In previous articles, we've talked about the merits of artificial intelligence and big data and how these technologies can enable a multitude of industries to begin learning how to do things more effectively. One area where these technologies can be used is in digital marketing. Also referred to as "programmatic marketing", AI and big data can be used to figure out what digital ad to serve you up at any given time to increase the likelihood that you'll click on it. While we've said before that you can't invest in artificial intelligence yet as a retail investor, we did come across one publicly traded company called Rocket Fuel (NASDAQ:FUEL) which is playing in the "programmatic marketing" space and while their value proposition sounds exciting, there's much more to this company than meets the eye. Founded in 2008, Rocket Fuel uses artificial intelligence and big data to determine which ad is best to serve at any given moment in order to increase the likelihood of you clicking on that ad, and then engaging with the advertiser.

It's a notion marketers will drool over: Imagine if their overloaded job responsibilities could be wiped clean by the use of robots to do tedious marketing tasks for them. Just as we already use programmatic buying and other data-driven marketing tools to simplify difficult and time-consuming processes, artificial intelligence (AI) is viewed by both robotics experts and marketing professionals as a tool to expedite menial content creation in the future. Efforts to bring AI to the mainstream are underway. IBM's Watson AI is already making appearances in ads holding conversations with celebrities. Robotic writing solutions have been used for simple writing tasks, such as recapping sporting events.

The experienced Machine Learning Technologist will have general knowledge in different techniques applied in machine learning such as supervised learning and unsupervised learning, and of basic concepts in probabilities and applied statistics. The types of algorithmic solutions should span across different types of data ranging from numeric, textual (structured or unstructured), images, and video. The candidate for this position will be able to effectively apply machine learning and data mining to different types of data collected from tasks and domains such as manufacturing, multimodal sensors, images and video, and online documents. They will have the general ability to design, apply, and create new algorithms, methods, and tools for the analysis of data to address project requirements. They will have the general ability to evaluate the performance of data analysis algorithms as well as general ability to select and apply algorithms to meet application requirements with respect to scalability.

Artificial intelligence (AI) is defined as being "the ability of a machine to perform at the level of a human expert". We have recently seen an example of this come to the fore when Google-owned DeepMind's program AlphaGo beat the reigning world Go champion, Lee Sodol, 4-1 in what many consider to be the most difficult game in the world. Traditional business use of the telephone as a major business tool involves two parties. A debt collection agent tries his or her best to "encourage" a client to pay their account. A sales rep attempts to entice a lead to purchase their product.

I'm often asked about my thoughts on the future. What will transportation be like? What new forms of entertainment will we enjoy? While I have covered these topics in previous articles, it's important to understand that they're all forms of work. So today I want to discuss the future of work -- how technological advancements, namely robotic assistants and tools, as well as tech-enhanced globalization, will affect our daily work flow and the labor market in general.

Artificial intelligence is nothing new at Google, but today we learned just how big a role top boss Sundar Pichai sees AI playing in our future. Answering an analyst query on Google-parent company Alphabet's Q1 2016 earnings call about how the company is leading innovation, rather than simply adapting to changes in technology, Pichai talked about his role in projecting where Alphabet is going in the next 10 years. He gave a shout out to VR as the hot new platform, and then wrapped up his comments by saying: "In the long run, I think we will evolve in computing from a mobile-first world to an AI-first world." Earlier in the call he cited Google's DeepMind AlphaGo super computer defeating a human champion as an extraordinary achievement. He also said the company is investing in AI and machine learning, areas that are taking off and beginning to bear real-world benefits.

Human patrols serve as the most direct form of protection of endangered animals, especially in large national parks. However, protection agencies have limited resources for patrols. With support from the National Science Foundation (NSF) and the Army Research Office, researchers are using artificial intelligence (AI) and game theory to solve poaching, illegal logging and other problems worldwide, in collaboration with researchers and conservationists in the U.S., Singapore, Netherlands and Malaysia. "In most parks, ranger patrols are poorly planned, reactive rather than pro-active, and habitual," according to Fei Fang, a Ph.D. candidate in the computer science department at the University of Southern California (USC). Fang is part of an NSF-funded team at USC led by Milind Tambe, professor of computer science and industrial and systems engineering and director of the Teamcore Research Group on Agents and Multiagent Systems.

How we explain reality to ourselves is a construction with many parts. We gather knowledge and generate meaning through our experiences and traditions; from what we learn in school, at work and at home; from how we witness others explaining reality for themselves (on TV, via social media, etc). This narrative that we tell ourselves everyday throughout our entire lives largely defines who we are and how we approach the world. The first time I ran (in Mexico) an adaptation of Stanford's workshop "Makers in Residence" (an intensive 80 hour program for high schoolers on digital fabrication and design thinking which was designed by the Transformative Learning Technology Lab) I was shocked by the comments of participants regarding their place in relation to technology. Most participants were impressed that they were "smarter" than the computers they programmed; when I asked them more about it I started understanding the new narrative that a generation of kids growing up surrounded by digital technology are developing in their heads.

I too believe AI could be bigger in the future once the under pinning technology and infrastructure moves to Quantum Technology so that hacking is under control and performance is where it needs to be. When Mark Zuckerberg thinks about the future, he sees a world that's dominated by mobile devices and virtual reality, but when Google CEO Sundar Pichai thinks about the future, all he sees is artificial intelligence. He suggested as much during Alphabet's quarterly earnings call on Thursday, saying that mobile devices and virtual reality will dominate the immediate future, but that they'll eventually be surpassed in importance by artificial intelligence. However, he didn't go into detail about what this future will look like. Artificial intelligence is nothing new at Google, but today we learned just how big a role top boss Sundar Pichai sees AI playing in our future.

Identifying the top 10 algorithms in the abstract is a pretty complicated exercise unless there is a clear dimension to make the comparison. Let me tackle this from a pretty subjective point of view: If I were interviewing you for a Data Mining position what would be the top 10 algorithms I would expect you to know in order of priority? Again, a pretty subjective list, but I think it is quite representative of what you need to do real data mining work in industry.