Artificial Intelligence (AI)

What is AI?

AI, which stands for artificial intelligence, is a branch of computer science that develops machine systems capable of demonstrating behaviors linked to human intelligence. AI programs use data collected from different interactions to improve the way they mimic humans in order to perform tasks such as learning, planning, knowledge representation, perception and problem-solving.

Artificial intelligence technology is used for a wide range of applications, including in web development, such as automated chatbots for customer service, product recommendations based on a user’s habits, speech recognition, and even to build a website from scratch. Essentially, the purpose of AI is to improve the systems we already use by automating tasks to make them more efficient.

How does AI work?

AI systems process large amounts of data through algorithms in order to find patterns that will help them understand and replicate human intelligence by predicting future behavior from an end-user. For example, when using an AI-powered chatbot, the system will work to preempt a user’s next question by offering information as a real chat agent would.

In order to do this, an AI system needs to be built based on three main cognitive skills:

Learning: an AI program needs to be able to gather information that is turned into algorithms.
Reasoning: once the algorithms are set, the AI needs to know how to select the right one for different scenarios.
Self-correction: in any AI machine, the algorithms need to be regularly updated based on new data in order to get a more accurate result.

The primary benefit of using AI is that these systems can potentially complete tasks better and more efficiently than humans. This is especially relevant when it comes to mundane or repetitive tasks, which these machines are able to perform at a higher pace and with a much lower chance of error.

The main types of artificial intelligence

In order to fully understand what AI is and how it works, one must take into account the current state of artificial intelligence and the potential scenarios towards which it can evolve as the technology is further developed.

According to the original outline of Arend Hintze, a professor at Michigan State University, there are four main types of AI. This categorization spans from the way we’re used to interacting with AI today, to the more “sci-fi” view of how AI might function in the future as sentient systems.

01. Reactive machines

In reactive machines, the AI’s main goal is to complete a task by reacting to the information presented to it. This type of artificial intelligence system isn’t able to store memory of previous data, therefore it can’t use data in order to fine-tune its responses to a present task. For this reason, reactive AI machines are generally used to perform specific tasks with set outcomes rather than learn from a multitude of different scenarios.

One of the most famous examples of reactive machines is IBM’s Deep Blue, a supercomputer built to play chess and ended up winning in a game against then-grandmaster, Garry Kasparov. While Deep Blue was able to look at a chessboard and identify chess pieces and potential moves, its intelligence was limited to making predictions on moves and taking the most logical next move. The machine wasn’t able to learn about its opponent by gathering data about his habits, game-play flaws, or signature chess moves.

02. Limited memory

Unlike Deep Blue and other reactive machines, a limited memory AI system is able to learn, to a limited extent, from the information it has already seen in order to inform its future actions. The opportunities with limited memory AI systems are a lot greater since they’re able to improve their behavior using the data they’re exposed to.

In order to create this limited memory, human teams need to train the AI system with a model so that it can learn to analyze new data. The machine needs to be consistently exposed to new data so that when it’s faced by a user, it has the existing memory necessary to predict what comes next. An example of limited memory technology is self-driving cars, which are exposed to enough data and models of different driving scenarios so that it can make its own decisions when on the road.

03. Theory of mind

Theory of mind AI systems have a much deeper psychological core, as they’re able to read and interpret human emotions and learn from social intelligence in addition to raw data. We have yet to achieve this level of artificial intelligence in our society, however, AI programs falling under the theory of mind category would be able to understand how humans make decisions based on emotions so that it could more accurately predict behavior. This would allow for more of a symbiotic relationship between man and AI-powered machines.

04. Self-awareness

The self-aware type of artificial intelligence also does not exist, but might conjure up images from films of robots taking over humanity as we know it. While that scenario is highly unlikely, the notion of AI developing into something with consciousness is the final type of artificial intelligence technology.

In addition to being able to understand the psychology and emotions of others as we saw in the theory of mind programs, this type of machine would also be aware of its own existence and place in the world. However, for now, this kind of AI remains the stuff of science fiction as it will take tons of advanced research into fully understanding and reproducing a human-like consciousness.

Weak vs strong AI

Another way that we use to divide the different types of artificial intelligence is by categorizing them as weak and strong, also known as narrow and general.

Weak (or “narrow”) AI

Weak AI refers to the kinds of artificial intelligence that we’re used to in our day-to-day lives. In other words, weak AI is the type of machine that’s meant to complete a set task very well. While these types of systems might seem highly intelligent, they’re functioning within boundaries that limit the level of intelligence they can achieve.

Examples of weak or narrow AI include any type of software that automates or analyzes data, virtual assistants like Siri or Alexa, and even weather apps. This type of artificial intelligence programs are more focused on making our lives more efficient, instead of simulating real human intelligence in all its capacity.

Strong (or “general”) AI

Strong AI, also sometimes called Artificial General Intelligence (AGI), refers to artificial intelligence systems that, at the moment, only exist in the movies. Robots from films such as I, Robot or in the series Westworld exemplify the extreme sides of AGI.

In reality, strong artificial intelligence in the future might look like AI systems that are able to completely mimic the scope of human intelligence, including emotion, creativity, and adaptability in order to fulfill tasks. However, unlike in dramatised versions of artificial intelligence machines in movies, general AI is likely to assist and expand our abilities as humans rather than replacing them entirely.

