Artificial Intelligence: What is AI and how it can help us


Artificial Intelligence, the mere mention of it probably conjures up images of robots in science fiction and sci-fi movies But AI is so much more than just a futuristic concept.

The launch of ChatGPT by OpenAI in late November 2022 was met with a great deal of excitement and interest around the world. This has marked a significant advancement in the field of conversational AI (ChatGPT-4 is the more advanced model from OpenAI).

In this article, you’ll learn what AI is, how it works, and the potential ways that it can help us.

What is Artificial Intelligence (AI) exactly?

AI develops computer systems with human-like capabilities, performing tasks like decision-making, language understanding, and problem-solving.

The term “artificial intelligence” was first coined in 1956 and wasn’t until the last decade that the possibility of computer science achieving a human-like level of AI became a reality.

AI can be used in a variety of ways to help us automate tedious tasks so that human workers can focus on more meaningful work. Examples include medical diagnostics, automated customer service systems, robotic process automation (RPA), predictive analytics, and much more.

I. Artificial intelligence technologies and applications

Artificial intelligence technologies and applications have become increasingly important in the modern world. From self-driving cars to automated customer service, AI is making its mark in nearly every industry, from large corporations such as Google and Amazon to smaller startups.

Here are a few important examples of AI technologies and their applications

  • Medical Diagnosis: Machine learning systems equipped with image recognition, expert systems, and neural networks are helping medical professionals achieve accurate diagnoses.

One example is IBM Watson’s ability to assist with cancer research and diagnosis by analyzing vast quantities of medical data.

screenshot of IBM watson health home page


  • Chatbots: Chatbots powered by natural language processing can assist customers with questions, or resolving issues.
  • Autonomous vehicles: self-driving cars equipped with machine vision sensors, such as LiDAR and cameras, can detect objects and obstacles, and predict their motion.

Tesla’s Autopilot feature can navigate highways and even park in tight spaces.

  • Industrial robots: Robots used in manufacturing processes, such as car assembly and packaging and perform tasks that are repetitive or hazardous to human workers.

screenshot of amazon warehouse robots

source: amazon

  • Speech recognition: Commercial applications such as Siri and Alexa use deep learning models to perform speech and natural language processing tasks
  • Video Analytics: Video analytics can detect motion, track objects in the scene, and recognize people or faces.

II. The Building Blocks of Artificial Intelligence

To better understand AI’s potential, it’s important to look at the building blocks that make it possible.

A. Machine Learning

At the heart of artificial intelligence is machine learning, a subset of data science that trains computers to “learn” by recognizing patterns and leveraging algorithms to make decisions.

A machine learning algorithm is fed large quantities of data so that it can create a model, specific to a task. After the machine learning model is trained, it can be used to apply its learning to new data inputs.

Machine learning can be classified further into different categories, such as:

  • Supervised learning involves feeding a model labeled data and the model learns how to classify data based on the training data fed to it.
  • Unsupervised learning involves feeding the model unlabeled data an model learns to seek out patterns on its own without predefined labels.
  • reinforcement learning, which involves focusing on rewards and punishments to train the model, such as in the case of self-driving cars, where the car must learn to propel itself toward an objective.

Generative AI is a rapidly growing subfield within the broader subcategory of machine learning. It is focused on creating new content, such as text, images, and videos, using various machine learning techniques, including deep learning, and natural language processing (NLP).

Plenty of AI tools have come out in the last few years, from text-to-speech, AI art creation, natural language processing, music generation, video creation, and much more.

B. Deep Learning

A related area of machine learning is deep learning, which structures the neural network in a hierarchical and multilayered manner.  Creates computer systems that mimic human abilities, handling tasks such as making decisions, understanding language, and solving problems.

This technique has proven to be particularly useful in image and speech recognition, natural language processing, and even gameplay.

C. Natural Language Processing (NLP)

Natural language processing (NLP) is a subset of artificial intelligence that helps computers understand human language. This technology allows computers to read, interpret, and respond to natural human language, making it possible to build chatbots, voice assistants, and more.

For example, ChatGPT is a natural language processing (NLP) model that uses a type of deep learning algorithm called a generative pre-trained transformer (GPT). ChatGPT is an AI-powered chatbot that uses GPT technology to generate replies to user inputs.

screenshot of openai chatgpt 4 homepage

D. Computer Vision

Computer vision is an artificial intelligence technique that enables computers to recognize, interpret, and understand the visual world. This technology is used in various applications, including automated surveillance, self-driving cars, and facial recognition.

Computer vision technology must be able to analyze the visual world, including videos, images, and other objects, and recognize patterns in that data. As computer vision continues to improve, the potential applications for this technology are virtually limitless.

E. Neural Network

A neural network is a model of machine learning that simulates the neural structure of the human brain. Such artificial neural networks can recognize patterns and relationships in data, allowing AI to understand complex structures.

Deep Neural Networks (DNN)

These are a type of artificial neural network that uses deep learning algorithms to analyze data and make decisions. By using multiple layers of neurons, a DNN can learn complex patterns in the data it receives.

DNNs are used for a wide range of applications, such as object detection, facial recognition, and Robotics.

