Alan Turing and Machine Learning
The concept of artificial intelligence starts back in the 1950s, with Alan Turing, a young British polymath who explored the mathematical possibility of artificial intelligence. Turning believed that we as humans use available information and reason in order to solve problems and make decisions. So why couldn’t machines do the same thing? This ended up being the base of his framework for a paper he wrote in 1950’s titled “Computing Machinery and Intelligence”, which he discussed how to build intelligent machines and how to test their intelligence. This personally was amazing to read about, considering the how long ago he wrote the paper. It was truly a concept, and idea beyond the technology capabilities at that time. However, development in computing have taken Turning’s concept and we now are closer to what he foresaw back in the 1950’s. Nicholas Ismail who is an editor focused on smart technologies for Information age, wrote “The history of Machine Learning (ML) has been full of surprises, acclaimed, abandoned and rediscovered approaches, covering all the range from knowledge-intensive and symbolic approaches, to data-intensive and statistical ones.”
Artificial Intelligence, and Machine Learning have become the focal points of recent innovations, and developments in computing. Companies like Google, Apple, and Amazon are among those inching closer to unlocking its true potential. Artificial intelligence can be viewed as a hierarchical term that can be used to describe processes of intelligent automation, like machine learning, natural language processing (NLP), cognitive computing, and deep learning. Among them machine learning is the process that has found widespread acceptance among enterprises. Organizations have found success by integrating machine learning into their enterprise software to uncover predictable and data driven models, which allow them to automate internal processes. (Saratchandran, 2018)
Traditional Enterprise Software
When you begin to think of traditional Enterprise software one thing that comes to mind is a software application used by an organization for meeting that organizations specific needs. However, businesses today are now taking advantage of machine learning. They’re finding ways to improve operations, and capitalizing on the innovation to improve their customer experience. Automation is the key ingredient in the way businesses are changing their environment across many industries to deliver innovative opportunities for automated products. This has been a tough topic for organizations decision-makers, as they are becoming more increasingly aware of the advantages and benefits of AI and automation. As this new breed of technology continues to have break-troughs it has also presented challenges, risks, and dangers in regards to the workforce. Just last year, World Bank chief Jim Kim Yong, indicated that automation threatens 69 percent of India’s jobs, and up to 77 percent in China. As an example, Ocado a billion dollar retail giant whose headquarters are based out of London, is currently in the process of converting their warehouses with robot-operators. The use of AI is allowing Ocado to eliminate the human element to their operations. This showcases two possible outcomes for future of AI and that’s either the potential to disrupt the workforce, or how industries will evolve and thrive using AI. While AI can be very appealing to an organizations infrastructure it’s going to be important to consider the possible economic down fall of these implementations.
This year, an audience of about 4,000 exhibitors attended the Las Vegas Convention Center halls, showcasing the latest in high-tech products, devices and services. Experts indicated that the top trends at this year’s Consumer Electronic Show (CES) event included Artificial Intelligence (AI) and the ‘Internet of Things.’ ‘Artificial intelligence and machine learning, they come together and you’ll find it in cars, in the home, in all these sorts of devices,’ says Michael Josh from GadgetMatch.com tech website. What it comes down to is eliminating the guess work out of mundane tasks so we don’t have to think or worry about it ourselves. A good example is many of our smart phones, I remember when camera phones were a new trending item. We’d take them out have to adjust settings, get the flash ready, all for the goal of taking that perfect picture. Now we have phones that we can set to auto-mode and it can decipher what optimal settings to use in order for us just too simply push a button to take that perfect picture.
Immediate Future
This is just a small example of what AI is doing for us, and what we’re going to continue seeing more of in the future. “In the immediate future, AI language is looking like the next big thing. In fact, it’s already underway. I can’t remember the last time I called a company and directly spoke with a human. These days, machines are even calling me!” (Anyoha, 2017) If we look at recent trends, sales in the United States for smart speakers have more than tripled to nearly 25 million in 2017, roughly 11 million of those sales came during the holiday quarter, according to a Consumer Technology Association (CTA) estimate. (Press, 2018) In 2018, growth is expected to reach close to 40million, as Apples’ HomePad join the competitive market. At the CES, Amazon’s Alexa and Google’s Assistant controlled everything, such as internet-connected lights, locks, and laundry machines as a showcase of what the future has instore for us. (Press, 2018) I personally have used Google’s Assistance in my home, and it’s learned and assisted my family with useful information. It provides us with morning weather, daily commute information, and simple questions my children have for it. It almost feels like it’s become part of our family in some sort of weird technology way. The important thing I’ve come to realize is that it’s all made possible by AI and machine learning.
It’s becoming more obvious that machine learning and AI is at the center point of most organizations current or future strategies. We are giving computers and the internet of things the opportunity to learn our daily patterns without any explicit programming. Many industries are now faced with the critical decision to adapt to stay ahead of the curve or to stay stagnate in the adoption of AI. The outcome in time will decipher if these pivotal moves are in the best interest of these industries and our economy. The important element we have to consider is small business owners, and larger organizations have always looked for ways to operate more efficiently. That has always entailed investing in their infrastructure, and trying to utilize new technology to their advantage for growth. Now with how rapidly AI technology is evolving decision-makers will have to consider the potential impacts this will have in countries’ economies. When you really sit-back and think of potential economic issues being driven by new technology, that in itself is an indication of the role and how powerful AI will be in our future.
