Artificial Intelligence (AI) has emerged as a great tool to develop everything from simple applications like recommending movies to complex systems driving autonomous vehicles. AI differs from basic deep learning models in terms of handling complex tasks, showing greater empathy and making decisions without human-in-the-loop. This shifts our understanding of what machine intelligence is.

In this blog, we will delve deeper into the different types of artificial intelligence and their capabilities in detail. 

Understanding AI

At its core, Artificial Intelligence (AI) is the creation of intelligent algorithms that mimic or even surpass human intelligence. The term can also apply to any machine exhibiting traits associated with a human mind, such as learning and problem-solving. 

Artificial intelligence can be categorized into two broad categories based on: AI capabilities and AI functionalities.

Types of AI Based on Capabilities

Narrow or Weak AI

Narrow AI, also known as Weak AI, refers to artificial intelligence systems that operate under a pre-defined range or set of rules, with no ability to perform beyond their programmed capabilities.

Not surprisingly, Narrow AI is the most common form of AI we use in our everyday life. This is due to it’s narrow focus and ability to complete tasks without any interruptions. Narrow AI can complete tasks like image analysis, text translation or voice recognition, which would need human intelligence. But, unlike humans, Narrow AI can’t use their knowledge beyond the tasks they’re programmed to perform. 

Benefits of using Narrow AI

Narrow AI is extremely efficient and reliable in performing computational tasks and repetitive tasks. They outperform humans in speed and accuracy and therefore, are great at replacing humans in manual tasks. 

Examples of Narrow AI

Here are some examples of Narrow AI: 

Recommendation systems used in Netflix or Amazon to recommend you movies or products is a great example of Narrow AI. These AI systems analyze your past behavior to recommend something you’ll like. 

Voice activated assistants like Siri and Alexa are also Narrow AI. They use natural language processing to understand what you’re saying and take actions. They can perform only predefined actions, which is very aptly put by “Sorry, I’m having trouble understanding what you’re saying” notes. 

General AI

General AI, or Artificial General Intelligence (AGI) is a term you would’ve recalled from Sam Altman’s speech and launch of GPT stores. General AI is a type of AI (currently hypothetical) which possesses the ability to understand, learn, and apply its intelligence across a wide range of tasks. What makes it unique, is that General AI surpasses humans in all ways to perform all the tasks. 

AGI is a theoretical concept. Major companies like Amazon, OpenAI, Microsoft and Google are working to develop a General AI. With current AI technologies, we haven’t reached it yet, but the development of AGI would mark a significant milestone, as it would mean creating machines capable of reasoning, problem-solving, and creative thinking across diverse domains without specific programming for each task.

Superintelligent AI

Superintelligent AI takes it one step further. Instead of being better than humans in general tasks, superintelligent AI is a type of artificial intelligence that surpasses the brightest human minds in practically every field. This includes scientific creativity, general wisdom, and social skills. This type of AI will be better than the entire humanity in every sense and capability. 

While the development of super intelligent AI is interesting, it also invokes critical ethical and existential risks. The primary concern revolves around ensuring that the AI’s  goals are aligned with human values and interests.

Types of AI Based on Functionality

Reactive Machines

As the name suggests, reactive machines are a type of artificial intelligence that are reactive to data. They operate on the provided data in real-time without using any previous data.These systems focus on immediate responses to specific inputs and are designed to accomplish narrowly defined tasks.

Reactive Machines represent one of the most basic forms of AI. Reactive machines can’t learn, make decisions or perform actions. They just respond to a set of predefined scenarios. They’re ideal for applications requiring precise and repetitive operations as they’re extremely reliable and efficient.

Examples of Reactive Machines

Let’s take a look at some example of reactive machines to gain a deeper understanding. 

IBM’s Deep Blue: Deep Blue, the chess-playing computer that famously beat world champion Garry Kasparov in 1997, is an example of a Reactive Machine. It analyzed the current state of the chessboard to make its moves, relying on predetermined strategies and brute-force calculations without learning from past games or adapting its strategy over time.

