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1. Digital Marketing With AI
The creation of computer systems that are capable of carrying out activities that normally require human
intelligence is known as artificial intelligence, or AI. Learning, thinking, problem-solving, speech recognition,
comprehension of natural language, and visual perception are some of these skills. AI seeks to build cognitively-
like computers that can evaluate information, come to conclusions, and gradually become more efficient.
 Certain common examples of AI which we use in our day-to-day life are:
1. Siri, Alexa and other smart assistants
2. Google maps
3. Live chatbots
4. Self-driving cars
5. Interactive video games
6. Wearable sensors and devices
7. Biosensors for medical purpose
8. Robotic-advisors for stock trading
 How Does Artificial Intelligence AI Work?
In order to solve complex problems by using human-like thought processes, artificial intelligence (AI)
science aims to develop computer systems that can accurately simulate human behavior. Artificial
intelligence (AI) systems process large amounts of data quickly and efficiently by combining intelligent
processing algorithms with the data.
AI accomplishes the tasks assigned to it in a way that is nearly identical to that of the human mind
thanks to its primary tools, “deep learning” and “machine learning.”
Artificial intelligence is the foundation of artificial intelligence (AI), and machine learning, of which
deep learning is a type, is a subset of AI.
 Machine learning (ML)
ML is a more general term that refers to the creation of models and algorithms that enable computers
to recognize patterns in data without needing to be explicitly programmed. A wide range of
approaches are included in machine learning (ML), such as support vector machines, decision trees,
and conventional statistical methods.
 Deep Learning (DL) :
DL is a branch of machine learning (ML) that specializes in multi-layered neural networks, or “deep
neural networks.” The architecture of the human brain, which is made up of interconnected layers of
artificial neurons, is attempted to be mimicked by deep learning algorithms. These neural networks
are capable of automatically identifying and representing intricate data patterns.
 Advantages of Artificial Intelligence (AI)
Artificial intelligence or AI, is a revolutionary achievement of the branch of computer science in its true
sense. Gradually, AI has become a core component of modern software over the years and decades
to come. Current and topical discoveries in AI development have stemmed mostly from “machine
learning” and “deep learning” algorithms.
Instead of feeding a particular set of data or information from AI to mimic or follow, the latest
techniques in AI use a large set of datasets and then perform predictive analysis.
For example, live chatbots based on AI are based on information comprising recordings of human
conversation, which is in turn collected from various messenger apps to learn the way how human
responds, and thus come up with appropriate responses
Following are the various benefits and advantages of AI:

2. More Accuracy and Precision: The main benefit of AI is that it is helpful in lessening human errors and
thus promises a high level of accuracy and precision in their outcome. The decisions taken by AI
based systems are based on past data or information and a certain set of algorithms. If AI is
programmed properly, then there are literally no chances of any error.
No Risks of Human Lives: AI can easily overcome many risks which might have fallen upon any
human being by letting AI robots work for them. With the help of an AI robot, all perilous tasks can be
performed via them without any direct human involvement.
For instance, AI robots can be used for diffusing a bomb, exploring the deep ocean, where machines
can easily work and survive but such tasks can cause enormous amounts of risks to human beings.
Available Round-the-clock: AI based systems can work anytime in a day. As AI systems do not need
any break and thus can work endlessly and perform multiple tasks with most accurate outcomes. AI
based systems or robots can even perform tedious and repetitive tasks with ease.
Serving Customers Digitally: Several new-age companies have started using AI based digital
assistants, which help them to deliver user-based content timely. Now, companies can create their
own chatbots which help them to answer all the customer queries much on time.
Unbiased Approach: Artificial intelligence does not work on the basis of emotions and sentiments, thus
helps in delivering highly practical and rational decisions. A huge advantage of artificial Intelligence is
that it doesn’t have any biased views, which ensures more accurate decision-making.
 Disadvantages of Artificial Intelligence ?
Lack of Understanding and Interpretability : AI models frequently function as “black boxes,” making it
difficult to comprehend how they arrive at particular decisions. This is especially true of complex models like
deep neural networks. Interpretability problems can be very serious in important applications where
accountability and transparency are crucial.
Security Concerns : Adversarial attacks, in which malevolent parties alter input data to trick the AI model, can
weaken AI systems. It is extremely difficult to guarantee the security and resilience of AI systems, particularly
in vital industries like healthcare and driverless cars.
Ethical Considerations : The use of AI raises ethical concerns, such as privacy issues, surveillance, and the
potential for misuse. Determining the ethical guidelines and standards for AI development and deployment is an
ongoing challenge.
Unemployment and Job Displacement : The automation of tasks through AI and robotics has the potential to
lead to job displacement in certain industries. Jobs that involve routine, repetitive tasks are particularly
susceptible to automation, which can result in unemployment for certain segments of the workforce.
High Implementation Costs : Developing and implementing AI systems can be expensive, requiring
significant resources in terms of infrastructure, skilled personnel, and ongoing maintenance. Small businesses
and developing economies may face challenges in adopting AI technologies due to these high costs.
Dependency on Data : AI systems heavily depend on the quality and quantity of data used for training.
Inadequate or biased data can lead to poor performance and unreliable outcomes. Moreover, some applications
may require vast amounts of labeled data, which might not always be readily available.
Limited Creativity and Common Sense : While AI systems excel at specific tasks, they often lack creativity,
intuition, and common sense reasoning. Understanding context, making nuanced decisions, and adapting to
unexpected situations are challenges for current AI technologies.
Lack of Emotional Intelligence : AI systems do not possess emotional intelligence or empathy. This limitation
is significant in applications where human emotions play a crucial role, such as healthcare, counseling, and
customer service.
Environmental Impact : Training large-scale AI models, especially deep neural networks, requires substantial
computational power and energy consumption. The environmental impact of AI, particularly in terms of carbon
footprint, is a growing concern.