Artificial Intelligence: A brief history, importance, advantages, and disadvantages
Artificial intelligence (AI) is the
intelligence expressed by robots when compared to the natural intelligence
exhibited by humans and animals. The study of intelligent agents, or any system
that understands its environment and acts in a way that maximizes its chances
of succeeding, has been defined as the focus of AI research. Read this article to know Artificial Intelligence: A brief history, importance, advantages, and disadvantages...
Machines are already capable of
mimicking and even outperforming human minds, thanks to artificial
intelligence. AI is becoming more and more prevalent in daily life, from the
emergence of self-driving cars to the proliferation of smart assistants like
Siri and Alexa. As a result, numerous IT firms from a variety of sectors are
making investments in artificial intelligence technologies.
What is Artificial Intelligence?
The goal of the broad field of
artificial intelligence in computer science is to create intelligent machines
that can carry out tasks that traditionally call for human intelligence.
A quick overview of artificial intelligence:
Computers could execute commands prior to 1949, but they were unable to retain these commands, therefore they were unable to recall what they had done. In his work "Computing Machinery and Intelligence," published in 1950, Alan Turing examined how to create and assess intelligent machines. Five years later, during the Dartmouth Summer Research Project on Artificial Intelligence, the initial AI program was displayed (DSPRAI). For several decades, this incident served as a catalyst for Artificial Intelligence development.
Between 1957 and 1974, computers
were quicker, more affordable, and more widely available. As machine learning
algorithms advanced, one of the hosts of DSPRAI predicted to Life Magazine in
1970 that within three to eight years, a computer will have the same general
intelligence as the typical person. Despite their achievements, computers'
incapacity to effectively retain or swiftly interpret information posed
challenges over the next 10 years in the development of artificial
intelligence.
With the development of the
algorithmic toolbox and increased funding, AI experienced a resurgence in the
1980s. Deep learning techniques, developed by John Hopfield and David
Rumelhart, let computers gain knowledge via practice. "Expert
systems," which resembled human decision-making, were first introduced by
Edward Feigenbaum. Despite a lack of government support and media hoopla, Artificial Intelligence flourished, and several significant objectives were accomplished over the
following two decades. Grandmaster and current chess World Champion Gary
Kasparov lost to IBM's Deep Blue, a chess-playing computer program, in 1997. In the same year, Windows users could use speech recognition software created by
Dragon Systems. Additionally, Cynthia Brea-zeal created Kismet, a robot that
could discern and express emotions.
A poker-playing supercomputer named
Libratus defeated the greatest human players in 2017 after Google's AlphaGo
algorithm defeated Lee Se-dol in Go in 2016.
Types of Artificial intelligence
Based on the kinds and levels of
complexity of the tasks a system is capable of performing, Artificial Intelligence can be categorized
into four categories. Automated spam filtering, for instance, belongs to the
most fundamental category of artificial intelligence, while the distant
possibility of creating robots that can understand human emotions and thoughts
belongs to a completely separate subcategory of Artificial Intelligence.
Here are types of artificial intelligence.
- Reactive machines: They can perceive and respond to the
environment around them while carrying out specific activities.
- Limited memory: able to save historical information and
forecasts to help with future predictions.
- Theory of mind: the capacity to make choices based on
assumptions about how others feel and think.
- Self-awareness: Ability to function at a human level of
consciousness and comprehend one's own existence.
Reactive Machines:
The most fundamental AI principles
are followed by a reactive computer, which, as its name suggests, can only use
its intellect to see and respond to the environment in front of it. Because a
reactive machine lacks memory, it is unable to use previous experiences to
guide current decisions.
Reactive machines can only perform a
small number of highly specialized tasks because they are only capable of
experiencing the world immediately. However, intentionally limiting the scope
of a reactive machine's worldview means that this kind of Artificial Intelligence will be more
dependable and trustworthy – it will respond consistently to the same stimuli.
