AI And The Evolution Of Software Development
A quick glance into the respective futures of data science, information technology, business, and industry would reveal a common thread – artificial intelligence.
2016 alone saw substantially increased activity in the realm of AI in the form of machine learning acquisitions by major tech corporations, the launch of several AI platforms by companies such as Amazon and Google, and significant levels of investment in AI startups.
Students currently enrolled in a software development degree program are in an advantageous position to develop the skills and experience that will make them attractive to tech companies looking to fill AI development, data analytics, IoT, bot development, and natural language processing positions.
How Many Languages Do You Code?
One of the primary deciding factors in the hiring process for AI positions in tech firms will be proficiency in programming languages associated with machine learning algorithms and data analytics.
“First of all, we see that one size does not fit all,” Jean-Francois Puget, distinguished engineer and machine learning authority at IBM, reports in his article, “The Most Popular Language For Machine Learning Is…” on IBM’s DeveloperWorks blog. The article details the results of Puget’s Indeed.com trend search covering programming languages included in job offers.
“A number of languages are fairly popular in this context,” he says. “Second, there is a sharp increase in popularity for [all programming languages], reflecting the increased interest in machine learning and data science over the last few years.
“Third, Python is the clear leader, followed by Java, R, then C++. Python’s lead over Java is increasing, while the lead of Java over R is decreasing. Fourth, Scala growth is impressive. It was almost non-existent three years ago and is now in the same ballpark as more established languages.”
Other languages capable of being used in either machine learning, data science, or both include Javascript, C, Julia, Lua, Lisp, Prolog, and Google’s Go language. Obviously, nobody expects programmers to be completely versed in every language, but becoming comfortable in the most popular languages and familiarizing oneself with a handful of others will look good on a software developer’s résumé.
Bots, Bots, And More Bots
Software development students interested in AI and current developers wishing to transition into a new career can take several steps to increase their chances of getting hired.
First and foremost, working knowledge of the programming languages used in AI is essential. Of these, Python, R, Java, and C++ are a good starting point. All are used in both weak and strong AI.
Weak, or narrow, AI is designed to focus on a single task. Siri is one example, and most AI at work in the world today falls under this category. Strong, or true, AI is a level of intelligence relatively equal to that of a human being. A strong AI should be able to accomplish most of the same tasks that a person could. A third type, called superintelligence, which could surpass human intelligence, is only theoretical at this point.
An aspiring AI programmer can start with simple bots. “A bot is the most basic example of a weak AI that can do automated tasks on your behalf,” explains AI expert Shashank Chaudhary in his article, “Artificial Intelligence 101: How To Get Started,” on the HackerEarth blog.
“Chatbots were one of the first automated programs to be called ‘bots.’ You need AI and ML (machine learning) for your Chatbots. Web crawlers used by search engines like Google are a perfect example of a sophisticated and advanced bot.”
Bots also are being used in Facebook Messenger. “Facebook calls them ‘chat extensions.’ They’ll serve not just as group bots, but as an extremely powerful form of smart discovery,” writes programmer and tech writer Matthew Black in his blog post, “Live From F8 – ‘Group Bots’ With Messenger Chat Extensions,” on ChatBotsMagazine.com. “Until today, bots were exclusively a 1:1 experience. You would message a bot and only have a singular conversation.
“Now, with chat extensions, bot developers can create rich experiences directly in-line,” he says ”Bots can now have full features, similar to apps, and allow for multiple users within a single bot conversation – group conversations.”
Time To Publish
The rising popularity of bots presents the perfect opportunity for programmers to jump on the AI bandwagon while simultaneously polishing their AI and ML skills.
Once a programmer has a handful of working AI bots or other apps to his or her credit, the next step is publishing the work online. Sites such as GitHub showcase tech accomplishments the way portfolios do for writers or artists.
“One of the best ways to garner eyeballs is to broadcast,” according to “How To Become An Artificial Intelligence Engineer” on LiveEdu.tv. “Artificial Intelligence is atop the new technology evolution, and almost everyone is interested in learning something new. Recruiters nowadays are also interested in watching candidates code on projects before calling them for a personal interview. So, as a learner, you are in a win-win situation if you decide to broadcast your projects.”
GitHub hosts finished projects while other sites, including LiveEdu.tv, allow for ongoing coding projects to be broadcast live, while the programmer is still programming.
“Your reputation is yours and is portable between companies,” explains magikcraft.io founder Josh Wolf in his article, “The Impact GitHub Is Having On Your Software Career, Right Now” on Medium.com.
“GitHub is a social network where your social capital, created by your commits [changes to your file] and contribution to the global conversation in whatever technology you are working, is yours – not tied to the company you happen to be working at temporarily.”
Once a body of work is available for prospective employers to view online, a programmer can focus on reading more about AI, studying other coders’ work, concentrating on sub-fields within the larger AI community, and participating in open-source artificial intelligence projects.
The Changing Landscape Of Software Development At Maryville University
Machine learning, deep learning, bots, natural language processing, AI programming other AI applications autonomously – the future of software development involves freeing up the time developers spend on menial, monotonous tasks so that programmers can concentrate on improving AI algorithms and focusing on creativity.
Maryville University’s Online Masters Degree in Software Development delivers a top-ranked, competitive education in development for computer programs, web applications, and cutting-edge technologies. Data structures, web applications, object-oriented coding, agile systems analysis, and advanced topics are covered in this online post-graduate program.
Contact Maryville University today to learn more about software development and other online programs.
Sources:
The Most Popular Language For Machine Learning Is… – https://www.ibm.com/developerworks/community/blogs/jfp/entry/What_Language_Is_Best_For_Machine_Learning_And_Data_Science?lang=en
Artificial Intelligence 101: How To Get Started – http://blog.hackerearth.com/2015/12/artificial-intelligence-101-how-to-get-started.html
Live From F8 – ‘Group Bots’ With Messenger Chat Extensions – https://chatbotsmagazine.com/live-from-f8-group-bots-with-messenger-chat-extensions-641a3d66b367
How To Become An Artificial Intelligence Engineer – http://blog.liveedu.tv/become-artificial-intelligence-engineer/
The Impact GitHub Is Having On Your Software Career, Right Now… – https://medium.com/@sitapati/the-impact-github-is-having-on-your-software-career-right-now-6ce536ec0b50