Applications of Artificial Intelligence

Artificial Intelligence

 

SEO keeps changing, and it seems to exponentially as the years go on. So, we can expect it to keep changing as we advanced towards 2020. We must keep readjusting our marketing and SEO strategies to stay in the game. It has become a real headache for digital marketers. But doing so can have a big payoff, especially if your competitors are lazy about staying up to date on the ever-changing landscape of the internet.

Mr. Natural

We are always told that natural things are best and we should avoid artificial ones. Now one of the newest things in Digital Marketing and SEO is ARTIFICIAL INTELLIGENCE, AI for short. The best definition of artificial intelligence might be from the English Oxford Living Dictionary:

“The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”

Artificial Intelligence Examples

You already see AI being used in many ways. From self-driving cars to SIRI, the friendly voice-activated computer many people interact with on a daily basis. Google employs it in search algorithms and the military uses it to make autonomous weapons. Remember Terminator? Not an impossible thing to see in the future. Kind of scary actually. Technology can always be used for good or bad – if Dr. Evil gets a hold of it.

Advantages of Artificial Intelligence

AI is used in digital marketing like PPC to collect data to target ads, to see if the content is relevant, to distinguish customer segments for cross-selling, for streamlining ads campaigns and much more.
Artificial intelligence is used in tools like Google Analytic, SEMrush, and other free/paid tools. It is used to find on-page problems and resolve them. AI helps to analyze competitor’s websites so you can identify opportunities for growth, improve your keyword list, and do tracking and analysis for your traffic report.

Can you be replaced?

Currently, AI is designed to do narrow tasks such as internet searches, talking to customers online with chatbots, facial recognition or just to drive a car. It’s able to do better than humans at many specific tasks it is designed to do, like solving equations or playing chess. However, the long-term goal of many researchers is to get AI to the point where it can outperform humans at nearly every cognitive task. Called general A (AGI), you better keep improving yourself or you may soon be replaced by a robot!

What makes AI so intelligent?

Many internet gurus are saying the future of Google and SEO is AI and it is progressing rapidly. But what exactly is artificial intelligence?

One of the fastest-growing fields in technology there is so much to know it can be overwhelming. As a person involved in marketing and looking for ways to increase user engagement, you don’t need to know all there is to know. However, it helps to learn something about AI so you can have a basic understanding of what it is and how it affects SEO and how you can use it to your advantage.

AI’s cutting-edge technologies enable computer systems to understand the meaning of human language, learn from experience, and then make predictions. These technologies have revolutionized the way humans interact online and make decisions. Familiarity with how AI works can help you understand the real-world applications.

Basic components of Artificial Intelligence

Machine Learning

Machine learning, by definition, is any technology that uses algorithms to create repeatable results. Algorithms allow the machine to learn from its operations. The process is iterative, as the machine runs, algorithms take in data and parse it, evaluate it and compare different and new data pieces to come up with results and provide insights.

Machine Learning Training Sets

How does this happen? Where do the data results come from?

Data come from a training set, critically important in a machine learning program. The training data set offers the machine learning program something to start with, an initial baseline data to compare to new data sets.

For Example. A programmer wants a computer to learn to differentiate between three different kinds of fruit: bananas, grapes, and oranges. The training data set will orient the machine learning program to understand markers for each fruit type – the names of the fruits and the colors yellow, purple and orange, and the shapes: long and thin, round or clustered.

After training runs using a training set and validation set, the machine will take in new pieces of information and look for those markers or properties in the machine learning world.

The computer will learn to recognize these fruits from any data background. A new data set might have many fruits and vegetables in which the machine learning program will learn to pick out those individual fruits and identify them. The whole key is that it has done this by internalizing the original training set and applying that to new sets of data.

Deep Learning

Artificial Intelligence is any kind of program that tries to make computers “smarter” or help it operate in ways similar to human thought. Machine learning is a type of AI, but it’s a very specific one. Neural networks are another type of machine learning that enable “deep learning.”

