Artificial Intelligence (AI) has made a huge impact across several industries, such as healthcare, finance, education, business, telecommunications, and social media, and is expected to disrupt even more industries in the future. Artificial Intelligence has the potential to give rise to such new industries, which we can’t imagine in the present. There is a huge demand for AI Engineers and AI professionals to implement AI to use its potential to the maximum.
In this blog, we have compiled a list of Artificial Intelligence viva questions and their answers:
Artificial Intelligence | Machine Learning | Deep Learning |
In 1950-Alan Turing proposes the ‘Turing test’ to check the intelligence of machines. | In 1952-Arthur Samuel wrote the first computer learning program. | In the mid-1960s-Mathematician, Alexey Ivakhnenko created small but functional neural networks. |
AI represents imitated intelligence in machines. | ML is the practice of getting machines to make decisions without being programmed. | DL uses artificial neural networks to solve complex problems without using any inputs. |
Artificial Intelligence is a tool. | Machine Learning is a way to build the tool. | Deep Learning is a type of ML to achieve Artificial Intelligence. |
Aims to build machines capable of thinking like humans. | Aim to enable the machines to recognize past experiences. | Aim to solve complex problems, like the human brain, through various algorithms. |
Requires a huge amount of data to work. | Can work with fewer data as compared to AI and Deep Learning. | Requires a huge amount of data as compared to ML. |
Artificial Intelligence is a computer science field wherein the human brain’s cognitive functions are studied and replicated on a machine or a system. AI is used in widely used for various applications like computer vision, speech recognition, decision-making, perception making, reasoning, and so on.
Snapchat uses Face Detection Technology to provide virtual filters, while Apple uses Face Recognition for FaceID unlock.
Grammarly uses Natural Language Processing algorithms to identify incorrect grammar usage and suggest corrections. It can also provide readability and plagiarism grades.
Facebook, Twitter, and Instagram rely heavily on AI to personalize what you see on your feeds.
Computer scientists train chatbots to impersonate the conversational style of customer representatives using Natural Language Processing.
Netflix, Spotify, and YouTube rely on smart recommendations provided by AI.
Google, Bing, and DuckDuckGo use a quality control algorithm to recognize high-quality content.
Siri, Bixby, and Alexa use AI algorithms to understand and process the commands.
Google Nest uses AI to set room temperatures according to the preference of users.
The simplest machine that can provide output after giving a certain input.
Example- IBM’s chess-playing AI- DeepBlue
The system can store some memory and make decisions accordingly.
Example- Self-Driving cars.
Artificial Intelligence is capable of understanding human emotions, beliefs, intents, and knowledge. Artificial Intelligence expert teams are still working on reaching this stage of AI.
Self-aware machine capable of human-level consciousness with the ability to think, desire, and understand feelings.
Machine learning is a part of AI which provides intelligence to machines with the ability to learn with experiences without being explicitly programmed automatically. It is based on the idea that machines can learn from past data, identify patterns, and make decisions.
It is a software trained to learn famous people’s properties through people answering the questions in the game.
The machine had to train itself by looking at pictures of dogs, cats, stairs, and other objects and comparing them with similar-looking pictures of other objects.
Deep Learning is an AI function that imitates the working of the human brain in processing data and creating patterns for decision making. The neurons and neuron connections inspire the structure of Deep learning in the human brain.
Artificial Neural Networks (ANNs) are a subset of machine learning. They are comprised of node layers containing one or multiple hidden layers and an output layer. If the number of layers, including the input and output layers, is more than three, it is called a Deep Neural Network.
Any Deep Neural network will comprise three types of layers:
We compiled the most relevant questions on topics of Artificial Intelligence, Machine Learning, and Deep learning most concisely and understandably. You can refer to the links below if you need more help with your artificial intelligence training. Several good AI certification courses are being offered worldwide, and Jigsaw Academy is one of the proponents of such studies.
The above-mentioned artificial intelligence interview questions and answers will help you gain extensive knowledge about AI and its related fields. UNext Jigsaw offers PG and diploma degrees in Management and Artificial Intelligence. Learn from industry experts and broaden the horizons of your knowledge.