I've been seeking the intersection of consciousness and technology for most of my life, so when I discovered the Consciousness Hacking MeetUp in Silicon Valley, I signed up immediately for a curious MeetUp titled, "Enlightened AI." The talk was led by Google researcher, Mohamad Tarifi, PhD. Not only is he a bright engineer working on the next level of artificial intelligence at one of the top companies in the Valley, he's also very well versed in the philosophies of consciousness. From the Abrahamic traditions, to the Buddhists and Eastern teachings, Tarifi displayed a grasp of the whole of humanity unlike any other technologist I've met. His speech focused on the fact that while many, like Sam Harris in his post on the AI apocalypse, warn us of the dire consequences of AI, there instead exists the possibility that artificial intelligence would most likely be more like a Buddha or saint, than a tyrannical operating system hell bent on destroying humans.

Alphabet Inc (NASDAQ:GOOGL) is one of the numerous tech giants to currently work on developing artificial intelligence software. Artificial intelligence has divided opinion amongst the leading technology gurus, where some are highly in favor of such technical advancement but others are not too sure about its consequences. Many are worried about the physical threat that AI systems can pose to human life. In order to avoid a'terminator' like doomsday, Google aims to perfect its artificial intelligence systems with the implementation of five golden rules. In a blog, Google researcher, Chris Olah, stated five ways for the company to ensure that AI systems never pose a threat to the human race. The first rule is "Avoiding Negative Side Effects" which means that artificial intelligence should complete its tasks as it was designed to and not indulge in disturbing its environment.

A recently published survey by the Evans Data Corporation shed light on a growing trend in the world of technology development. It showed the high-profile shift in focus of data-driven corporations towards artificial intelligence, robotics, and the Internet of Things. This survey, which included 1,441 developers, found that of all the industries impacted by big data analytics, the Internet of Things was ranked at the top with 15.1% followed closely by telecommunications and professional scientific services at 10% each. Among data mining app developers, robotics, automobiles, and entertainment were being focused on by over half of those surveyed. The sensors used in IoT technologies offer data mining applications valuable insights that go beyond the data traditional systems could obtain.

Amazon.com Inc.'s new U.S. intelligence community (IC) marketplace may make it easier for small software vendors to compete for classified business. According to Amazon Chief Evangelist Jeff Barr, "Our goal is to give the Intelligence Community as broad a selection of software as possible, so we are working to help our AWS Marketplace sellers through the onboarding process so that the Intelligence Community can benefit from use of their software." To be eligible for the IC marketplace, software must already be available on Amazon's public marketplace, according to Amazon. And, according to Nextgov, "The IC Marketplace is essentially a classified version of AWS' public marketplace that allows customers to peruse -- and try before they buy or deploy -- nearly 3,000 software offerings created by 925 independent software vendors." Little information is publicly available about what's available on the IC marketplace, although it's a sure bet that companies are trying out their analytics and big data platforms.

If you've got more than a handful of 3D printers or other devices running at a time, it's a full-time job keeping them going -- removing and packaging products, tweaking settings, pushing "OK" after minor errors, that sort of thing. Why not have a robot do it for you? Tend.ai is a new company that helps you train collaborative robots to perform machine tending, something generally reserved for bots serving heavy industry. "This whole thing started because a friend of mine down the street literally has 20 3D printers, and his wife was having to run out every three minutes to keep them running," said Mark Silliman, co-founder and CEO of Tend.ai, in an interview. Silliman's company Smartwaiver was acquired in December, and his co-founders have also had a few recent exits. Security head James Gentes sold his analytics company The Social Business last year, as well, and backend engineer Robert Kieffer was part of Zenbe, which Facebook bought in 2010.

Semantic Scholar is an academic search engine from Microsoft co-founder Paul Allen's Allen Institute for Artificial Intelligence. It too uses AI to search the academic literature and it is impressively fast. Still in beta, it's interface is less elegant, more "academic utilitarian" than the sleek Iris. And it also throws up some oddities. A search for the landmark paper "A safe operating space for humanity", which appeared in Nature (along with Science, one of the two leading academic journals) in 2009, does not show up on the first page, nor does the follow up paper, which appeared in Science in 2015.

IBM is using the power of its Watson supercomputer, "cognitive imaging" and artificial intelligence to help doctors better diagnose patients facing major diseases. The tech giant on Wednesday announced its Watson Health medical-imaging collaborative, which includes 16 members from health systems, academic medical centers and imaging-tech vendors. IBM said participants could train its Watson for early detection of ailments like breast cancer, heart disease, diabetes, eye problems and other overlooked health conditions. Cognitive computing and imaging lets health care providers draw insights from massive volumes of sharable data, such as electronic health records, lab results and other reports. "Our collaboration allows us to help shape the future of medicine by joining efforts to create the tools which will be vital for physicians to make correct decisions based on evidence and complex sources of clinical data," said Dr. Jack Ziffer, chief medical officer for Baptist Health South Florida.

Take a breath because the future might not be as bleak as you expect. A report from Forrester Research predicts that artificial intelligence systems, which include robots, automation, smart machines and machine learning systems, will replace 7 percent of U.S. jobs by 2025. That's a net reduction because the analyst firm predicts that technology will replace 16 percent of U.S. jobs but will create the equivalent of another 9 percent, leaving a 7 percent total reduction. These numbers might reinforce people's concerns that businesses will be quick to replace people, who need vacation time and pricey health care, with robots. Forrester analysts Craig LeClair and J.P. Gownder note in the study, which was released Wednesday, that robotics will replace some human workers in their jobs, but technology will also create new, more interesting jobs for people.

Altoros brings "software assembly lines" into organizations through training, deployment, and integration of solutions offered by the Cloud Foundry ecosystem. As a result, customers of Altoros discover and monetize application-driven competitive advantages sooner than competition by using Cloud Foundry-based "software factories" and "data lakes." With 250 employees across 8 countries, Altoros is behind some of the world's largest Cloud Foundry deployments.

In part 1, we went over how to use data visualization and data analysis prior to machine learning. For example, we discussed how to visualize the data to identify potential issues in the dataset, examine the variable distributions, etc. In this blog post, we'll continue by building a very simple model and using data visualization to examine that model. Just a quick reminder: as I noted in part 1, we're working with a very simple model. This is deliberately a "toy" model, which allows us to focus on the visualization/analysis aspect of the task without the added level of complexity that we'd inject by using a more advanced machine learning algorithm.