Generative AI

At its core, Generative AI refers to a type of artificial intelligence that can generate new content, from images and music to text and code. In contrast to earlier versions of artificial intelligence, generative AI isn't just analyzing data and collecting insights, but is actually creating something new from what it has learned.

Common examples of artificial intelligence applications

AI can be used in almost any industry in order to make work more efficient and to lessen the burden on workers. Here are some recognizable types of artificial intelligence that are commonly used every day:

Education

AI is used in all levels of education to make a teacher’s life simpler and improve the experience of students in a classroom. AI programs are currently helping teachers grade students’ work, which is normally very time-consuming. It also allows for a more personalized learning experience for students. Programs like Carnegie Learning use AI to offer students feedback on their work as well as personalized testing and learning.

Healthcare

In the field of healthcare, AI is being used in order to help monitor, diagnose, and treat patients. Since AI today is able to adapt based on the data it learns, the more it learns about different patients, the better it develops into an essential tool. Programs such as IBM Watson Health allow medical staff to ask questions in natural language and get a response, which helps doctors optimize their performance.

Finance

Within the finance industry, AI is used across the board, from personal finance tools to Wall Street. Tax return software such as TurboTax uses AI-powered technology to provide financial tips based on personal data that is gathered through the program. Not only that, but Wall Street traders and statisticians are relying on artificial intelligence to process big amounts of data used in investment trading.

Business

AI has reached a lot of different areas of business, from assisting customer service teams with automated chats to analyzing data in customer relationship management (CRM) programs. The AI in CRM programs allows businesses to better understand their clients by looking at their previous buying habits in order to recommend new products and forecast behavior. AI technology is also used in the recruiting process to help HR teams screen large numbers of resumes to find the best candidates.

Online marketing

AI marketing is becoming an important part of digital marketing by helping marketers pick up on trends a lot quicker. It also helps personalize content a lot better and easier, especially when it comes to email marketing content. Email marketers can use AI to send a personalized message to each customer at the right time, improving the chances of sending an email that converts. Not only that, but users can now create a custom website completely from scratch using AI-powered technology. For example, users can build a website in a few minutes just by answering a few questions.

Manufacturing

Factories rely heavily on AI technology to automate and streamline many time-consuming and tedious manufacturing processes. The manufacturing industry places a great emphasis on productivity, and AI machines allow them to produce stock a lot more quickly and safely. Using AI technology on the production line allows manufacturers to create smart operations that reduce both time and cost and also minimize downtime.

Voice recognition

Voice recognition software is now enmeshed in our daily lives. Asking Siri to set a timer when you’re cooking or asking Alexa what the weather is outside are both examples of how we use AI day-to-day. Over time, when we use this voice recognition technology more frequently, the AI learns to get to know us better so that it can offer responses more tailored to our personalities, such as song choices or search results.

Transportation

Transportation is another industry where AI has dominated, often without us even realizing it. Self-driving cars are what first comes to mind, but there are other types of AI used in everyday transportation that make our lives a lot easier, such as mobile apps’ ability to predict and manage traffic or foresee flight delays. When it comes to ride-sharing, AI technology is used to predict surges in demand on apps such as Uber and helps increase the availability of drivers in an area with high demand ahead of time.

Chatbots

Chatbots are used in many customer service teams to help filter the number of users who interact with real customer service agents and provide more immediate answers. These chatbots use an AI that is able to answer basic questions based on certain keywords a customer types in. Some of them are even able to offer near-human-level customer service, while others simply help direct customers to the right department or human service agent.

Law

The field of law is another industry where AI technology is helping professionals work more effectively. Lawyers are often faced with parsing through thousands of documents during the discovery stage of a case to find the most relevant ones. Today, AI technology such as Ross Intelligence is being used in law firms to review and analyze documents using NLP and choose the ones that are relevant. Additionally, other types of AI software are used to forecast all the different outcomes of cases that go to trial so that lawyers can see the likelihood of winning or whether they should settle.

eCommerce

Frequent online shoppers might notice that the online stores they visit often tend to know exactly what they’re shopping for. Online stores such as Amazon use AI to learn which type of products each individual shopper tends to purchase or even just look at, and then make product recommendations based on their search. The information gathered by AI while consumers shop online is then used in other e-commerce tools, such as ad retargeting.

Security

AI is used to minimize threats in both security for in-person events as well as in cybersecurity. Technologies like facial recognition or biometric registration work together with AI to scan attendees at an event in order to reduce the chances of error in security checks. In cybersecurity, AI is trained to detect new threats, such as malware or bots, and fight to remove them from a system in order to protect sensitive data and reduce vulnerabilities.

Banking

The banking sector uses AI in similar ways to the business and finance industry. Chatbots are often used by banks to offer more immediate customer service, while artificial intelligence security programs for customer authentication are used to make accounts more secure and help detect and prevent fraudulent activities. Additionally, banks also need to process huge amounts of data for compliance processes such as Anti-Money Laundering (AML) and Know Your Customer (KYC). To better understand customer behavior, banks use AI algorithms to analyze this data and investigate when there are anomalies.

Streaming services

Media streaming services such as Spotify, Netflix or Hulu operate a lot like online shopping. These streaming services use AI to understand a user’s preferences in order to make recommendations. When a user chooses a song and Spotify plays the next one, or when Netflix shows a preview of a show based on what was previously viewed, that’s AI technology at work.

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