Tools are Proliferating
If you ask many people to name the technology categories that are creating sweeping change right now, cloud computing and Big Data analytics would probably be top of mind for a lot of them. However, there is an absolute renaissance goind on right now in the field of artifical intelligence and the closely related field of machine learning.
Some of the biggest tech companies are helping to drive the trend, and Google added to the momentum on this front this week. Specifically, Sundar Pichai, Google's CEO, said on a conference call, "I do think in the long run we will evolve in computing from a mobile-first to an A.I.-first world." In this post, you'll find a collection of the most notable A.I. tools that have recently been open sourced. And yes, open source and A.I. are now feeding each other.
In statements related to Sundar Pichai's, Alphabet Chairman Eric Schmidt has said that he sees A.I. and machine learning playing a huge part in the technology future.
Google has open sourced a program called TensorFlow. It’s based on the same internal toolset that Google has spent years developing to support its AI software and other predictive and analytics programs. You can find out more about TensorFlow at its site, and you might be surprised to learn that it is the engine behind several Google tools you may already use, including Google Photos and the speech recognition found in the Google app.
According to Google, TensorFlow could help speed up processes ranging from drug discovery to processing astronomy-related data sets.
Additionally, we reported on how H2O.ai, formerly known as Oxdata, has announced a new funding round that it is getting to the tune of $20 million. The money will go toward advancing its machine learning toolset, and the company is entirely open source-focused. We recently caught up with Oleg Rogynskyy, VP of Marketing & Growth at H2O, for an interview.
Meanwhile, Facebook is open sourcing its machine learning system designed for artificial intelligence (AI) computing at a large scale. It's based on Nvidia hardware. And, IBM announced that its proprietary machine learning program known as SystemML will be freely available to share and modify through the Apache Software Foundation.
And, Yahoo has released its key artificial intelligence software (AI) under an open source license. The company previously developed a library called CaffeOnSpark to perform a popular type of AI called “deep learning” on the big troves of data found in its Hadoop file system. Now CaffeOnSpark is becoming available for community use under an open source Apache license on GitHub.
As WIRED notes:
"CaffeOnSpark is based on deep learning, a branch of artificial intelligence particularly useful in helping machines recognize human speech, or the contents of a photo or video. Yahoo, for example, uses it to improve search results on Flickr by determining the contents of different photos. Instead of relying on the descriptions and keywords entered by the people who upload photos to the site, Yahoo teaches its computers to recognize certain characteristics of a photo, such as specific colors or even objects and animals."
CaffeOnSpark works with x86 chips or graphics processing units (GPUs). It can be run on cloud infrastructure or within data centers. Among many uses for it at Yahoo, it has helped make connections for content recommendations.
"In 2016, every company will want to get on the machine-learning bandwagon," said Monte Zweben, co-founder and CEO of Splice Machine and executive chairman of RocketFuel, in a recent interview. "But without the right people, many won’t have the expertise to do it. Expect to see the development of turnkey databases that allow developers to build predictive models without having a Ph.D."
Notably, Microsoft has open sourced the artificial intelligence framework it uses to power speech recognition in its Cortana digital assistant and Skype Translate applications. The framework is called, CNTK, and can help machines do things like understand speech and determine logical connections between photos.
Microsoft released its Computational Network Toolkit (CNTK) as an open source project on GitHub, and developers are likely to leverage it to advance deep learning networks.
Ray Kurzweil's site has also rounded up many of the top machine learning and artificial intelligence breakthroughs of recent times here.
The basic goal with most machine learning and A.I. tools is to take a vast quantity of data and reduce it to manageable, actionable insights. Now, some of the biggest tech companies are putting the tools in place to let the community advance these efforts. Expect much more in this space as 2016 continues.