Daily Tech Digest - December 24, 2016

Smart Homes: Are the Security Risks Worth It?

Early smart home systems have some serious security flaws that have come to light within the last few years. Trailblazing smart home manufacturers have been more concerned with innovation and getting their products to market than in keeping up with the latest developments in cyber security. These companies often neglect even the basics of keeping their smart home systems safe, making them ridiculously easy to hack. One Synack security analyst who tested the cyber security of some of these products was able to hack into 15 of 16 smart home devices within 20 minutes. When you consider that those devices could include home security cameras, garage doors, and water pumps, it’s easy to see that these vulnerabilities pose a physical threat to the home’s inhabitants.


The State of Autonomous Vehicles: A "Who's Who" of Industry Drivers

Forward-thinking car manufacturers, in Detroit and abroad, are taking advantage of these disruptive technologies, focusing on building partnerships, acquiring startups, and beefing up internal R&D departments to avoid extinction. These partnerships and acquisitions also signal a maturing market, with further maturity reached as new revenue streams emerge in both automotive and also tangential industries that focus on providing services that complement or depend on the self-driving car experience.  Autonomous vehicles are about more than a "new" iterative feature sets, faster 0-60 speeds, or any other typical measurement of automotive innovation. They enable an entirely unprecedented consumer lifestyle, much like the internet itself, that surpasses traditional industry boundaries and will serve as the foundation for entirely new business models for the corporations that fuel its evolution


Want to know how to choose Machine Learning algorithm?

Machine Learning is the foundation for today’s insights on customer, products, costs and revenues which learns from the data provided to its algorithms. Some of the most common examples of machine learning are Netflix’s algorithms to give movie suggestions based on movies you have watched in the past or Amazon’s algorithms that recommend products based on other customers bought before. Typical algorithm model selection can be decided broadly on following questions: How much data do you have & is it continuous?; Is it classification or regression problem?; Predefined variables (Labeled), unlabeled or mix?; Data class skewed?; What is the goal? – predict or rank?; Result interpretation easy or hard? Here are the most used algorithms for various business problems


5 trends in open source documentation

People are increasingly choosing lightweight markup languages for a number of reasons. They are usually easier to write, at least for simple things. They tend to play better with version control systems, because they're generally line oriented. And they can help lower the barrier to entry for new contributors, although you should be careful not to expect a change in source format alone to drive lots of contributors to your project. ... Another reason static sites are more popular is that source hosting sites are easier to use, and a growing number of technical people use them. One of the draws of a wiki was that somebody could contribute without downloading anything or installing special tools. If your source files are stored in a hosting service like GitHub, anybody with a GitHub account can edit them right in their web browser and ask you to merge their changes.


EHR Data, Machine Learning Create Cost-Based Clinical Pathways

“With medical cost being such an opaque subject, providers may not have the best guidance strategy for the treatments that they offer to their patients,” wrote authors Yiye Zhang, PhD, and Rema Padman, PhD. Value-based care and innovative payment models for chronic disease management are prompting providers to take a more patient-centered approach to treatment, Zhang and Padman said, and require more patient involvement in their own care.  By creating step-by-step clinical pathways based on a patient’s anticipated disease development, big data analytics techniques could help providers “achieve accurate predictions of anticipated future events and costs following different clinical and cost pathways for improved shared decision making, and, subsequently, identify appropriate ranges of cost for targeted clinical pathways within a patient population,” says the article.


The 5 Most Worrying Technology Trends For 2017 And Beyond

Combining AI with advances in robotics, medicine and gene-technology means that people could stop dying or at least live a lot longer. That sounds great at first, but more people living well past 100 years would have massive implications for the economy and society at large. The population would continue to grow at an even faster rate, putting more pressure on resources around the world. ... As technology advances, we run the risk of entering a world of digital feudalism, in which a few technology elites — whether they are individuals or corporations — control our lives and our fate by controlling our data and our world. So far, people can still choose to opt-out, but it’s already inconvenient and uncomfortable. What happens when all transactions are handled digitally, when you can’t do something as simple as buy food, drive a car, or read a book without a digital signature.


5 game-changers coming to cloud in 2017

According to the same IDG survey, 21 percent are worried about vendor lock-in, which is understandable. The big public cloud providers offer one-size-fits-all cloud models that can orphan back-end systems or even require complete rewriting of critical business applications. Once you’re on their proprietary systems, it can be expensive — if not completely cost prohibitive — to move your workloads and data off their cloud. Take a look at this ZDNET story detailing how American Airlines is migrating to the cloud and using IBM Bluemix to develop new services and business models. IBM and American are partnering to build cloud-based applications that solve specific problems unique to their business, workloads and data. It’s a cloud strategy shaped around American’s unique business model, not its public cloud provider’s.


What the 4th Industrial Revolution Means for Future Jobs

Putting a little extra “elbow grease” into your work isn’t necessarily a good thing anymore (and with that, all couch potatoes rejoice). Mundane tasks are being replaced by more significant and engaging work for employees as Smart Technology is allowing for increased worker productivity by having computers do the tedious and time consuming work (sorry lazy people, you still have to actually do some work). Smart Technology is empowering the workforce. With IIoT solutions, employees develop working relationships with intelligent machines to achieve production results that neither human nor machine could accomplish independently. As IIoT innovations continue to develop, it is expected that the number of connected devices will multiply into the tens of billions! Many industrial organizations already see considerable value in IIoT technology as a complementary service to Big Data analytics.


8 Content Marketing Trends To Watch Out For In 2017

Regardless of your expertise in the growing realm of content marketing, one of the most important factors that goes into successfully marketing your brand is knowing how to use your time and budget to effectively relate to an evolving marketplace. ... One of the best ways for brands to capture attention is by creating interactive content. According to a recent study done by The Content Marketing Institute, 81% of the marketers surveyed said, “Interactive content grabs attention more effectively than static content.” Users today like to feel involved in the content they consume. Some of the popular ways brands are implementing interactive content is though quizzes, polls, or assessments.


Conquering the Challenges of Cloud Migration

If you haven't already, you're going to move something to the cloud at some point in the future. Even if you are not sure that a cloud service is right for you, you still need to investigate the cloud migration process to be able to make an informed decision -- even if you ultimately decide not to go that route. If you are not an expert in cloud migration -- I assume most of you are not -- there are services that can help you be successful. Once you decide to migrate some functions to the cloud, you will discover that this is only the beginning. Likely, more functions will be moved spanning years of IT and UC operation. Along this journey, many challenges will surface. Among the most common difficulties is the task of properly maintaining existing application services during the migration. Other challenges will be not disrupting the user experience or weakening the security you already have.



Quote for the day:


"The function of leadership is to produce more leaders, not more followers.” -- Ralph Nader