Artificial Intelligence garners more front-page headlines every day. Artificial Intelligence, or AI, is the technology enabling machines to learn from experience and perform human-like tasks.
Ping-ponging between utopian and dystopian, opinions vary wildly regarding the current and future applications, or worse, implications, of artificial intelligence. Without the proper moorings, our minds tend to drift into Hollywood-manufactured waters, teeming with robot revolutions, autonomous cars, and very little understanding of how AI actually works.
This is mostly due to the fact that AI in itself is describing different technologies, which provide machines the ability to learn in an “intelligent” way.
Ever wonder about artificial intelligence and how it works? Let’s talk about AI, what it is and how it applies to your marketing.
What is AI?
AI means Artificial Intelligence and we use it to describe any time a computer does something that would require the intelligence of a human or anything that mimics human intelligence, whichever way you want to think of it.
How does AI work?
Artificial intelligence uses machine learning to mimic human intelligence. The computer has to learn how to respond to certain actions, so it uses algorithms and historical data to create something called a propensity model.
Propensity models will then start making predictions.
AI can do much more than this, but those are common uses and functionality for marketing. And while it might seem like the machines are ready to rise up and take over, humans are still needed to do much of the work.
Mainly, we use AI to save us time adding people to email automation and allowing AI to do much of the work while we work on other tasks.
How is artificial intelligence applied?
Popular misconceptions tend to place AI on an island with robots and self-driving cars. However, this approach fails to recognize artificial intelligence’s major practical application; processing the vast amounts of data generated daily.
By strategically applying AI to certain processes, insight gathering and task automation occur at an otherwise unimaginable rate and scale.
Parsing through the mountains of data created by humans, AI systems perform intelligent searches, interpreting both text and images to discover patterns in complex data, and then act on those learnings.
What are the basic components of artificial intelligence?
Many of AI’s revolutionary technologies are common buzzwords, like natural language processing, Deep Learning, and predictive analytics. Cutting-edge technologies enable computer systems to understand the meaning of human language, learn from experience, and make predictions, respectively.
Understanding AI jargon is the key to facilitating discussion about the real-world applications of this technology. The technologies are disruptive, revolutionizing the way humans interact with data and make decisions, and should be understood in basic terms by all of us.
- Machine Learning
Machine learning, or ML, is an application of AI that provides computer systems with the ability to automatically learn and improve from experience without being explicitly programmed. ML focuses on the development of algorithms that can analyze data and make predictions. Beyond being used to predict what Netflix movies you might like, or the best route for your Uber, machine learning is being applied to healthcare, pharma, and life sciences industries to aid disease diagnosis, medical image interpretation, and accelerate drug development.
- Deep Learning
Deep learning is a subset of machine learning that employs artificial neural networks that learn by processing data. Artificial neural networks mimic the biological neural networks in the human brain. Multiple layers of artificial neural networks work together to determine a single output from many inputs, for example, identifying the image of a face from a mosaic of tiles. The machines learn through positive and negative reinforcement of the tasks they carry out, which requires constant processing and reinforcement to progress. Another form of deep learning is speech recognition, which enables the voice assistant in phones to understand questions like, “Hey Siri, How does artificial intelligence?"
- Neural Network
Neural networks enable deep learning. As mentioned, neural networks are computer systems modeled after neural connections in the human brain. The artificial equivalent of a human neuron is a perceptron. Just like bundles of neurons create neural networks in the brain, stacks of perceptrons create artificial neural networks in computer systems. Neural networks learn by processing training examples. The best examples come in the form of large data sets, like, say, a set of 1,000 cat photos. By processing the many images (inputs) the machine is able to produce a single output, answering the question, “Is the image a cat or not?”
This process analyzes data many times to find associations and give meaning to previously undefined data. Through different learning models, like positive reinforcement, the machine is taught it has successfully identified the object.
- Cognitive Computing
Cognitive computing is another essential component of AI. Its purpose is to imitate and improve the interaction between humans and machines. Cognitive computing seeks to recreate the human thought process in a computer model, in this case, by understanding human language and the meaning of images. Together, cognitive computing and artificial intelligence strive to endow machines with human-like behaviors and information processing abilities.
- Natural Language Processing (NLP)
Natural Language Processing or NLP, allows computers to interpret, recognize, and produce human language and speech. The ultimate goal of NLP is to enable seamless interaction with the machines we use every day by teaching systems to understand human language in context and produce logical responses. Real-world examples of NLP include Skype Translator, which interprets the speech of multiple languages in real-time to facilitate communication.
