Answers to all your questions on AI

Dark Background

We have a lot of baffling questions about AI that we want answers to. We’ve addressed some of the frequently asked questions here. We’ve also added a white paper that explores the topic of AI in depth. 

Don’t forget to get your copy!

AI – what is the definition?

Artificial intelligence or AI has been defined in various ways, through the years. Since it is a combination of complex technologies, the best way to describe it is as a powerful machine that analyzes data quickly and is able to mimic human-like decision-making behavior.

“[AI is] the field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem-solving, and pattern recognition.”


What are some of tasks that machines can accomplish?

Machines can now accomplish tasks that were once possible only by humans. Some of these tasks include

  • Problem solving
  • Interpreting visual cues
  • Speech recognition/Natural language processing

These tasks are accomplished with the help of complex algorithms. Algorithms are intelligent programs that run on various types of hardware or software. The ability of artificial intelligence to infuse into any kind of technology is what makes it both baffling and sophisticated.

Who invented AI?

It would be difficult to pinpoint at one individual as the inventor of artificial intelligence. It evolved over a decade. AI began in ancient history, with myths and stories filled with rumors of machines being endowed with human-like intelligence by its master craftsman. Later on, classical philosophers planted the seeds of modern AI. They described human thinking in terms of mechanical manipulations. This eventually culminated in the invention of the digital computer in the 1940s. This device inspired scientists to discuss and consider the possibility of building an electronic brain that mimics the human brain.

What are some of the AI terms I should know?

AI is a mix of complex technologies. So, as it evolves, the definition and the various terms in the AI glossary keep evolving with it. However, here are some of the terms you should be acquainted with.


It is a set of rules or commands provided to a computer so that it can complete a specific task.

Artificial Neural Network (ANN)

This is a network that is modelled to imitate the human brain. It is done so by creating an artificial neural system using pattern-recognizing algorithms. These algorithms learn, interpret, and categorize sensory information.

Deep learning

Deep learning is a machine learning technique that teaches computers to mimic the way a human mind learns using classification techniques.

Explainable AI

Explainable AI is a type of artificial intelligence that is able to explain its decision-making process.

Machine learning (ML)

ML is a subset of artificial intelligence focused on developing programs that perform specific tasks without too much human interference and mostly relying on patterns and inference.

Natural language processing (NLP)

NLP is a type of machine learning algorithm that help process, interpret, and analyze human language using natural language data.

Is it dangerous?

Well, there are mixed opinions about this. Think of artificial intelligence as a tool. It could work wonders if utilized in the right way, but in the wrong hands, it can be catastrophic. The more important question should focus on what kind of values drives people and organizations that are building this technology.

How will it impact the future?

If you are referring to AI trends for 2020, then we have our bet pinned on the rise of federated learning. Federated learning is a type of machine learning (ML) technique where ML models are distributed over different devices for computation, instead of being computed on large, centralized machines. This results in faster deployment and testing of smarter models, lower latency, and less power consumption, all the while ensuring privacy.

AI is indefinitely evolving and it is being adopted for various use cases ranging from customer churn to asset management. The future beyond 2020 looks bright if we pay enough close attention. We need to understand that we can’t dive into developing a complex technology like AI without considering the long-term effects. We need to seriously consider the ethics and implications surrounding it if we want our future to look bright in the company of artificial intelligence.

This future doesn’t depend on the lines of code that programmers in Silicon Valley. To develop a technology we need teams from multiple disciplines to help us understand how we can integrate this sophisticated technology into our world. The future can be anything we want it to be. If we are not careful, the AI utopia can quickly turn into dystopia. Let’s build one that’s bright and safe.

Do we need AI?

Yes. AI is part of the progress that we humans have constantly been striving for. Though AI might not be our last invention, it significantly impacts our lives in numerous ways. Because of AI, we can now offload a lot of our manual tasks to machines. It would be incorrect to say that AI has made our lives easier. Some of the areas where it has positively affected us include healthcare, agriculture, business processes, and education.

But that’s not all. We’re sure you must have a ton of other questions you want answers to. To find out more about AI and how you can effectively implement it in your business processes and operations, download a free copy of our whitepaper – Uncomplicating AI.

uncomplicated Ai cover image

Artificial Intelligence

Get the whitepaper for free and keep reading!

More whitepapers from the Brainalyzed team

ai-artificial swarm intelligence

Artificial swarm intelligence

enterprise ai

Enterprise AI