A neural network is a software setup that seeks to imitate the behavior of the human brain through the use of layers of artificial neurons, which are digital constructs with weighted inputs, activation functions and outputs. These complicated and sophisticated setups are made up of algorithms that work like machine learning algorithms but have a biological model applied to them.

With neural networks, scientists have created specific methodologies and models that work in different ways. Neural networks called convolutional, share their parameters across space and use many layers of filtering and pooling and other techniques to help computers to recognize images. For instance, pictures of cats or dogs or a pizza or human faces, or for biometric facial recognition.

Cognitive Computing | Inferences from Context

Cognitive computing is a fundamental component of AI. Its purpose is to simulate and enhance communications between humans and machines. Cognitive computing imitates the human thought process with a computer model by understanding human language and the context of images. Combined, cognitive computing and AI give machines human-like behaviors and information processing capabilities.

Natural Language Processing (NLP)

Recurrent neural networks help to imitate human memory and allow machines to process natural language. With NLP, computers can recognize, interpret, and produce human language and speech. NLP enables seamless interaction with systems by teaching them to understand human language in context and provide logical and useful responses. With natural language processing search results can find niche results for queries both for a narrow and broad range.

Computer Vision | Understanding image

Computer vision is a machine learning model with features chosen specifically for object detection. It uses deep learning and pattern recognition to understand the content of an image; including tables graphs, and pictures within PDF documents, and other text and video. Computer vision is an essential field of AI helping computers, identify, process and interpret visual data.

When Modern Machine Learning was Born

Machine learning is not technically a new science. It’s one that’s gotten a boost from new models like neural networks. Some of the earliest machine learning programs could have been written in Basic programming language, but computers didn’t have the power to make it seem like they were learning in a human way. Technology had not advanced to the point where it was possible to set up an algorithm that could sort data in intricate ways and make conclusions on its own. There was just an input/output model being used.

Then came Big Data. Storage media was able to handle more and more data. Gigabytes and terabytes became containable in small and inexpensive devices. When machine learning algorithms were applied to these enormous data sets to pick out actionable results, modern machine learning was born.

The difference between traditional programming and modern machine learning is that traditional programming was deterministic, it had an “if-then” relationship. Computers were simply doing what they were told. Now computers can make their own conclusions.

HISTORY OF AI

AI and SEO

Now that hopefully, you have a better understanding of what AI is, we can move on to how this advanced technology is affecting SEO and is used in digital marketing.

Google AI

No discussion of AI and SEO can be had without talking about Google.

Artificial intelligence is the key to everything Google does nowadays. Google uses AI to return relevant results in the SERPs by identifying patterns between seemingly unconnected searches. This information is indexed to use in future searches to better align with a searcher’s intent, creating a personalized, predictive, and conversational search experience much different than before.

Google even has a division of dedicated solely to artificial intelligence started in 2017 called guess – Google AI.

“Google’s mission is to organize the world’s information and make it universally accessible and useful. AI is helping us do that in exciting new ways, solving problems for our users, our customers, and the world.”

A Brain That Ranks

A core component of Google’s search algorithm Hummingbird is RankBrain, a machine-learning algorithm in use since 2015 that interprets unknown search strings. It plays a role in helping Google with searches that do not have a clear answer. When Hummingbird was first introduced in 2013 it improved search engine results, but it still was not able to understand all queries. RankBrain helps Google interpret queries it does not understand.

Google says links and content are still the two most important ranking factors, RankBrain is the third most important feature of its algorithm.

It used to be, way back in the day, when you entered a search term, google checked its index for matching terms and that was it. Now with AI, Google gathers and remembers things like your search history, area, favorite websites, and what other people clicked on for the same query. The machine-learning algorithms like RankBrain learn from people’s behavior as they click on search results and from there can decide which ranking factors to use for every search.

AI and Keywords

AI, by its design, is constantly evolving as it learns to classify, categorize and present the data that is most likely to meet the requirements of searches at that particular time. Improvements in search results mean how you use keywords and keywords phrases has evolved also.