- Computer Vision
Computer vision is a technique that implements deep learning and pattern identification to interpret the content of an image; including the graphs, tables, and pictures within PDF documents, as well as, other text and video. Computer vision is an integral field of AI, enabling computers to identify, process, and interpret visual data. Applications of this technology have already begun to revolutionize industries like research & development and healthcare. Computer Vision is being used to diagnose patients faster by using Computer Vision and machine learning to evaluate patients’ x-ray scans.
Additional Supporting technologies for Artificial Intelligence
- Graphical Processing Units or GPUs are a key enabler of AI, providing the massive computing power necessary to process millions of data and calculations quickly.
- The Internet of Things, or IoT, is the cumulative network of devices that are connected to the internet. The IoT is predicted to connect over 100 billion devices in the coming years.
- Intelligent data processing is being optimized using advanced algorithms for faster multi-level analysis of data. This is the solution to predict rare events, comprehending systems and unique situations.
With the integration of Application Processing Interfaces or APIs, aspects of artificial intelligence can be plugged into existing software, augmenting its normal function with AI.
AI in marketing is already prevalent, and you probably interact with AI on a daily basis. Here are some ways you interact with artificial intelligence:
- Search engines like Google use AI to determine the most appropriate result for a search.
- Automated marketing emails use AI to figure out what emails to send based on how you’ve interacted with a business or website.
- Various types of online ads use AI to determine who should see a specific ad, based on past behavior, interests, and search queries.
- Chatbots are becoming more common in online messengers so that larger brands can assist customers immediately and efficiently.
- Voice searches on smart speakers or even smartphones use AI to determine the best result for those long-tail keywords and conversational queries.
How do marketers use AI?
AI comes into play for the marketing we do for clients here fairly often.
For instance, local search results are determined in part by AI deciding what’s the best business for a searcher’s needs. So, when someone searches for "pizza," artificial intelligence has to figure out whether the person wants to know more about pizza or if they want to find a pizza place, and if it thinks they want a pizza place, it has to figure out which pizza place is the best answer for the search.
And, the ads we create for clients are shown to local consumers depending partially on who AI determines to be the right audience for an ad.
Still, we have to do much of the heavy lifting ourselves, setting up campaigns, claiming and optimizing listings, etc. In the future, this could change, but for now, marketing is a very hands-on industry and you need someone watching out for new trends and even for changes in AI.
Think about the times Google changes its algorithm and businesses automatically get penalized for something that didn’t get them into trouble in the past. While artificial intelligence is still prevalent in the strategy, you need to have someone to watch over your marketing to make sure that AI isn’t detrimental to your marketing.
It's also important to make sure that there's a human element to your marketing.
As nice as it would be for you to set up your marketing and let it run wild on its own, effortlessly bringing you new customers every day, that’s just not possible yet.
Artificial Intelligence is a diverse topic
As we have learned, AI is describing a set of different technologies. Each of these technologies requires a detailed explanation. Staying up to date and understanding the differences of these technologies is a difficult task. Keep up with the latest changes and stay tuned for our upcoming posts.
There is no expert who can remain an expert without sharing their knowledge. So, keep sharing your knowledge with everyone.
- Neural Network
Neural networks enable deep learning. As mentioned, neural networks are computer systems modeled after neural connections in the human brain. The artificial equivalent of a human neuron is a perceptron. Just like bundles of neurons create neural networks in the brain, stacks of perceptrons create artificial neural networks in computer systems. Neural networks learn by processing training examples. The best examples come in the form of large data sets, like, say, a set of 1,000 cat photos. By processing the many images (inputs) the machine is able to produce a single output, answering the question, “Is the image a cat or not?”
This process analyzes data many times to find associations and give meaning to previously undefined data. Through different learning models, like positive reinforcement, the machine is taught it has successfully identified the object.
- Cognitive Computing
Cognitive computing is another essential component of AI. Its purpose is to imitate and improve the interaction between humans and machines. Cognitive computing seeks to recreate the human thought process in a computer model, in this case, by understanding human language and the meaning of images. Together, cognitive computing and artificial intelligence strive to endow machines with human-like behaviors and information processing abilities.
- Natural Language Processing (NLP)
Natural Language Processing or NLP, allows computers to interpret, recognize, and produce human language and speech. The ultimate goal of NLP is to enable seamless interaction with the machines we use every day by teaching systems to understand human language in context and produce logical responses. Real-world examples of NLP include Skype Translator, which interprets the speech of multiple languages in real-time to facilitate communication.
