Machine Learning as a sub-discipline of Artificial Intelligence
The machines, learn Autonomously
I don’t know about you, but I have been reading about AI, Machine, and Deep Learning for a long time without ever understanding it. In short, what was it, there are thousands of information on these issues on the internet, but there is never a connection between them, and then I said to myself, I have to go deeper into the topic and understand the various connections. Here’s what I found out.
So, I start trying to understand what exactly Machine Learning is, and I discover that it is not a technology in itself, but a sub-discipline that works with AI.
If we made it clear about AI, in the previous article, which is based on the ability to learn from data from every aspect of human life, we understand that the process that comes with it is crucial as a consequence. And it is in this learning process that Machine Learning enters, which is a sub-discipline of AI with the precise purpose of creating machines that can learn from the data obtained and processed with the AI, autonomously. Machines are computers, smartphones, software, industrial equipment, robots, vehicles, etc.
Machine Learning allows us to effectively apply AI in machines with the same method that uses the human brain that learns from data and not from pre-set rules to develop and improve in fact, we human beings are continuously learning and interpreting from the surrounding environment, and we generally improve over time through our successes and failures. That is where our actions or decisions are based on what we have learned.
Therefore, Machine Learning replicates with AI the same human learning process inside the machines and therefore, instead of giving simple instructions to execute (as happens on the computer) the Machines can now learn for themselves from the AI data they receive, with a machine learning process. We should also mention the existence of a sub-discipline of Machine Learning that is often read on the net which is Deep Learning, in short it is a more advanced process of machine learning, in which there are levels of greater complexity of data processing, about which I will write a next article.
Always taking the human brain as a reference, it is obvious to think that like humans, the more data that machines will receive to learn, the greater the degree of intelligence that they will reach over time. And this is the explanation of the great results and progress that AI has achieved recently, results that were impossible to achieve ten years ago. To make AI work, we need data and that is why we see a huge demand for data accumulation in every sector and human environment, this explains the existence of the technological trend called Big Data. To date, the continuous expansion in terms of the amount of data associated with advances in computing power results in a rapid acceleration of AI learning ability. This means that we are recently observing a rapid infiltration of AI into our daily lives, but above all the transformation imposed on our industries and businesses.
Business, Industries and Work, transformed with Machine Learning
After all I have described, it would now be correct to write that it is in progress, and it will go on for at least a decade, a complete and total transformation of how we see and intend to do business or industry habitually. Everything will change in terms of efficiency by associating AI with Machine Learning to create machines that learn independently, but above all, what will have a greater transformation will be the concept of human work on this Machine and Deep Learning machines based.
AI in Machine Learning will transform many human jobs. IBM planning a complete retraining of more than 120 million workers in the next five years, worldwide. AI in the automation industry will have a particularly significant impact on many jobs. In the same way McKinsey sees it on the future of work, where we will have many jobs that will be lost and new ones that will be born, but in fact almost all jobs will change. The COVID-19 crisis has accelerated this trend and has caused organizations to reevaluate many aspects of work from the past.
“It would be important to avoid having a vision of the dystopian near future where all human jobs will be entrusted to robots, I like to believe that AI will still make our working lives better and more advanced”
It is established that AI in automation and in many industries will have a strong impact on the job, and many current human jobs will disappear in the next 10 or 20 years, but how do I describe AI with Machine Learning will greatly improve human work by making it possible to create new jobs as a replacement for old ones. For example, something similar happened with computer science and the development of the Internet that led to the disappearance of some jobs but in the same way created many others with new skills. In addition, it must be said that machines will become increasingly intelligent and capable of performing human tasks over time, and therefore unique human abilities such as creativity, empathy and critical thinking will become even more valuable in the jobs of the future.
In 2021, there are some industries that have used Machine Learning for their business processes, thanks to Covid-19, achieving great results including:
- The Healthcare and Medical Industry (healthcare professionals can now generate large volumes of data to make in-depth clinical decisions in less time)
- Finance and Banking (ML applications are explored and used in the areas of investment modeling, trading, risk prevention, and consumer behavior analysis customer investment)
- The Media and Entertainment Industry (here ML is useful for predictive modeling, which plays an important role in communicating with customers so that their future demands can be anticipated, which means making investments with better knowledge)
- The Commerce and Retail Industry (here the ML is assisting the retail and commerce industry in reinventing the supply chain, inventory management, user behavior prediction, and customer analytics main trends)
- The Manufacturing Industry (here ML is and will become a key element with data connectivity, automation, real-time error detection, Cost Reduction, Asset Tracking, Supply Chain Visibility, and Warehouse Efficiency)
How to Prepare for the Future Using the Machine Learning
All companies in every sector cannot afford to neglect the existence of AI-based Machine Learning, for their present and future business processes, even regarding lack of funding recognized by banks or states if not under adoption of these innovative digital technologies, so they will and will only be able to find answers to the question:
How can I use AI-powered Machine Learning for my business?
Today, companies typically use AI to improve their business in three ways:
- Develop more efficient products
- Create and deliver more services efficient
- Making Business Processes more efficient
Given these three approaches or ways of using AI, you will need to prepare a robust strategy to get the most out of AI that is connected to your business strategy. To put it simply, you need to look at what your business is trying to achieve, and then understand how using AI with ML can help your business achieve it is intended goals.
