If you’re like most people, when you hear the term “AI” you might think of Hollywood blockbusters like Blade Runner or The Terminator, where robots have become so intelligent that they can outstrip humans in just about every way. But did you know that we already use AI in our everyday lives, from digital assistants like Siri and Alexa to Amazon’s product recommendations?
Narrow AI, mostly referring to today’s machine learning, is the kind of AI that you’re most likely familiar with. It’s AI that’s been specifically designed to carry out a particular task, like translating text from one language to another or identifying objects in a photograph.
In this article, we'll explore what narrow AI is, how it's used, and the benefits it can bring to businesses; as well as how it's different from general AI and strong AI.
There are three types of AI: narrow AI, general AI, and super AI. Each has different capabilities and implications for society and the economy.
Narrow AI is the prevalent form of AI that’s all around us. Sometimes referred to as weak AI, it is focused on a specific task, such as recognizing objects in pictures or translating text. Narrow AI is becoming increasingly sophisticated and can now be found in many consumer products, such as digital assistants and autonomous vehicles.
General AI, alternatively referred to as AGI, or Artificial General Intelligence, is still in its research stages but has the potential to surpass human beings in intelligence. It would not only complete specific tasks but also learn on its own and adapt to new situations. General AI could eventually be used to create smarter algorithms, design new products, and solve complex problems.
Super AI is the most advanced form of AI. Also known as artificial super intelligence, it would be even more intelligent than general AI and would become self-aware. Super AI could be used to make major advancements in fields such as healthcare, transportation, and manufacturing. However, it also poses a risk to humanity if it falls into the wrong hands. For now, it’s more of a sci-fi concept than a real-world project that AI researchers are making headway on.
Each type of AI presents different opportunities and challenges for businesses and the economy. Narrow AI is already having a significant impact and will continue to do so in the future. General AI is still in its research stages but has enormous potential. Super AI is still far off but would have an unimaginable impact when it arrives. It is important for businesses to start preparing for all three types of AI now so they can take advantage of the opportunities they present.
When John Searle coined the term "strong AI" in 1980, he was referring to a future in which machines would be able to think and understand the world in the same way humans do. The more practical term "narrow AI" was introduced in 1956 by John McCarthy, who defined it as machines that can "use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves."
Narrow AI has come a long way since McCarthy's definition and is currently being used in a number of industries to carry out a variety of tasks. In short, there are countless examples of weak AI, from fraud detection to attrition prediction. In the field of churn prediction, for example, narrow AI can be used to build models that can identify which customers are most likely to churn and why.
Beyond churn, however, that model is limited to the data it was trained on and cannot generalize to other customer data sets. In other words, if you want to use the churn model to predict whether a customer is likely to churn in the future, it will work as long as the customer data set you're using is similar to the one the model was trained on. If you try to use the model on a data set that's different from the one it was originally trained on, the results will likely be inaccurate.
This limitation is one of the key drawbacks of using narrow AI. The other drawback is that narrow AI algorithms can be opaque, meaning that it's difficult to understand how they work. This can make it difficult to trust their results and can also impede our ability to tweak them if necessary.
Despite these drawbacks, narrow AI is still a powerful tool that can be used in a number of industries. When used correctly, its results can be accurate and trustworthy. Perhaps counterintuitively, narrow AI is actually quite flexible, as there are many models that can learn from virtually any data source.
For instance, artificial neural networks can be used for tasks like speech recognition and natural language processing. These algorithms fuel tools like Apple’s Siri, the Google Assistant, and IBM Watson. When learning from big data, these models become examples of “deep learning,” which is, in principle, similar to the neural networks of the human mind. These AI systems are fueling everything from today’s social media giants to search engines.
Practically speaking, businesses can't go out and buy a general AI platform. But they can build narrower AI capabilities to address specific needs. Narrow AI is designed to do one thing really well, whereas general AI is designed to do many things.
Narrow AI is growing in power and sophistication, and its applications are becoming more widespread. It is being used to power everything from digital assistants to self-driving cars. Let’s look at the advantages of narrow AI and explore some of the ways businesses can use it to improve their operations.
There are many advantages to using narrow AI. Some of the most common include:
Narrow AI can be used to automate tasks that are time-consuming and repetitive. This can free up employees to focus on more important tasks.
From lead capture to intelligent appointment scheduling, many routine tasks can be automated with narrow AI. By automating these tasks, businesses can improve their efficiency and free up employees to focus on more important tasks.
Narrow AI can be used to provide customers with faster, more accurate support. For example, digital assistants can help customers with tasks such as booking appointments or finding information.
And when it comes to sentiment analysis, chatbots can help customer service reps to identify and address customer dissatisfaction quickly.
Narrow AI can be used to help businesses make better decisions by analyzing data more efficiently than humans can. This can lead to improved performance and greater profits.
Everything from which products to stock on store shelves to where to allocate resources can be improved with the help of narrow AI. The technology can help businesses become more agile and responsive to market changes, as well as identify opportunities and threats that would otherwise be missed.