- Computer Vision
Computer vision is a technique that implements deep learning and pattern identification to interpret the content of an image; including the graphs, tables, and pictures within PDF documents, as well as, other text and video. Computer vision is an integral field of AI, enabling computers to identify, process, and interpret visual data. Applications of this technology have already begun to revolutionize industries like research & development and healthcare. Computer Vision is being used to diagnose patients faster by using Computer Vision and machine learning to evaluate patients’ x-ray scans.
Additional Supporting technologies for Artificial Intelligence
- Graphical Processing Units or GPUs are a key enabler of AI, providing the massive computing power necessary to process millions of data and calculations quickly.
- The Internet of Things, or IoT, is the cumulative network of devices that are connected to the internet. The IoT is predicted to connect over 100 billion devices in the coming years.
- Intelligent data processing is being optimized using advanced algorithms for faster multi-level analysis of data. This is the solution to predict rare events, comprehending systems and unique situations.
With the integration of Application Processing Interfaces or APIs, aspects of artificial intelligence can be plugged into existing software, augmenting its normal function with AI.
AI in marketing is already prevalent, and you probably interact with AI on a daily basis. Here are some ways you interact with artificial intelligence:
- Search engines like Google use AI to determine the most appropriate result for a search.
- Automated marketing emails use AI to figure out what emails to send based on how you’ve interacted with a business or website.
- Various types of online ads use AI to determine who should see a specific ad, based on past behavior, interests, and search queries.
- Chatbots are becoming more common in online messengers so that larger brands can assist customers immediately and efficiently.
- Voice searches on smart speakers or even smartphones use AI to determine the best result for those long-tail keywords and conversational queries.
How do marketers use AI?
AI comes into play for the marketing we do for clients here fairly often.
For instance, local search results are determined in part by AI deciding what’s the best business for a searcher’s needs. So, when someone searches for "pizza," artificial intelligence has to figure out whether the person wants to know more about pizza or if they want to find a pizza place, and if it thinks they want a pizza place, it has to figure out which pizza place is the best answer for the search.
And, the ads we create for clients are shown to local consumers depending partially on who AI determines to be the right audience for an ad.
Still, we have to do much of the heavy lifting ourselves, setting up campaigns, claiming and optimizing listings, etc. In the future, this could change, but for now, marketing is a very hands-on industry and you need someone watching out for new trends and even for changes in AI.
Think about the times Google changes its algorithm and businesses automatically get penalized for something that didn’t get them into trouble in the past. While artificial intelligence is still prevalent in the strategy, you need to have someone to watch over your marketing to make sure that AI isn’t detrimental to your marketing.
It's also important to make sure that there's a human element to your marketing.
As nice as it would be for you to set up your marketing and let it run wild on its own, effortlessly bringing you new customers every day, that’s just not possible yet.
Artificial Intelligence is a diverse topic
As we have learned, AI is describing a set of different technologies. Each of these technologies requires a detailed explanation. Staying up to date and understanding the differences of these technologies is a difficult task. Keep up with the latest changes and stay tuned for our upcoming posts.
There is no expert who can remain an expert without sharing their knowledge. So, keep sharing your knowledge with everyone.
- Cognitive Computing
- Natural Language Processing (NLP)
- Computer Vision
Additional Supporting technologies for Artificial Intelligence
- Graphical Processing Units or GPUs are a key enabler of AI, providing the massive computing power necessary to process millions of data and calculations quickly.
- The Internet of Things, or IoT, is the cumulative network of devices that are connected to the internet. The IoT is predicted to connect over 100 billion devices in the coming years.
- Intelligent data processing is being optimized using advanced algorithms for faster multi-level analysis of data. This is the solution to predict rare events, comprehending systems and unique situations.
AI in marketing is already prevalent, and you probably interact with AI on a daily basis. Here are some ways you interact with artificial intelligence:
- Search engines like Google use AI to determine the most appropriate result for a search.
- Automated marketing emails use AI to figure out what emails to send based on how you’ve interacted with a business or website.
- Various types of online ads use AI to determine who should see a specific ad, based on past behavior, interests, and search queries.
- Chatbots are becoming more common in online messengers so that larger brands can assist customers immediately and efficiently.
- Voice searches on smart speakers or even smartphones use AI to determine the best result for those long-tail keywords and conversational queries.