III. The Advantages of Artificial Intelligence

Artificial intelligence is an incredibly powerful technology that is rapidly changing the world around us. From healthcare and finance to transportation and retail, AI has the ability to transform virtually every industry.

let’s look at some of the benefits


One of the primary advantages of AI is its ability to automate routine tasks. AI-powered machines and software can handle tasks, such as data entry, customer service, and decision-making, quickly and with fewer errors than humans. This increased efficiency saves time and money for businesses and organizations, allowing them to focus on more high-level tasks.


AI-powered tools can process vast amounts of data at incredible speeds, making them suited for tasks that require high levels of accuracy.

For example, AI applications can detect even the tiniest differences in medical images, diagnose diseases, and even predict future complications. This can lead to earlier diagnoses and more effective treatment options, ultimately improving patient outcomes.


Artificial intelligence is highly adept at analyzing vast amounts of data to recognize patterns and personalize recommendations. For example, online shopping sites use AI algorithms to recommend products to customers based on their purchase history and preferences. This personalized approach keeps customers engaged, increases sales, and maximizes revenue for businesses.


Artificial intelligence is a constantly evolving technology, with new applications and uses cases being discovered all the time. This constant innovation and evolution lead to breakthroughs that can boost productivity, improve processes, and create new business opportunities. Additionally, AI can help companies to anticipate market trends, adapt quickly to changes in demand, and stay ahead of competitors.


AI-powered machines and software can also enhance safety in various industries, such as transportation and manufacturing. Autonomous vehicles can react more quickly to changes in the environment than human drivers and potentially reducing the number of accidents on our roads.

Cost Savings

AI’s efficiency and accuracy can result in significant cost savings for businesses and organizations. By automating routine tasks and reducing the need for human employees, AI-powered tools can free up resources that can be used for more critical endeavors.

Environmental Impact

By optimizing energy consumption and reducing waste, Artificial intelligence can also have a positive impact on the environment. For example, AI-powered smart grids can optimize energy distribution, reduce emissions, and cut down on energy waste.

IV. The Disadvantages of Artificial Intelligence

Artificial intelligence systems often require large upfront investments due to the cost of hardware, software, and data. Additionally, there may be ongoing maintenance costs if the system needs to be updated or tweaked.

Job Loss

One of the most pressing concerns about artificial intelligence is the potential loss of jobs. As AI-powered machines and software automate routine tasks and make them more efficient and accurate, human employees may become redundant. While new jobs may be created as AI advances, many workers will require reskilling to remain employable.

screenshot of current work tasks could be automated by AI in the US and Europe by 2030 according to Bloomberg

according to a recent study by Bloomberg.


Another significant disadvantage of artificial intelligence is the potential for bias. AI systems learn from datasets, including human-generated datasets, and can perpetuate existing societal preconceptions and prejudices. For example, AI-powered facial recognition systems have been found to be less accurate in identifying individuals with darker skin tones, leading to potential discrimination.

Lack of Creativity

Artificial intelligence systems rely on data inputs and algorithms, which can limit their creativity. AI lacks the ability to generate truly novel ideas or creative solutions to problems the way humans can. While AI can provide valuable insights and optimize processes, it cannot replicate the human mind or creativity.


As reliance on AI systems grows, dependence on this technology could become an issue. If systems fail, critical processes could be disrupted, leading to potential safety risks, financial losses, or other significant problems.

Ethical Concerns

Artificial intelligence systems can raise ethical concerns about privacy, transparency, and responsibility. AI-powered systems can collect vast amounts of data about individuals, leading to potential breaches of privacy. Additionally, it can be tough to trace and identify the decision-making process of AI-powered systems, leading to concerns about accountability.

High Costs

Artificial intelligence systems can be expensive to implement and maintain, requiring significant investments in computer hardware, software, and personnel. For smaller businesses or organizations with limited financial means, implementing AI may not be feasible.

V. AI’s Support of Big Data Analysis

Big data analytics is transforming the way businesses operate, and artificial intelligence (AI) is at the center of it all. AI’s ability to analyze vast amounts of data and provide insights and predictions is essential to making sense of big data.

A. AI’s Ability to Automate Tasks

Artificial intelligence has the potential to revolutionize how we work by automating tedious or repetitive tasks. This could free up time for more creative and meaningful activities and reduce costs by eliminating the need for manual labor. Additionally, automation can improve accuracy by reducing human error.

One example is UiPath – a software platform for automating repetitive tasks such as data entry, processing invoices, and budget forecasting.

screenshot of homepage of UiPath company

B. Improved Decision Making

Artificial intelligence systems are able to make decisions faster and more accurately than humans. This can help businesses make better-informed decisions quickly and effectively, leading to improved performance. AI can also be used to identify trends or patterns in data that may otherwise be difficult for humans to detect.

