With stiff penalties for being caught and the whiff of secretive underground or even nefarious acts, computer hacking can be seen as a somewhat dubious pursuit. Not all hackers operate with the motive of emptying your Paypal account, however; there are many hackers who utilize their skills to aid companies in locating security flaws ("penetration testing") or engage in hacking with the goal of becoming cyber-freedom-fighters that champion simple human freedoms, such as the right to free speech.

Computer hacking is as much an art as it is a skill. At its simplest distillation, hacking is the systematic search for chinks in programming armor. While advanced problem-solving, intuition and sophisticated understanding of programming languages are a distinct advantage, there does exist a number of push-button programs that computing wizards have written allowing those less sophisticated in the art of hacking to break into remote computers in a variety of ways. Because of this new ubiquity, today's hackers no longer need to be a programming Wunderkind; they simply need to know where to download software and be able to turn on a computer. It really is that simple and the implications can be disturbing.

Phishing, Push-Button Programs and Brute Force Tactics

There's no need to crack a company's firewall if you have direct physical access to their computers. One aspect of hacking is the impersonation of an employee or service worker with the goal of gaining access to a company's database, where the hacker can then unleash whatever havoc he or she has planned into the system. Another is to engage in simple phishing techniques, such as impersonating an employee who forgot their password and needs help logging into the system.

Because such impersonations often fail thanks to companies becoming more security-conscious, taking over operations of a computer remotely is often the preferred method of gaining access. Such attempts can be facilitated in a variety of ways. One is the brute-force method, in which a program such as SQLmap, Nmap or Burpsuite is used; running one of these programs is analogous to trying every doorknob in a neighborhood to see which house is unlocked. Using a variety of different parameters, these programs can find access to a vulnerable computer or network in less than a minute.

Hackers can also attempt to gain access with a program like Metasploit. With literally a few clicks of a mouse, access to a remote and vulnerable computer can be achieved by a relative newbie. With a related hacking aid, called Meterpreter, a backdoor is created that allows access into an operating system. It does not install itself onto the remote computer, running instead using the computer's memory; in fact, Meterpreter can hide itself inside the operations of a perfectly valid program, so it cannot be detected even by sophisticated programmers. Once engaged, it allows a remote user carte blanche access to the system in question.

Where to Learn the Art of Hacking

Of course, for those who wish to learn the actual skills rather than download someone else's hack, there are a number of practice sites that pose an increasingly difficult set of challenges intended to train neophytes in the art of hacking. For example, Hack This Site starts beginners with the goal of cracking simple flaws in coding scripts or software such as HTML, Unix, Javascript and Apache. Their structured series of tests increase in complexity, incorporating real-word scenarios and even old-fashioned "phone phreaking" challenges that recall the bygone golden age of hacking skills displayed by Matthew Broderick in "WarGames."

Using just these simple tools and free practice sites, beginners have a powerful array of hacking resources just a simple mouse click away.

Machine learning systems are equipped with artificial intelligence engines that provide these systems with the capability of learning by themselves without having to write programs to do so. They adjust and change programs as a result of being exposed to big data sets. The process of doing so is similar to the data mining concept where the data set is searched for patterns. The difference is in how those patterns are used. Data mining's purpose is to enhance human comprehension and understanding. Machine learning's algorithms purpose is to adjust some program's action without human supervision, learning from past searches and also continuously forward as it's exposed to new data.

The News Feed service in Facebook is an example, automatically personalizing a user's feed from his interaction with his or her friend's posts. The "machine" uses statistical and predictive analysis that identify interaction patterns (skipped, like, read, comment) and uses the results to adjust the News Feed output continuously without human intervention. 

Impact on Existing and Emerging Markets

The NBA is using machine analytics created by a California-based startup to create predictive models that allow coaches to better discern a player's ability. Fed with many seasons of data, the machine can make predictions of a player's abilities. Players can have good days and bad days, get sick or lose motivation, but over time a good player will be good and a bad player can be spotted. By examining big data sets of individual performance over many seasons, the machine develops predictive models that feed into the coach’s decision-making process when faced with certain teams or particular situations. 

General Electric, who has been around for 119 years is spending millions of dollars in artificial intelligence learning systems. Its many years of data from oil exploration and jet engine research is being fed to an IBM-developed system to reduce maintenance costs, optimize performance and anticipate breakdowns.

Over a dozen banks in Europe replaced their human-based statistical modeling processes with machines. The new engines create recommendations for low-profit customers such as retail clients, small and medium-sized companies. The lower-cost, faster results approach allows the bank to create micro-target models for forecasting service cancellations and loan defaults and then how to act under those potential situations. As a result of these new models and inputs into decision making some banks have experienced new product sales increases of 10 percent, lower capital expenses and increased collections by 20 percent. 

