Whoever becomes the leader in this sphere [AI] will become the ruler of the world.
– Vladimir Putin
Imagine a scenario in the future wherein a machine is identifying the violation of safety events in companies. It can prevent an accident and injury to employees and avoid potential safety issues. A small shoe-box size device is in the making using Artificial Intelligence principles such as computer vision and machine learning, which detect and classify safety events. Known as Onetrack.AI, it keeps an eye on the forklift working in the warehouse for any potential violation and reports it back to the manager for immediate action.
It is one example of many such developments in one of the hottest and fastest-growing Artificial Intelligence fields. It is a prime field under which extensive research and investment are ongoing due to the immense benefits. For example, looking at the patent filed in previous years, significant contributions come from Artificial Intelligence Domains. As per data published in USPTO, United States Patent and Trademark Office, the annual patent application received in Artificial Intelligence at USPTO has increased substantially by 100% from 2002 to 2018. This growth was across organizations and geography, which indicates the importance of Artificial Intelligence in all sectors. While EPO studies suggest, Artificial Intelligence technologies associated with smart connected objects show an annual growth rate of 54.6% since 2010.
As per the Statista article published in Dec 2020, the Artificial Intelligence market is expected to grow dramatically in upcoming years and reach $126 billion by 2025. Many big corporations such as Microsoft, Google, IBM are investing hefty sums in Artificial Intelligence research & developments and start-ups linked to Artificial Intelligence related technologies. So, it makes sense to learn AI and step into this promising career option.
Introduction to Artificial Intelligence
Artificial Intelligence is a compelling and game-changer technology and has existed for a long time. However, it could not be used extensively in the past due to the absence of supporting technologies. Development in supporting technologies in the last decade enabled Artificial Intelligence to come back to its prominence, and finally, It has achieved the necessary focus it deserves. Rapid growth in Artificial Intelligence in recent years can be attributed to multiple related factors.
Some of the essential factors are
- Availability of large data sets in various domains which are helpful to train models.
- Better data storage capacity at a lower cost.
- Enhancement of computation power or more commonly known as processing speed.
- Development and deployment of better infrastructures, big data, cloud platforms.
- Advancement in programming languages.
- Improved neural networking and deep learning models.
What is Artificial Intelligence
Strictly speaking, Artificial Intelligence is a branch of computer science, expected to create smart devices that can perform tasks requiring human-level intelligence. It has subdomains, namely machine learning and deep learning.
Machine Learning
Machine learning involves writing algorithms to allow machines to learn independently using historical data, interpret, and recommend or predict future events with almost no human intervention. It is part of artificial intelligence and works in the tendon with deep learning and data science. Key proficiencies in machine learning include advanced statistics, classifying algorithms, handling large data sets, and so on.
Deep Learning
The human brain consists of complex structures of billions of neurons to perform multiple tasks. It is divided into different parts composed of layers of neurons and arranged in the complex network. Each layer is responsible for processing received data and passing the output to the next layer. The brain performs tasks based on a lot of data. On similar lines, Deep learning, an advanced part of machine learning, involves complicated layers of algorithms and tries mimicking the human brain in terms of structure and functions. Deep learning relies on large data sets to learn and perform operations.
Types of AI
Artificial Intelligence is usually classified in two ways. The first one is based on the ability of machines compared to the human mind.
- Reactive AI has no data storage capabilities. It is based on the human mind’s ability to respond to various situations with no prior experience. Common examples include chess supercomputers, the supercomputer observes the moves and responds with the best possible way to win the game.
- Limited Memory is comparatively more advanced, equipped with storage and learning skills that help machines respond based on historical data. Limited AI technology is extensively used in virtual assistants and personalize search engines.
- Theory of mind AI is yet to be developed. This machine will understand the emotions, thoughts, and beliefs with which it is interacting.
- Self-aware AI can be considered as the final level of development. At this level, machines will understand the emotions with which it interacts and has feelings, beliefs, and desires of its own.
The other way of classification can be as follows.
Weak AI, commonly referred to as Narrow AI. It is primarily focused on machines performing a single task with a high degree of accuracy. However, the operation of devices in narrow AI is very constrained and limited. Common examples include facial recognition, voice assistance, etc. Narrow AI can further be reactive or with little memory.
Strong AI, commonly known as Deep AI or Artificial General Intelligence, At this level, AI will have the ability to learn, understand, and perform similarly to humans. Machines can perform multiple tasks with high accuracy.
ASI stands for Artificial superintelligence, is a distant dream and the hypothetical level which refers to not only emulating human intelligence and behavior, self-awareness but also surpassing human intelligence and ability. ASI is expected to be exceptionally better than humans in every aspect, such as science, art, sports, relationships, etc. ASI will mean higher memory, processing capabilities, improved decision-making, and problem-solving skills.
Artificial Intelligence Application
Artificial Intelligence is pervasive, and it can find its footprints in virtually every industry in one form or the other. Yes, some sectors might have started to see significant use of Artificial Intelligence while others are on the path of completion. Regardless Artificial Intelligence presence cannot be ignored. Some of the applications are as follows.
- DeepMind Technologies, a British subsidiary of Alphabet Inc, works on AI, Created a machine that allows computers to mimic the human brain’s short-term memory.
- Watson, developed by IBM, is a computer system designed to use in medical space. It suggests treatment as per patients’ medical history.
- Google’s driverless cars, along with Tesla’s Autopilot features, are marvels of AI in the automotive space. Features such as automatic parking, navigation, and collision detections are being developed.
- Virtual Assistants such as Siri, Alexa are using AI technologies such as voice recognition to follow instructions. Gradually building capabilities and improving day by day.
- In banking, AI technology is used in various ways, such as fraud detections, customer supports, and anomaly rectifications.
- In finance, Machine learning can help find patterns in data and make future predictions.