Simple Customer Service Chatbots: Basic chatbots that respond to customer inquiries with pre-set answers are Reactive Machines. They process input (customer queries) and provide responses based on a limited set of predefined rules, without the ability to remember past interactions or learn from them to improve future responses.

Limited Memory AI

Limited Memory AI are types of artificial intelligence systems that can use past experiences or historical data to inform current decisions. Differing from reactive machines, these AI systems have a short-term memory which can be used as inputs and allow them to learn from past data to make a decision. 

Limited Memory AI is a more advanced form of AI.Limited memory AI systems are widely used for pattern recognition, decision-making under uncertainty, and predictive analytics. The “limited” word is due to it’s inability to look at all historical data but rather focus on a very short period of data. Limited Memory AI rely on pre-programmed models and are limited by the scope of their memory and learning capabilities.

Examples of Limited Memory AI

Let’s take a look at examples of limited memory AI. 

Autonomous Vehicles: Limited Memory AI is used in self driving cars to make immediate decisions on the road. They analyze data like the speed and trajectory of nearby vehicles, road markings and more to make a decision to navigate safely. 

Autocorrect Features: Autocorrect has ruined a lot of texts, mine too. It uses limited memory AI to predict the next word you might type or correct spelling errors. They learn from your recent typing habits and the context of the conversation to make real-time suggestions, improving accuracy and efficiency in communication.

Theory of Mind AI

Theory of Mind AI is a futuristic (hypothetical) type of artificial intelligence that can understand and interpret the emotions, beliefs, thoughts, and intentions of humans. This type of AI would be capable of genuinely understanding human psychology, facilitating more natural and intuitive interactions between humans and machines.

Theory of Mind AI moves from just decision-making to actually understanding human emotions and intentions.Theory of mind AI also exhibits empathy and understanding. The development of such AI would mark a monumental leap in technology. It would enable AI to be emphatic and handle situations like patient interactions. 

Self-aware AI

Self-aware AI is one step further. It is a type of AI which possesses consciousness and self-awareness. 

Self-aware AI is a sci-fi concept where an AI can not only understand and interact with the external world but also possess an internal consciousness, making it capable of independent desires, preferences, and decision-making.

Practical applications of AI in business

We discussed a lot about different types of artificial intelligence, and while a lot of them were hypothetical, AI is playing a vital role in improving business efficiency. Here, we will explore practical applications of AI technologies across various business scenarios, highlighting how companies can leverage AI.

Customer Service Automation

AI-powered chatbots and virtual assistants are revolutionizing customer service by providing 24/7 support and personalized assistance. NLP enables these bots to understand and respond to customer queries in natural language, while ML helps them learn from interactions to improve their responses over time. 

On top of this, you can also use limited memory AI, to improve the knowledge base of the AI and help the AI converse with your customers and solve their issues. At Alltius, we help customer success teams deflect tickets with a pre-trained AI that solves customer queries using the company's knowledge base. 

This not only enhances customer satisfaction but also reduces operational costs by automating routine inquiries, allowing human agents to focus on more complex issues.

Predictive Analytics in Sales and Marketing

AI-driven tools (limited memory AI) can analyze historical data and market trends to forecast future customer behaviors, purchase patterns, and product demand. 

Businesses use these insights to optimize inventory management, tailor marketing campaigns, and identify cross-selling or upselling opportunities. By predicting customer needs and behaviors, companies can proactively engage with their audience, improving sales performance and customer loyalty.

Personalized Recommendations

We see it in action almost everyday. Our social media platforms, e-commerce platforms and entertainment platforms use AI to offer personalized recommendations we would like. By analyzing past behavior, preferences, and interactions, deep learning algorithms identify patterns and preferences unique to each user, suggesting products, services, or content that they are likely to appreciate. This not only enhances the user experience but also increases conversion rates and customer retention.

Fraud Detection and Risk Management

Financial institutions employ AI to detect fraudulent activities and assess risks in real-time. Machine learning models are trained to recognize patterns indicative of fraud or financial risk by analyzing transaction data. These models can identify anomalies that deviate from normal behavior, enabling companies to take preventive actions swiftly. This application is critical in safeguarding assets, minimizing losses, and complying with regulatory requirements.

AI with Alltius

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