{"id":6352,"date":"2019-08-23T11:00:27","date_gmt":"2019-08-23T10:00:27","guid":{"rendered":"\/gb\/en\/blog\/?p=6352"},"modified":"2023-01-16T12:37:33","modified_gmt":"2023-01-16T12:37:33","slug":"artificial-intelligence-vs-machine-learning-vs-deep-learning","status":"publish","type":"post","link":"\/gb\/en\/blog\/artificial-intelligence-vs-machine-learning-vs-deep-learning\/","title":{"rendered":"Artificial Intelligence Vs Machine Learning Vs Deep Learning"},"content":{"rendered":"

Artificial intelligence (AI) has changed the world as we know it forever.\u00a0<\/span><\/p>\n

This technology is no longer the stuff of science fiction. Instead, we see artificial intelligence in virtually every part of our lives. Smart assistants exist in our phones and speakers, helping us to find information and complete everyday tasks. At work, chatbots are supplementing the customer support team<\/a>, with predictions estimating that they’ll be responsible for <\/span>85% of customer service<\/span><\/a> by next year.\u00a0<\/span><\/p>\n

There are even intelligent algorithms that can use vast amounts of data to make accurate predictions behaviour of people and clients. However, while AI is more common than ever<\/a> in today’s world, it’s still something that many people don’t fully understand.\u00a0<\/span><\/p>\n

There are so many different phrases associated with this disruptive technology, that some terms often end up blending. For instance, in specific circle, terms like artificial intelligence, machine learning, and deep learning may even be used interchangeably. However, while these concepts are all connected, they’re not the same thing.\u00a0<\/span><\/p>\n

As intelligence experts have explained, the different components of AI are laid out like Russian nesting dolls. The outer layer is artificial intelligence, the largest, all-encompassing aspect of the technology. Within that is the more refined concept of machine learning, and within that is the smaller subset of deep learning.\u00a0<\/span><\/p>\n

Here’s your guide to understanding each of these things a little better.\u00a0<\/strong><\/p>\n\t

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What is Artificial Intelligence?<\/strong><\/h2>\n

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Let’s start with the basics.\u00a0<\/span><\/p>\n

By next year (2020), 30% of companies worldwide believe that they’ll be using AI in their digital processes in some way. The question is – what does artificial intelligence mean, and why is it so essential to the modern landscape?<\/span><\/p>\n

An artificial intelligence definition<\/strong> isn’t always easy to come by. At a basic level, AI has been a part of our research labs and scientific study for decades – ever since computer scientists initially rolled out the term in 1956 at a Dartmouth Conference.\u00a0<\/span><\/p>\n

Since then, AI has been heralded as the future of human civilisation. However, at its core, it’s just another computer program. Artificial intelligence is any computer algorithm that can perform intelligently. In other words, it uses a complex statistical model or if-this-then-that statements to perform tasks. Artificial intelligence is “smart” because it can follow a very complicated series of instructions, rather than just responding to a single or basic trigger.\u00a0<\/span><\/p>\n

In recent years, <\/span>AI has exploded in popularity<\/span><\/a>, thanks to the rise of available GPUs that make parallel processing easier, cheaper, and more accessible. However, not all AI is the same. There are 3 fundamental sides to artificial intelligence that form the basis of most discussion. The first option is narrow AI, where an intelligent bot can do one essential thing – like beating a human being at a board game. This is something the Google DeepMind product <\/span>Alpha Go did in 2016<\/span><\/a>.\u00a0<\/span><\/p>\n

The second option is artificial general intelligence, or AGI, which can successfully perform a range of intellectual tasks, like responding to questions in a customer service station. There’s also super-intelligent AI – a concept that scientists are still working towards. Superintelligent AI is more intelligent than a human being.\u00a0<\/span><\/p>\n

What is Machine Learning?<\/strong><\/h2>\n

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If artificial intelligence is the umbrella term for all computer programs capable of following complicated instructions, then machine learning is the thing that comes underneath that umbrella. So, what does machine learning mean? Is machine learning ai? Simply put, it’s a subset of AI. With machine learning tools, it’s possible to establish computer algorithms that can search through data and apply heaps of knowledge and training to a specific task.\u00a0<\/span><\/p>\n

For instance, a machine learning service could use millions of pictures of faces to detect specific people or certain features on a face. Machine learning is now being used in areas like machine translation<\/a>, object recognition, and speech recognition. It’s also possible to teach machine learning tools how to understand emotion and sentiment.\u00a0<\/span><\/p>\n

Machine learning allows a system to recognise the patterns in data that a human being might not be able to pick up on their own. Because these algorithms can process such vast amounts of information almost instantly, they can make informed decisions about data sets a lot faster than a human.\u00a0<\/span><\/p>\n\t

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For machine learning algorithms to thrive, they need huge amounts of data. The more information a program has to browse through, the easier it is for that solution to make decisions and answer essential questions. Machine learning tools also take a significant amount of time to train so that they can be as accurate as possible. The original machine learning definition came from the early minds of the AI crowd. Over the years, the algorithmic approaches used for this technology have included everything from inductive logic programming, to reinforcement networks and even Bayesian networks.\u00a0<\/span><\/p>\n

What is Deep Learning?<\/strong><\/h2>\n

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Now we come to the complicated stuff – deep learning.\u00a0<\/span><\/p>\n

When you compare deep learnings vs. machine learning, you’ll discover that deep learning is a refined subset of the machine learning practice. Deep artificial neural networks use complex algorithms in deep learning to allow for higher levels of accuracy when solving significant problems, such as sound recognition, image recognition, recommenders, and so on.\u00a0<\/span><\/p>\n

Deep learning algorithms use some of the basic techniques in machine learning to solve complicated real-world problems by tapping into the neural networks that are similar to those that we use for decision making as human beings. Although deep learning is far more complex and accurate than artificial intelligence or machine learning, it’s also more expensive. Scientists need massive data sets to train neural networks because there are a vast number of parameters for any learning algorithm to understand before it can make accurate choices.\u00a0<\/span><\/p>\n

Artificial general intelligence is far more complex. It's the kind of artificial intelligence that we see on television - capable of performing several different tasks with the help of machine learning and deep learning. <\/a><\/span>Click To Tweet<\/a><\/span><\/blockquote>\n

The neural networks responsible for deep learning strategies come from our own understanding of human biology and how the brain works. It’s about creating connections between hundreds, thousands, or even millions of different data sets so that machines can make more contextual and relevant decisions.\u00a0<\/span><\/p>\n

How Artificial Intelligence Works<\/strong><\/h2>\n

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So, now that you know the basics about each of these concepts let’s dive a little deeper and ask, “How does artificial intelligence work?” Less than a decade after he broke the enigma of the Nazi encryption machine, mathematician Alan Turing transformed the world by asking whether machines could think. A paper was published in 1950 called “<\/span>Computing Machinery and Intelligence<\/span><\/a>,” and the Turing test was established as a result.\u00a0<\/span><\/p>\n

Since Turing made his initial query, most of the break-through in artificial intelligence have been designed to discover whether machines could be taught to think, just like a human being. The artificial intelligence that we have today falls under the categories of narrow AI and artificial general intelligence.\u00a0<\/span><\/p>\n