A few decades ago, anything to do with machines and artificial intelligence was seen as science fiction. Take Star Wars or any other movie that had fictional machine intelligence, and you'll see that they were all based on some planet other than Earth. Maybe script writers and directors of those days thought machine intelligence is beyond the realm of human understanding.
How wrong they were. Today, machine learning algorithms and artificial intelligence are becoming an integral part of our everyday life. And it's only going to increase, simply because the algorithms that teach machines to learn and perform are getting more sophisticated by the day. Currently, thousands of researchers are working on these algorithms to make them better and more efficient, so get ready -- they are going to drive every aspect of our life, including our businesses.
If you're wondering why they should be such an important part of our lives, let's start with a relatively simple situation. Let's say, you have to identify a particular letter in the alphabet, say "E", every time someone writes it. You can do it, say a thousand times, but will you be able to analyze zillions of data and identify this letter every time? What a waste of time and energy would that be for you. Instead, how cool would it be if a machine can do this task for you? Even so, how will you train your machine to solve it? A lot of questions, but nevertheless they are important ones that will give you an insight into the power of machine learning algorithms.
It's harder than you may think to train these machines because each person writes the letter "E" a little differently from others. In other words, no two handwriting samples are the same, so no two "Es" will be the same.
In the past, programmers had to feed millions of variations of "E" to the system, and it'll identify the letter only if it matched with any of the data. This was time-consuming and an inefficient way of solving a problem, not to mention the fact that the solution was highly limited.
Today, you can resolve it more efficiently. What you can do is teach the machine to look for certain patterns, so it can intuitively learn and identify all possible variations of the letter. For example, if you tell the machine to look for a vertical line, and three horizontal lines - one at the top, middle, and bottom -- it should be able to find all variations of letter "E" for you. This way, you don't have to feed in millions of variations of the letter. Rather, you can use algorithms to teach machines to look for certain patterns. Undoubtedly, the results will be more accurate within the quickest time possible. This is just a minor example of what machines can do, if you "teach" them well.
If that impressed you, welcome to the world of machine learning algorithms. Before we go into why it'll drive businesses in the future, let's briefly see what machine learning exactly is, and why it has become so prominent.
What is machine learning?
In simple words, machine learning is a change in the way we write programs. Earlier, we used to write a program and ask it to perform a particular result based on the data that was fed to it. Today, we are teaching the machine to find patterns from the data that we feed to it. We teach the machine to find patterns based on a set of instructions or algorithms, and in turn, this gives us new insights into the same information.
The obvious advantage with machine learning is it can find multiple patterns from tons of data with the highest level of accuracy -- something that is impossible for humans to do on an everyday basis.
So, why is machine learning so advanced today? What transformed it from an execution machine to a learning one?
According to Lance Olson, director for Cortana Intelligence at Microsoft, three important trends have given a big boost for machine learning:
- Growth of data: As you already know, data has grown by leaps and bounds over the last few years. The emergence of IoT and the ever-growing number of connected devices have led to a massive explosion of data. More importantly, much of this data is born digitally, so it can be fed directly to machines.
- Cloud maturity: Cloud capabilities have become more mature, and this has transformed the way we design systems. We no longer have to build every capability from scratch. Instead, we can use pre-existing components, storage, and infrastructure to build scalable and flexible systems that are best suited for our business.
- Maturity of algorithms: Humans have also learned to generate algorithms that have greater accuracy and flexibility than before. A few years back, speech recognition software used to get thrown off with new accents and background noises. But today, these algorithms can understand pretty much any accent, and they have the ability to filter out unwanted background noise with the highest levels of accuracy. Much of these advancements can be attributed to the growing ability of human intelligence to create more precise algorithms. After all, we're also evolving!
In other words, a combination of technological advancements and better application of human intelligence has led to the development of machine learning algorithms.
Now that we have a fair idea of machine learning, let's look at some areas where it can become an integral part of business operations in the future.
The manufacturing sector is known for expensive machines that require high capital expenditure. Machine learning algorithms can provide advance warnings about system failure, so the maintenance crew can be ready with a backup, or can make plans to repair the faulty system at the earliest. This will ensure minimum downtime and loss.
In fact, this predictive maintenance is useful not just for the manufacturing sector, but also for all machine-based applications, whether they be elevators or airplane engines.
Supply chain management
Machine learning algorithms can help your business to predict demand better. This way, you'll know how many units of a product are needed in a particular region, so you can distribute your products more efficiently. And of course, there's no more loss due to wrong inventory estimates.
These algorithms will give you an accurate market segmentation, so you can come up with the right marketing programs and campaigns to reach out to your target audience. Such an approach is sure to improve the ROI of your marketing budget.
Customer understanding is probably the biggest benefit you'll gain from machine learning. When the digital data created by customers is analyzed by these machines, it can give you a precise idea of the background of your customers, their preferences, and can even predict what they're going to do next based on their past habits. With this understanding, you can give proactive suggestions for your customers, thereby increasing your sales and revenue. In addition, it also helps you build a deep and long-term relationship with customers, and that is sure to augur well for your business.
Machine learning can help to not only automate much of the record-keeping process, but can also provide valuable insights from this information such as, when a patient is due for the next checkup, disease identification, risk stratification, proactive health management, and more.
Want to know which stocks are the safest investment? Need to make intelligent guesses about market swings on any given day? Machine learning may have the answers for you, as it can scour through millions of data to form meaningful patterns that, in turn, can provide answers to your questions. A lot of financial companies today are already turning to machines to evaluate credit worthiness and for risk analysis and regulation.
Another major area where machines will play a big role in the future is energy. From smart grids to renewable energy, they're already involved in ensuring that energy is properly generated and distributed, based on the needs of different regions. It won't be long before the entire sector will be automated with the help of these smart machines.
The above areas provide a glimpse into the huge potential of machine learning algorithms, and the myriad ways in which they can be used to improve the overall quality of our life.
In short, machines have evolved in the last few years to make the right predictions based on existing data. We have made them intelligent through our algorithms, so their usefulness and capabilities have increased multi-fold. Today, they are used in every major sector to improve performance and reduce inefficiencies, besides providing personalized service to customers.
Are you poised to tap into these machine learning capabilities to enhance the operations of your business, and to add value to your customers?