Narrow AI can be used to improve the quality of products and services offered by businesses. For example, machine learning can be used to create custom recommendations for customers or to improve the accuracy of predictions made by business systems.
To give another example, a business that sells products online could use machine learning to improve the accuracy of its predictions about what products a customer is likely to buy. This would allow the business to recommend products that are more likely to be purchased by the customer.
Narrow AI can be used to monitor the performance of business operations and identify potential problems before they become serious. This can help businesses to run more smoothly and efficiently.
Whether it’s keeping track of employee productivity or ensuring that the company’s online presence is up to par, there are a number of things that businesses need to keep an eye on. With the help of narrow AI, many of these tasks can be automated, allowing business owners and managers to focus on more important issues.
In just a few short years, narrow artificial intelligence has revolutionized industries as diverse as healthcare, finance, manufacturing, and retail. By utilizing the latest machine learning techniques, many businesses are now able to build systems that can learn and make decisions on their own.
The benefits of narrow AI are clear. With these systems in place, businesses can automate tasks that would otherwise require human intervention, saving time and money. In addition, narrow AI can make decisions based on large amounts of data that would be impossible for humans to process. This allows businesses to gain insights into their operations that they would not otherwise have access to.
Netflix is a good example of how narrow AI can be used to improve customer experiences. The company’s recommendation engine utilizes machine learning algorithms to analyze the viewing habits of its customers and make suggestions for new content. This has allowed Netflix to become the most popular streaming service in the world, with over 200 million paying subscribers.
Siri and Alexa are another great example of how narrow AI can be used to improve customer experiences. These virtual assistants use machine learning algorithms to understand natural language commands and respond in a way that is natural for humans. This allows users to perform tasks like checking the weather or turning on the lights without having to fumble through complicated menus or type in commands.
YouTube is another company that has been able to benefit from narrow AI. The video streaming service uses machine learning algorithms to recommend videos to its users. This has led to over a billion hours of watch time each day on the platform.
The North Face is a retailer that has been using narrow AI to improve the customer experience for years. The company’s Expert Personal Shopper product uses machine learning algorithms to recommend items to customers based on their preferences and budget. This has allowed The North Face to become the largest seller of outdoor apparel in the United States.
Wells Fargo is another company that is using narrow AI to improve customer experiences. The bank has developed a messenger bot that allows customers to ask questions and conduct transactions without having to speak to a human representative.
Meanwhile, PayPal is using narrow AI to prevent fraud. The company’s machine learning algorithms are able to identify patterns of fraudulent behavior and block transactions that are likely to be fraudulent.
The benefits of narrow AI are clear. businesses that are able to incorporate these systems into their operations will be able to improve their bottom line and provide a better experience for their customers.
Legacy AutoML tools are hardly any easier to use than traditional programming languages. Even for experienced data scientists, incorporating artificial intelligence into business processes can be difficult and time consuming.
Akkio changes all that. With Akkio’s no-code AI, businesses of all sizes can quickly and easily apply artificial intelligence to predictive modeling, churn prediction, and a host of other tasks. Akkio automates the entire process, from data preparation to model selection to deployment.
Akkio’s intuitive interface and drag-and-drop tools make it easy for even novice users to get up and running quickly. For instance, suppose you wanted to predict customer churn for your business. With Akkio, you can easily build a predictive model using only a few mouse clicks.
First, you’ll need to select a data set to work with. Akkio includes a library of pre-built data sets, or you can upload your own data. Next, you’ll need to select a target variable. In this case, the target variable is customer churn. Akkio will automatically build a model to predict that target variable in the background.
With just a few mouse clicks, you’ve now built a predictive model that can help predict customer churn. But that’s just the beginning. Akkio also provides a host of features that make it easy to deploy your models into production.
For instance, Akkio offers a drag-and-drop interface for building sophisticated machine learning pipelines. Best of all, Akkio makes it easy to monitor the performance of your models in production. You can track key performance metrics such as accuracy, precision, recall, and F1 score. You can also see when your models start to perform poorly so that you can take corrective action quickly.
In short, Akkio makes it easy for businesses of all sizes to quickly and easily apply artificial intelligence to predictive modeling tasks such as churn prediction.
By now, you can likely identify at least one place where you could use AI to improve your business. While strong AI is the Holy Grail of AI, it remains elusive. General AI is capable of human-level intelligence and is still some way off. In the meantime, we have narrow AI, which is designed to complete a specific task such as identifying objects in pictures or translating text.
These types of artificial intelligence could one day be used to improve your business in a number of ways, but for now, so-called weak artificial intelligence is more than capable of helping you to automate processes and make your business more efficient.
Narrow AI is already being used by businesses to improve efficiency and productivity. In some cases, it is even outpacing human performance. Akkio’s no-code AI can automate the process of building predictive models, outperforming legacy AutoML tools by multiple orders of magnitude.
Businesses that are not making use of machine intelligence are at a disadvantage. To stay competitive, it is important to understand the different types of AI. Start small and test different applications to see what works best for you - get started with a free trial of Akkio.