Artificial Intelligence

What is artificial intelligence?

With the growing hype around AI, vendors have sought to promote the use of AI in their products and services. In this context, artificial intelligence requires a platform of specialized hardware and software to write and train machine learning algorithms. No programming language is synonymous with AI, but some, including Python, R and Java, are popular.

In general, AI systems work by collecting large amounts of selected training data, analyzing the data to find correlations and patterns, and using those patterns to make predictions about future states. In this way, for example, a chatbot could learn to have real conversations with humans using examples of text chats, or an image recognition program could learn to identify and describe objects in images using millions of examples.

Artificial intelligence programming focuses on three cognitive skills: Learning, Logical Reasoning, and Self-Correction.

• Learning: this aspect of AI programming focuses on gathering data and creating rules for how to turn data into actionable insights. Rules, also called algorithms, give computers step-by-step instructions on how to perform a specific task.
• Logical reasoning: this aspect of AI programming focuses on choosing the right algorithm to achieve the desired result.
• Self-correction: this aspect of AI programming is used to continuously refine algorithms to ensure that they produce the most accurate results possible.

What is the importance of artificial intelligence?

Artificial intelligence is important because it can give companies insights into their operations that they may not have known about before, and because AI can perform tasks better than humans in some cases. Especially for repetitive and detailed tasks like analyzing a large number of legal documents to make sure nothing is left out. AI tools usually get the job done very quickly and with relatively few errors.

Types of artificial intelligence

Artificial intelligence can be divided into four categories, from task-specific intelligent systems that are widely used today to sentient systems that do not yet exist. The categories can be divided as follows:

• Type 1, Reactive Machines: These AI systems have no “memory” and are task-specific. One example is IBM’s “Deep Blue” chess program, which defeated Garry Kasparov in the 1990s. Deep Blue can identify pieces on the board and make predictions, but since it has no memory, it cannot draw on past experience for future use.
• Type 2, Limited Memory: These AI systems have memory that allows them to use past experience to make future decisions. Self-driving cars are designed on this basis.
• Type 3, Theory of Mind: “Theory of Mind” is a psychological term. Applied to AI, it means that the system has social intelligence to understand emotions. This type of AI is able to recognize human intentions and predict behavior - a capability AI systems need to be full members of a human environment.
• Type 4, self-awareness: In this category, AI systems have a sense of self that gives them awareness. Self-aware machines understand their own current state. This type of AI does not exist today.

What are the advantages and disadvantages of artificial intelligence?

Artificial intelligence technology is changing rapidly, primarily because AI processes large amounts of data much faster and makes more accurate predictions than humans. While the vast amount of data generated daily would be overwhelming, AI applications that use machine learning can quickly turn that data into useful insights. However, artificial intelligence also has advantages as well as disadvantages.

Advantages

• Strong for detail-oriented tasks
• Less time consuming for data intensive tasks
• Delivers consistent results
• AI-driven systems are always available

Disadvantages

• Costly
• Requires in-depth technical expertise
• Limited supply of skilled labor to develop AI tools
• Can only learn content that the AI has had experience with in the past
• Lack of ability to generalize from task to task