Artificial Intelligence (AI)

Content

• What is artificial intelligence?
• How artificial intelligence works
• Types of artificial intelligence
• Where artificial intelligence is used
• Artificial intelligence in marketing
• Advantages and challenges of implementation

What is artificial intelligence?

Artificial intelligence (AI) is the process of modeling human intelligence using machines and computer systems. Modern AI systems are capable of performing tasks that require intelligent thinking, including imitating human behavior, using information to solve problems, and participating in games. The integration of AI into various mechanisms and systems helps automate routine and complex processes, which in turn increases accuracy and productivity and reduces the risk of errors associated with the human factor.

However, modern AI systems have a limited set of capabilities. For example, a robot that can play chess will not be able to answer questions, and a waiter robot that can make coffee will not be able to participate in a Dota game. This highlights the importance of understanding that the AI we have today is still far from the universal capabilities inherent in the human mind.

How artificial intelligence works

Artificial intelligence encompasses a wide range of capabilities and technologies that are constantly evolving. There are two main approaches to AI development: machine learning and deep learning.

Machine Learning

Machine learning involves the use of labeled or unlabeled data for analysis, relying on mathematical and statistical methods. A small amount of input data is sufficient for predictions. The learning process is divided into clear stages, and the output is presented in numerical format: code, classification, evaluation, and cost. There are several methods of machine learning, including supervised and unsupervised learning. This allows humans to tackle monotonous tasks, such as sorting and classifying objects, as well as identifying patterns in data.

Deep Learning

Deep learning is considered a subtype of machine learning and uses neural networks for training. Unlike machine learning, where the model is trained on the original dataset, deep learning trains the model on the results of previous stages. This resembles the natural learning process of humans, who use their experiences to make decisions. Deep learning is characterized by the complexity of algorithms, where part of the process is hidden and lacks obvious logic. Modern neural networks represent one of the methods of deep learning and can have millions of hidden layers that process information.

Types of artificial intelligence

There are three main types of AI:

• Weak AI: This is the current version of AI used in voice assistants, image and text generation, as well as in autonomous vehicles.
• Strong AI: This type of AI will possess self-awareness and capabilities close to human abilities. It is expected to emerge no earlier than 2075.
• Super AI (AGI): General artificial intelligence that will be able to surpass humans in some aspects and program itself independently. Its emergence is predicted no earlier than 2300.

Considering the growing popularity of AI, many companies are actively integrating AI technologies into their products and marketing strategies, even if sometimes these developments cannot be truly called artificial intelligence.

Where artificial intelligence is used

Artificial intelligence is implemented in various fields, including:

• Transport: Autonomous vehicles and drones use AI technologies to deliver goods to remote areas.
• Medicine: Neural networks help diagnose diseases from medical images and predict disease progression.
• Business: AI is used for risk assessment, analyzing customer solvency, and optimizing costs.
• Communications: AI allows for voice command recognition and managing chatbots for customer support.

Artificial intelligence in marketing

Companies use AI for:

• Conducting marketing analysis and demand forecasting.
• Automating the purchase of digital advertising using neural networks.
• Generating recommendations, significantly increasing sales.
• Creating content, including text, images, and translations.

Advantages and challenges of implementation

Despite the numerous advantages of AI, there are several challenges that need to be considered:

• Advantages:
  • Minimizing the impact of the human factor, which reduces the number of errors.
  • Accelerating processes through rapid processing of large volumes of data.
  • Cost savings, allowing companies to optimize expenses.
  • Reducing risks, especially in life-threatening areas.
• Challenges:
  • Requirement for human resources to train models and collect data.
  • Limitations in performing a narrow range of tasks.
  • High costs of developing and implementing technologies.
  • Potential threats associated with the use of AI, such as the creation of deepfakes.

Considering these aspects, it is important to minimize risks and develop legislative measures to ensure the safe use of AI. Currently, AI is a powerful tool that must be mastered, not feared.