Introduction
AI research follows two distinct, and to some extent competing, methods, the symbolic (or “top-down”) approach, and the connectionist (or “bottom-up”) approach. The top-down approach seeks to replicate intelligence by analyzing cognition independent of the biological structure of the brain, in terms of the processing of symbols—whence the symbolic label. The bottom-up approach, on the other hand, involves creating artificial neural networks in imitation of the brain’s structure—whence the connectionist label.
What is Artificial Intelligence?
Artificial intelligence (AI), is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks—as, for example, discovering proofs for mathematical theorems or playing chess—with great proficiency.
How does AI Work?
Less than a decade after breaking the Nazi encryption machine Enigma and helping the Allied Forces win World War II, mathematician Alan Turing changed history a second time with a simple question: “Can machines think?” Turing’s paper “Computing Machinery and Intelligence” (1950), and its subsequent Turing Test, established the fundamental goal and vision of artificial intelligence. At its core, AI is the branch of computer science that aims to answer Turing’s question in the affirmative. It is the endeavor to replicate or simulate human intelligence in machines. The expansive goal of artificial intelligence has given rise to many questions and debates. So much so, that no singular definition of the field is universally accepted.
Types of Artificial Intelligence
Reactive Machines
A reactive machine follows the most basic of AI principles and, as its name implies, is capable of only using its intelligence to perceive and react to the world in front of it. A reactive machine cannot store a memory and as a result cannot rely on past experiences to inform decision making in real-time.
Limited Memory
Limited memory artificial intelligence has the ability to store previous data and predictions when gathering information and weighing potential decisions — essentially looking into the past for clues on what may come next. Limited memory artificial intelligence is more complex and presents greater possibilities than reactive machines.
Self-awareness
Once Theory of Mind can be established in artificial intelligence, sometime well into the future, the final step will be for AI to become self-aware. This kind of artificial intelligence possesses human-level consciousness and understands its own existence in the world, as well as the presence and emotional state of others.
Evolution of AI
IFM is just one of countless AI innovators in a field that’s hotter than ever and getting more so all the time. Here’s a good indicator: Of the 9,100 patients received by IBM inventors in 2018, 1,600 (or nearly 18 percent) were AI-related. Here’s another: Tesla founder and tech titan Elon Musk recently donated $10 million to fund ongoing research at the non-profit research company OpenAI — a mere drop in the proverbial bucket if his $1 billion co-pledge in 2015 is any indication. And in 2017, Russian President Vladimir Putin told school children that “Whoever becomes the leader in this sphere [AI] will become the ruler of the world.” He then tossed his head back and laughed maniacally.
Future of AI
Some sectors are at the start of their AI journey, others are veteran travelers. Both have a long way to go. Regardless, the impact artificial intelligence is having on our present day lives is hard to ignore:
- Transportation: Although it could take a decade or more to perfect them, autonomous cars will one day ferry us from place to place.
- Manufacturing: AI powered robots work alongside humans to perform a limited range of tasks like assembly and stacking, and predictive analysis sensors keep equipment running smoothly.
- Healthcare: In the comparatively AI-nascent field of healthcare, diseases are more quickly and accurately diagnosed, drug discovery is sped up and streamlined, virtual nursing assistants monitor patients and big data analysis helps to create a more personalized patient experience.
- Education: Textbooks are digitized with the help of AI, early-stage virtual tutors assist human instructors and facial analysis gauges the emotions of students to help determine who’s struggling or bored and better tailor the experience to their individual needs.
Conclusion
Artificial intelligence is impacting the future of virtually every industry and every human being. Artificial intelligence has acted as the main driver of emerging technologies like big data, robotics and IoT, and it will continue to act as a technological innovator for the foreseeable future. AI is projected to have a lasting impact on just about every industry imaginable. We’re already seeing artificial intelligence in our smart devices, cars, healthcare system and favorite apps, and we’ll continue to see its influence permeate deeper into many other industries for the foreseeable future.
References
- https://www.builtin.com
- https://www.quantummagazine.com
- https://www.britannica.com