With Hummingbird’s extra capability to clarify queries, your keywords don’t need to be and shouldn’t be limited to a few keywords. Longtail and LSI keywords can deliver better results. Don’t just repeat the same keyword or phrase over and over, but instead include variations of it throughout your content. Artificial intelligence has significantly improved SEO past using simple keyword phrases.

Applications of Artificial Intelligence

AI is used in two technologies, chatbots and voice search.

Chatbots

Chatbots

Chatbots are computer programs designed to engage automatically with messages received by chat mediums like SMS text. Chatbots examples include website chat windows and social messaging services like Facebook chatbots, platforms like Slack, Skype, WhatsApp, and Alexa.

You may not know this but chatbots are not something new. They have been in development since the 1950s. Only in recent years have businesses started using them for communicating with customers and potential customers.

There are different types of Chatbots.

Simple Chatbots respond the same way each time by scanning for keywords in an inquiry and deliver pre-packaged answers.

Chatbots powered by AI and machine learning use natural language processing to create complex responses and conversations. One of the advantages of artificial intelligence is when a human is speaking and they don’t give the exact message they’re programmed to receive, AI actively learns from the conversations to help customers reach their goals.

Stateless chatbot approaches each conversation as if it was interacting with a new user.

Stateful chatbot reviews past interactions and frames new responses in context, as a human would do.

Chatbots can be used for many different kinds of services.

One of the most common ways to use a chatbot in marketing is to create one that interacts with your visitors upon entering your website.

There is hardly a website nowadays that doesn’t use online chat that pops up on a webpage. It may be there is an actual human chatting with you and answering questions, however, it could well be computer generated responses.

The technology has gotten that far that it may be hard to tell from simple to more complex quires. Chatbots that use artificial intelligence to receive and respond to messages are rising in popularity.

Some reasons it frees up having employees to do the chat, other advantages can be:

  • 24-hour service
  • Instant response
  • Answer simple questions
  • Easy communication
  • Complaints resolved quickly

Chatbots have become popular because you can actually learn how to create a chatbot fairly easily with the chatbot development platforms and apps available. Just search “how to create a chatbot“ and you will see many chatbot websites that will help you create one without any knowledge of coding.

Applications of Artificial Intelligence

Voice Search

One of the most incredible components of AI is natural language processing. NLP enables people to use voice to search instead of a query with text. That’s not hard to understand. But what needs to be understood is that when people use voice search, they tend to use words and phrases differently than when using text.

How Voice Search Is Changing SEO

Voice Search SEO requires using keywords and phrases that are more in line with the way people talk to a particular voice-enabled search. Whether they are using Google voice search online, YouTube voice search or one of the many voice assistants such as Alexa, Cortana, and Siri. Using their own words and phrases is the key to optimizing for voice search inquires.

With voice assistants, people tend to have more of a conversation, like talking to a real person. Conversational AI has changed the way people use search. Voice searches range from four to six words while text-based searches typically range between one to three words. Queries can be almost full sentences like “where is a restaurant near me” instead of “restaurant near me.”

When a query is entered into a search engine, hundreds of results are displayed. When people use voice search with a digital assistant, many of the spoken responses come from the “featured snippet” from the search results. Voice assistants such as Siri, Google, Cortana, and Alexa respond with just one result, not many other results on the search page. You will get traffic if you are that featured snippet in organic search. The way you do that is to use your own intelligence, the best practices of SEO, and have an effective strategy.

Artificial Intelligence Future

Personalized advertising and communications created by artificial intelligence using machine learning and neural networks are selling us things and more so in the future. Computers keep getting smarter and more intelligent as more research and development continues.

More than just advertising and selling stuff, the scientist working on AI are making it a priority to use the field to solve problems that will give artificial intelligence benefits to society.

Google, Amazon, Apple, DeepMind, IBM and Microsoft have founded the Partnership on AI to Benefit People and Society to use AI for socially beneficial purposes.

“Natural” Intelligence

While Artificial Intelligence has done a lot to change digital marketing and SEO, PrimeView also relies on “natural” intelligence, gained from years of designing and developing websites to deliver results. We then take advantage of AI for conversion analysis to get you ahead or the competition.