C. Improved Customer Service

Artificial intelligence can be used to improve customer service by automating mundane tasks such as answering frequently asked questions. AI-powered chatbots can provide instant responses to customers’ queries, which helps reduce wait times and improve customer experience. Additionally, AI can be used to analyze customer data and provide personalized recommendations or offers that can help boost sales.

one example Zendesk – is a platform that uses AI-powered chatbots and analytics to automate interactions, reduce response times, and identify customer trends.

screenshot of Zendesk homepage

D. Improved Predictive Analysis

Artificial intelligence algorithms can be used to identify patterns in large amounts of data and make predictions about future trends in structured data. This can help businesses plan for the future and better manage resources and improve decision-making by providing an accurate picture of potential risks or opportunities. AI-powered predictive analysis can also be used to identify potential customers or markets that may be worth targeting.

VI. AI Systems Still Require Human Oversight

Despite their potential, AI systems still require human oversight to ensure accuracy and prevent misuse. While artificial intelligence can automate mundane tasks, it can still make mistakes or misinterpret data in certain circumstances. Therefore, it is important that businesses establish proper protocols and procedures for monitoring their AI systems to ensure they are functioning properly. Additionally, businesses should consider the ethical implications of using Artificial intelligence and ensure they are taking appropriate measures to protect consumer privacy.

A. Explanation of AI Systems

Artificial intelligence systems are complex computer programs that can analyze large amounts of data and make decisions without human input. AI algorithms enable machines to learn over time, allowing them to adapt to changing conditions and become more accurate in their predictions.

B. Types of AI Systems

Reactive Machines: Reactive machines are AI systems designed to react only to current and present situations. They do not have memories or past experiences, and their decisions are based solely on current input.

Examples of reactive machines include self-driving cars, game-playing, and fraud detection systems.

Limited Memory Systems:  can retain a very limited memory ai the number of past experiences and thereby make decisions based on that limited memory.

Recommendation systems and autonomous robot vacuums are examples of limited memory systems.

iRobot Roomba – an AI-powered robotic vacuum cleaner that learns the layout of the home and adapts to different floor types.

screenshot of iRobot Roomba cleaning the floor

Theory of Mind Systems: These AI systems can understand people’s mental states, beliefs, emotions, and intent by analyzing their past behaviors, etc.

They can predict what people might do next and respond appropriately. They can have some capabilities, like natural language processing (NLP) and language generation, that help in analytic conversations.

Self-Aware Systems: These are the AI systems with consciousness. They know what they know and what they don’t know.

They can think about their internal state, emotions, and experiences and reason about them to improve their own cognitive abilities.

one example is Neurolink, Elon Musk’s company

screenshot of main homepage for neuronlike company of Elon musk

Human-Like Systems: are designed to function like human beings, capable of learning, reasoning, problem-solving, and even displaying emotions.

They are still under development and are expected to have a profound impact on human life in the future.

Sophia – an AI-based humanoid robot that can have conversations, express emotions, and make facial expressions like a human.


screenshot of homepage of Hanson Robotics presenting information about their robot Sophia

VII. Importance of Combining AI and Human Intelligence

While AI systems are becoming increasingly powerful, they still require human intelligence to ensure accuracy and prevent misuse. By combining AI with human expertise, businesses can harness the full potential of both approaches to create more effective solutions.

Humans can also help ensure accuracy by monitoring AI systems and detecting any errors or biases.

Additionally, humans can provide ethical guidance for AI applications to ensure they are used responsibly and in compliance with applicable laws and regulations.

VIII. What is Artificial General Intelligence (AGI)

Artificial General Intelligence (AGI) is a type of advanced AI system that can think and reason like humans.  AGI systems are capable of understanding complex concepts and making decisions based on multiple inputs.

Additionally, AGI systems can help improve decision-making by providing an accurate picture of potential risks or opportunities.

A. Benefits of Artificial General Intelligence (AGI)

There are several benefits to using AGI, including improved decision-making, more accurate predictions, and increased efficiency. AGI systems can help businesses gain valuable insights into customer behaviors or market trends. Additionally, AGI systems can automate mundane tasks quickly and efficiently, allowing businesses to focus on more creative work.

B. Challenges with Artificial General Intelligence (AGI)

Despite their potential, AGI systems still require human oversight to ensure accuracy and prevent misuse. Additionally, AGI systems may be prone to making mistakes or misinterpretations in certain circumstances.

Key Takeaways

– Artificial intelligence (AI) has immense potential to revolutionize how we work and live.

– AI can be used to automate mundane tasks quickly and efficiently, as well as improve decision-making by providing potential risks or opportunities.

– AI still requires human intervention and oversight to ensure accuracy and prevent misuse.

– Combining AI with human expertise can help businesses create more effective solutions to solve problems that are better suited to their needs.

– Proper protocols and procedures should be established to ensure AIare functioning properly and in compliance with applicable laws and regulations.

It’s clear that artificial intelligence has the potential to transform the way we approach work and our daily lives. By using intelligent systems businesses can ensure more efficient, precise, and timely completion of tasks. However, it’s crucial to remember that AI systems require human oversight.

We cannot rely solely on AI tools to operate with complete autonomy without the guidance of human intelligence. It’s imperative that humans are involved throughout the entire process, from the design phase to the implementation of AI systems.


Julian Neagu

As a tech and AI blogger with an entrepreneurial background, I aim to explore how AI can revolutionize technology and shape the future of innovation.

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