Emerging markets and industries

By now we have seen how cell phones and emerging and developing economies go together. This relationship has generated big data sets that hold information about behaviors and mobility patterns. Machine learning examines and analyzes the data to extract information in usage patterns for these new and little understood emergent economies. Both private and public policymakers can use this information to assess technology-based programs proposed by public officials and technology companies can use it to focus on developing personalized services and investment decisions.

Machine learning service providers targeting emerging economies in this example focus on evaluating demographic and socio-economic indicators and its impact on the way people use mobile technologies. The socioeconomic status of an individual or a population can be used to understand its access and expectations on education, housing, health and vital utilities such as water and electricity. Predictive models can then be created around customer's purchasing power and marketing campaigns created to offer new products. Instead of relying exclusively on phone interviews, focus groups or other kinds of person-to-person interactions, auto-learning algorithms can also be applied to the huge amounts of data collected by other entities such as Google and Facebook.

A warning

Traditional industries trying to profit from emerging markets will see a slowdown unless they adapt to new competitive forces unleashed in part by new technologies such as artificial intelligence that offer unprecedented capabilities at a lower entry and support cost than before. But small high-tech based companies are introducing new flexible, adaptable business models more suitable to new high-risk markets. Digital platforms rely on algorithms to host at a low cost and with quality services thousands of small and mid-size enterprises in countries such as China, India, Central America and Asia. These collaborations based on new technologies and tools gives the emerging market enterprises the reach and resources needed to challenge traditional business model companies.

The name placard in your cube might not say anything about sales, but the truth is that everyone, employed as such or not, is a salesperson at some point every single day. In the traditional sense, this could mean something like pitching your company’s solutions to a client. In the less-traditional sense, it could mean convincing your child to eat their vegetables. Yet for those two drastically different examples and everything in between, there is a constant for successful sellers: unveiling the “Why.”

Spending time and energy making prospects understand why you do what you do instead of exactly what it is you do or how you do it is not a new concept. But I’m a firm believer that proven concepts, no matter how old and frequently referenced they are, can’t be repeated enough. This idea has recently and fervently been popularized by marketer, author, and thinker extraordinaire Simon Sinek via his 2009 book, Start With Why. You can learn about him here on Wikipedia or here on his site. To begin, let me suggest that you watch Sinek’s TED talk on Starting With Why here on YouTube before reading any further. I’ll let him take care of the bulk of explaining the basics, and then will offer some ideas of my own to back this up in the real world and explore the best ways to start thinking this way and apply it to your business.

First, a little on me. After all, if I were to practice what Sinek preaches, it would follow that I explain why it is I’m writing this piece so that you, the reader, not only have a good reason to pay attention but also understand what drives me on a deeper level. So, who am I? I’m an entrepreneur in the music space. I do freelance work in the realms of copywriting, business development, and marketing for artists and industry / music-tech folks, but my main project is doing all of the above for a project I’ve been on the team for since day one called Presskit.to. In short, Presskit.to builds digital portfolios that artists of all kinds can use to represent themselves professionally when pitching their projects to gatekeepers like label reps, casting directors, managers, the press, etc. This core technology is also applicable to larger entertainment industry businesses and fine arts education institutions in enterprise formats, and solves a variety of the problems they’re facing.

Not interesting? I don’t blame you for thinking so, if you did. That’s because I just gave you a bland overview of what we do, instead of why we do it. What if, instead, I told you that myself and everyone I work with is an artist of some sort and believes that the most important thing you can do in life is create; that our technology exists to make creators’ careers more easily sustainable. Or, another approach, that we think the world is a better place when artists can make more art, and that because our technology was built to help artists win more business, we’re trying our best to do our part. Only you can be the judge, but I think that sort of pitch is more compelling. It touches on the emotions responsible for decision making that Sinek outlines in his Ted Talk, rather than the practical language-based reasons like pricing, technicalities, how everything works to accomplish given goals, etc. These things are on the outside of the golden circle Sinek shows us for a reason – they only really matter if you’ve aligned your beliefs with a client’s first. Otherwise these kind of tidbits are gobbledygook, and mind-numbingly boring gobbledygook at that.

Today we live in the age of technology. It seems like everyone owns at least one computer, but few actually know how they work. We hear about Java tutorials and C# programming, but why are these things important?

There has been an increasing demand for those who are proficient in web development. It is a job field that has grown substantially in the past decade, and it is still continuing to flourish with no signs of stopping. Learning a web language is not only a useful skill, but a necessary one. So why, out of all of the available web languages, is Java the most valuable?

·         First off, it is a simple language that is easily learned and well known.

·         Java has been around for awhile now, and has earned its place as one of the pillars of modern day computer architecture. Information on Java is abundant, and ranges from online tutorials to books, such as "Java for Dummies."