Artificial Intelligence (AI)
AI is well known for its superiority in image and speech recognition, smartphone personal assistants, map navigation, songs, movies or series recommendations, etc. The scope of AI is so much more and expandable that, it can be used in self-driving cars, health care sectors, defense sectors, and financial industries. It is predicted that the AI market will grow to a $190 billion industry by 2025 creating new job opportunities in programming, development, testing, support, and maintenance.
What is AI?
Artificial Intelligence can be described as a set of tools or software that enables a machine to mimic the perception, learning, problem-solving, and decision-making capabilities of the human mind. The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal. The two main subsets of AI are machine learning (the ability of the machine to learn through experience) and deep learning (networks capable of learning unsupervised from data that is unstructured or unlabelled). We have to note here that, deep learning is also a subset of machine learning.
History of AI
In 1943,Warren McCullough and Walter Pitts published “A Logical Calculus of Ideas Immanent in Nervous Activity.” The paper proposed the first mathematic model for building a neural network. Alan Turing published “Computing Machinery and Intelligence”, proposing what is now known as the Turing Test, a method for determining if a machine is intelligent in 1950. A self-learning program to play checkers was developed by Arthur Samuel in 1952. In 1956, the phrase artificial intelligence was coined at the “Dartmouth Summer Research Project on Artificial Intelligence.” In 1963, John McCarthy started the AI Lab at Stanford. There was a competition between Japan and the US in developing a super-computer-like performance and a platform for AI development during 1982-83. In 1997, IBM’s Deep Blue beats world chess champion, Gary Kasparov. In 2005, STANLEY, a self-driving car wins DARPA Grand Challenge. In 2008, Google introduces speech recognition. In 2016, Deepmind’s AlphaGo beats world champion Go player Lee Sedol.
How does AI work?
In 1950, Alan Turning asked, “Can machines think?” The ultimate goal of AI is to answer this very question. In a groundbreaking textbook “Artificial Intelligence: A Modern Approach”, authors Stuart Russell and Peter Norvig approach this question by unifying their work around the theme of intelligent agents in machines. They put forth 4 different approaches: Thinking humanly, Thinking rationally, Acting humanly, Acting rationally.
AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data. AI is a broad field of study that includes many theories, methods, and technologies, as well as the following major subfields:
- Machine learning
- Neural network
- Deep learning
- Cognitive computing
- Computer vision
- Natural language processing.
Stages of AI
There are 3 different stages of AI. The first stage is Artificial Narrow Intelligence (ANI) and as the name suggests, the scope of AI is limited and restricted to only one area. Amazon’s Alexa is one such example. The second stage is Artificial General Intelligence (AGI) which is very advanced. It covers more than one field like the power of reasoning, problem-solving, and abstract thinking. Self-driving cars come under this category. The final stage of AI is Artificial Super Intelligence (ASI) and this AI surpasses human intelligence across all fields.
Examples of AI
- Smart assistants (like Siri and Alexa)
- Disease mapping and prediction tools
- Manufacturing and drone robots
- Optimized, personalized healthcare treatment recommendations
- Conversational bots for marketing and customer service
- Robo-advisors for stock trading
- Spam filters on email
- Social media monitoring tools for dangerous content or false news
- Song or TV show recommendations from Spotify and Netflix
Risk factors of AI
There is always a downside to technology. Though scientists assure that machines may not show any feeling of anger or love, there are many risk factors associated with intelligent machines. The AI is designed in such a manner that it is very difficult to turn off and, in such conditions when in the hands of a wrong person, things could go devastating. AI does the job that it needs to do but it could take dangerous paths to do so. For example, in driving an automated car, if we tell the AI to reach the destination soon, it may take rash and risky routes or may exceed the speed limit causing immense pain for us. Therefore, a key role of AI research is to develop good technology without such devastating effects.