Limited Memory
When gathering information and
assessing options, limited memory Artificial Intelligence has the capacity to store earlier facts
and forecasts, effectively looking back in time for hints on what might happen
next. Reactive machines lack the complexity and potential that limited memory Artificial Intelligence offers.
Limited memory Artificial Intelligence environment is
developed so that models can be automatically taught and refreshed, or AI is
created when a team continuously teaches a model in how to understand and use
new data.
Theory of mind:
The theory of mind is purely
hypothetical. The technological and scientific advancements required to reach
this advanced level of AI have not yet been attained.
The idea is founded on the
psychological knowledge that one's own behavior is influenced by the thoughts
and feelings of other living creatures. This would imply that AI computers
might understand how people, animals, and other machines feel and make
decisions through self-reflection and determination and would use that
knowledge to make their own decisions. In essence, robots would need to be able
to understand and interpret the idea of the "mind," the changes in
emotions during decision-making, and a plethora of other psychological notions
in real-time, establishing two-way communication between humans and machines.
Self-Awareness:
The final stage of AI development
will be for it to become self-aware after the theory of mind has been created,
which will likely take a very long time. This sort of AI is conscious on a par
with humans and is aware of both its own presence and the presence and
emotional states of others. It would be able to comprehend what other people
could need based on both what they say to them and how they say it.
AI self-awareness depends on human
researchers being able to comprehend the basis of consciousness and then figure
out how to reproduce it in machines.
Techniques for Using Artificial Intelligence:
Let's look at the following examples
of how we can use AI:
Learning Machines
Artificial Intelligence has the capacity to learn thanks
to machine learning. Algorithms are used to do this by mining the data they are
exposed to for patterns and insights.
In-depth Learning
AI can simulate the neural network
of the human brain thanks to deep learning, a branch of machine learning. It
can help make sense of the data's patterns, noise, and sources of misunderstanding.
AI Applications and How It Operates
The automatic switching of
appliances at home is a typical application of Artificial Intelligence that we see nowadays.
The sensors in the room recognize
your presence and turn on the lights when you walk into a dark space. This is
an illustration of a machine without memory. Some of the more sophisticated AI
programs can even estimate your consumption patterns and activate appliances
without your explicit input.
Some Artificial Intelligence applications can recognize
your speech and respond appropriately. The TV will turn on when you command it
to do so using its sound sensors.
Importance of Artificial Intelligence:
Artificial Intelligence has a variety of applications,
including speeding up a vaccine research and automating fraud detection.
According to CB Insights, 2021 witnessed
a record-breaking year for Artificial Intelligence private market activity, with global funding
rising 108% from the previous year. Artificial intelligence (AI) is causing a
stir in a number of industries due to its rapid adoption.
And for medicine, a 2021 World
Health Organization research said that while incorporating AI into the
healthcare industry has its difficulties, the technology "holds immense
potential" as it may result in advantages like better health policy and
more accurate patient diagnosis.
AI has also impacted the
entertainment industry. According to Grand View Research, the global market for
AI in media and entertainment would increase from a value of $10.87 billion in
2021 to $99.48 billion by 2030. In that extension, AI applications like
detecting plagiarism and creating high-definition visuals are included.
Advantages and disadvantages of artificial intelligence
Although Artificial Intelligence is undoubtedly seen as a valuable and rapidly developing asset, this young area is not without its drawbacks.
In 2021, the Pew Research Center
polled 10,260 Americans about their views on Artificial Intelligence. According to the findings, 37%
of respondents are more concerned than excited, while 45% of respondents are
both excited and concerned. Furthermore, more than 40% of respondents said they
believed driverless automobiles will be detrimental to society. Even still,
more respondents to the survey (almost 40%) thought it was a good idea to use
AI to track the spread of incorrect information on social media.
AI is a blessing for increasing
efficiency and productivity while also lowering the possibility of human error.
However, there are some drawbacks as well, such as the expense of development
and the potential for robots to take over human occupations. It's important to
remember, though, that the artificial intelligence sector has the potential to
provide a variety of occupations, some of which haven't even been imagined yet.