From Siri to self-driving cars, Artificial Intelligence has literally made a huge impact on the markets. Earlier, investing in AI was considered an expense extravagant and to be done only when organizations had the extra budget. But now, it has become an essential component and a major part of businesses.
When we think about Artificial Intelligence vs Machine Learning, you might be forced into thinking that Artificial Intelligence and Machine Learning are quite similar in nature and can be used interchangeably. In reality, despite their differences, AI and ML are the two biggest buzzwords in the arena of transformational technologies. Despite knowing it, we often get confused, only due to our lack of understanding of the basic idea behind each.
In one way you can easily imply that Machine Learning is a subset of Artificial Intelligence, but there are some differences we need to record.
Let us understand each and then deduce their differences.
What is Artificial Intelligence?
In the simplest of terms, when a machine mimics the behaviour of a human, we can understand that Artificial intelligence is applied. Gartner has categorically classified that AI is the biggest game-changer for businesses. Artificial Intelligence is set to become the core of everything that humans interact with for years and years to come.
A look at the data revealed here by Statista, the average revenue growth has shown promising trends worldwide. The growth has been amazing and the journey has taken off organically.
We have all seen that robots are programmable entities that are designed to carry out a string of tasks that we have set aside. But when programmers successfully embed human-like intelligence, emotions and behavior in the mechanism it means that AI has been engineered in the robot or in the entire state of things. So, to understand it better, AI is the simulation of human intelligence in machines that are programmed to think and understand like us humans.
Get a detailed guide on the subtleties of Artificial intelligence with our basic guide.
THE PRIMARY TAKE AWAY FROM AI IS THE ABILITY TO RATIONALIZE AND TAKE DEFINITIVE ACTION THAT BEST SUITS THE ACHIEVEMENT OF GOALS.
As technology grows, the yardsticks that were used to define AI also have become outdated. For Instance, machines that calculate basic functionalities or diagnose text using the optimal character recognition, no longer comes under the purview of Artificial Intelligence because this has now become an inherent computer functionality.
AI for business has been the need of every strategy. AI is already been applied to different industries across various sectors. In the healthcare industry AI is used and tested for dosing drugs and diverse treatment options in patients. It also has a critical role in surgical procedures performed in the operating room.
One of the key drivers of the digital revolution and technology upgradation, and its use in custom web development has taken leaps beyond anyone’s imagination. Read here to see how AI has become a boon to the entire custom web development process.
Other highlighters of AI is the chess playing computer or the self-driving cars. In both the cases, the impending result of the action has to be understood. In the case of chess, winning is the end result and to do that, the computer has to play those moves which will inch it towards victory. In the case of self driving cars too
Source: Techtarget
Some vital stats related to Artificial Intelligence
- 61% of business executives with an innovation strategy say they are using AI to identify opportunities in data that would otherwise be missed. (source:global news wire)
- 61% of business professionals point to machine learning and AI as their company’s most significant data initiative for next year. (source:global news wire)
- 84% of businesses say AI will enable them to obtain or sustain a competitive advantage.(source:Forbes)
- 72% of business decision-makers say AI can enable humans to concentrate on meaningful work. (source:PWC)
- 59% of executives say big data at their company would be improved through the use of AI. (source:PWC)
Benefits of Artificial intelligence
- Robots and Artificial Intelligence will help humans perform their job better. This deadly combination of man and machine will be unstoppable. Pattern identification, digital content evaluation and facial recognition will be huge. Academic research, life sciences, and technology companies are going to benefit a lot from enhanced abilities of Artificial intelligence.
- AI will effectively handle all mundane tasks with extreme efficiency. AI powered smart homes will cut down on energy costs and provide better security.
- AI wearable monitoring devices will enable better diagnostics in the health care sector.
- Highly AI-focussed organizations have already implemented AI on behalf of humans to interact with their customers using different avatars.
- Repetitive jobs which become redundant from the perspective of human involvement, are now tackled by AI which has let humans focus their time on productive tasks.
- Precious data can be extracted thanks to the way in which AI has changed business methodology and ways in which customer is handled.
What is Machine learning?
In the past 50 years, there has been a bombardment of data. The data remains data only when nothing is analyzed out of it. But when underlying patterns and meanings are assimilated from the bundles of data, it becomes information and knowledge for future uses.
Machine learning techniques are used to discover these trends and decode the elemental hidden information that can be useful for businesses. In a way we can say that Machine Learning is a subspace of Artificial Intelligence. Machine learning is an application of Artificial intelligence that provides the system the ability to naturally learn and experience without the need for any explicit programming.
The process of learning involves, observing data, looking for patterns in data and making exemplary decisions based on the data got. The chief aim is to enable the process of learning without the need for human intervention.
BACK THEN ENGINEERS CREATED SOME RULES WITH DATA TO GET ANSWERS FOR QUERIES, BUT MACHINE LEARNING ON THE OTHER HAND USES PAST AND CURRENT DATA TO DISCOVER THE NUANCES BEHIND THE PROBLEM.
Process
The image below clearly indicates that the process of ML is a five step process one followed by the other:
The importance of ML in AI has assumed greater significance over a period of years. As is apparent from the illustration below, ML investment has grained grounds compared to its allies of AI.
Any AI based software put together for your application, will have Machine learning embedded in it as a necessary feature to derive maximum benefit.
According to Forbes, financial services, Insurance and healthcare Machine learning is critical to their success in the respective industry. A little less than 10% of educational institutions believe that AI and Machine learning will have little or no impact on their success.
Machine learning is referred to as the greatest components of Artificial intelligence. It makes work easier and this is primarily the reason why several organisations are infusing more and more funds, making it one of the widest adopted technologies in the world.
Difference between Artificial Intelligence and Machine learning
Now that we have a fair understanding of both AI and ML, we need to check the differences, just to ensure we don’t equate both of them. They are a part of each other but they are surely not synonymous.
| Artificial Intelligence | Machine Learning |
| AI is an emerging technology that enables to machine to replicate human behaviour | Machine Learning is an essential component of AI that allows the program to learn automatically without the need to program it |
| The main goal of AI is to make the machines as smart as a human being | Here the goal is to enable to machine assimilate information and extract important information out of it |
| Here the systems are designed to be intelligent enough to perform tasks like humans | In this case, without the need for any additional programming, it expects the system to learn from the data so collected |
| Artificial intelligence has a wider scope compared because it includes in its sphere several elements including machine learning and deep learning | On the other hand, the scope of machine learning is not as wide as AI |
| AI seeks to create intelligent systems that can handle some of the most complex tasks without much human intervention | Machine learning is about performing those tasks for which the machine has been specifically trained for |
| The main applications of AI are Siri, customer support utilizing chatbots, Online gaming, Intelligent humanoid robot and much more | Here the main applications of ML are Google search algorithm, FB auto-tagging a friend based on image and online recommender system |
| Based on their capabilities, they can be divided into a weak AI, General AI and strong AI | They also can be divided based on their three types namely, Supervised learning, unsupervised learning and Reinforcement learning |
| This includes reasoning and rationalization | This includes learning and self-correction with current data |
| AI deals with structured, semi-structured and unstructured data | ML deals with structured and semi-structured data |
Future of Artificial Intelligence and Machine Learning
Artificial intelligence and associated technologies like Machine learning, will be prevalent in many industries and will be a major part of our daily lives especially in 2020. Gartner has already predicted that by 2020, AI will feature among top 5 business investment fields for about 30% of CIO’s. Both AI and ML are considered to set new benchmarks in the way businesses are conducted.
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