Artificial Intelligence is a big topic in innovation and business. Numerous specialists and industry investigators contend that AI or Machine Learning is the future. Yet a closer examination reveals that it is not just the future, but our present.
Evolving leaps and bounds from when Alan Turing first explored the mathematical possibility of AI, this enigmatic field of computer science has become an integral part of today’s world at large. This fascinating field is progressing rapidly into diverse sectors of modern civilization.
We interact with AI in many ways, whether with Siri and Alexa, or through other forms like smartphones, social media feeds, and music and media streaming services. Currently, more and more organizations are putting assets into Machine Learning. Many are also demonstrating a powerful development in AI items and applications.
What is AI?
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines. The engineers program the machines to mimic human actions- such as prediction and decision making. One of the core characteristics of an Artificially Intelligent machine is its capacity to rationalize and take actions that procure the best chance of obtaining a specific goal.
According to B.J Copeland, professor of philosophy and director of the Turing Archive for the History of Computing, University of Canterbury,
“Artificial intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.”
Hence, Artificial Intelligence intelligently executes tasks that capitulate in creating extensive accuracy, flexibility, and productivity for the entire system. In like manner, AI Engineers also navigate the inner workings of the organization to create and deploy practical models for real-world use. To know more about the responsibilities of an AI Engineer, you can check this blog- Responsibilities of an AI Engineer.
Subsets of Artificial Intelligence (AI)
There are a plethora of methods that fall under the space of Artificial Intelligence, for example- linguistics, bias, vision, robotics, planning, natural language processing, decision science, etc. Let us look into 5 major subsets of Artificial Intelligence:
- Machine Learning (ML)
- Neural Network (NN)
- Deep Learning (DP)
- Robotics
- Computer Vision (CV)
Machine Learning (ML)
Modern computer programs can automatically adapt to, and learn from, new data without human assistance. This is what Machine Learning is. This process functions through Deep Learning techniques. Computer programs can automatically learn by absorbing large amounts of unstructured data such as images, texts, or videos. ML is perhaps the most applicable subset of AI to the average enterprise today.
Neural Network (NN)
The Neural Network (NN) is a part of Artificial Intelligence that utilizes nervous system science (a piece of biology that deals with the nerve and nervous system of the human cerebrum) to merge the aspects of cognitive science with machines so they can perform tasks. Neural Network and Machine Learning combinedly tackle numerous intricate tasks effortlessly.
Deep Learning (DP)
Chris Nicholson, CEO of Pathmind, offers a valuable analogy: Think of a lot of Russian dolls settled within one another. “Deep Learning is a subset of Machine Learning, and Machine Learning is a subset of AI, which is an umbrella term for any computer program that accomplishes something smart.”
Deep Learning brings into service the alleged neural systems, which learn from processing the labeled information provided during training. It then uses this answer key to realize what attributes of the information are expected to build the right yield. Deep Learning powers product and content recommendations for Amazon and Netflix. Furthermore, it also works in the background of Google’s voice-and image-recognition algorithms.
Robotics
Robotics is a fascinating division of the innovative field. This subset of Artificial Intelligence focuses on the design and development of robots. Robotics is an interdisciplinary field of science and engineering that combines aspects of mechanical engineering, electrical engineering, computer science, and numerous other fields. It decides the production, design, operation, and use of robots. Additionally, it also manages computer systems for their control, intelligent results and data change.
Computer Vision (CV)
According to IBM– Computer Vision is a field of Artificial Intelligence that enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs. Computers can then take actions or make recommendations based on that information. If Artificial Intelligence enables computers to think, Computer Vision enables them to see, observe and understand.
AI Applications
There are many sectors that use AI. Artificial Intelligence and like programs are extensively used for research in the medical field to improve the accuracy of programs that detect health conditions and in the creation of innovative technologies such as autonomous vehicles.
Artificial Intelligence is also used in popular programs such as Netflix and Spotify. This type of AI monitors user habits and makes recommendations based on recent activity. Banks use AI systems to monitor member activities to check for identity theft, maintain online security and approve loans. One can find such AI systems in call centers as well. The programs analyze a caller’s voice in real-time to provide information to the call center to help build a faster rapport.
Artificial Intelligence is creating advanced technologies in various fields which in turn creates a more efficient world. When you look at the environment today, you will find that AI-enabled machines are involved in various roles involving transportation, medical procedures, military applications, and even industrial and commercial fields.
As such, the field of Artificial Intelligence is extremely lucrative and offers many career opportunities. To know more about the skills required to become an AI Engineer, you can check this article- Skills Required to become an AI Engineer.
Conclusion
There is no scarcity of challenges that need to be solved today to enable a better tomorrow for our society and the planet. Collaboration between humans and Artificial intelligence can lead to solutions that otherwise wouldn’t have been thought of. These solutions then can be developed and vetted at a pace that wouldn’t be possible if only humans were working on it without AI. Proper use of Artificially Intelligent machines can provide innovative ways of solving extremely challenging problems. It can also provide ways of significantly improving life. AI Engineers are always looking for innovative ways to produce ingenious products that enhance our lives. Check this article that elaborates on what AI Engineering is- What is AI Engineering.
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