What is Artificial Intelligence (AI)? How companies can benefit from artificial intelligence?
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First, learning, which is the
acquisition of information and the rules for using it.
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Then reasons or uses rules to reach
approximate or definite conclusions.
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Finally autocorrect. Particular
applications of AI include narrow AI, facial recognition, and computer vision.
The AI can be classified as weak or strong. Weak AI or
Narrow AI is an artificial intelligence system designed and trained for a
specific activity. As such, virtual personal assistants like Apple's Siri are a
weak form of artificial intelligence. Strong AI or artificial general
intelligence has human cognitive abilities. Given an unknown task, a good AI
system can find a solution without human intervention.
The hardware, software, and human resource costs for
artificial intelligence can be high. Many vendors include AI components in
their standard offering and have access to them. AIaaS
(Artificial Intelligence as a Service)) platforms. AIaaS allows people and
businesses to experiment with AI and test multiple platforms before committing.
Popular AI cloud computing offerings include Amazon AI Services, IBM Watson
Assistant, Microsoft Cognitive Services and Google
AI Services.
Advanced intelligence for the general public:
Artificial intelligence tools offer a range of new
capabilities for businesses. However, the use of AI raises ethical questions.
Indeed, deep learning, or deep
learning, algorithms are the foundation of many of the most advanced artificial
intelligence tools. However, their intelligence depends on the data provided to
them during training. Because a human selects the data used to train an AI
program, the risk of human bias is inherent and should be closely monitored.
Types of artificial intelligence:
According to Arend Hintze, an assistant
professor of integrative biology, computer science and engineering at Michigan
State University, there are four types of artificial intelligence, some of
which do not yet exist.
Reactive machines: Examples include
Deep Blue, the IBM chess program that defeated Garry Kasparov in the 1990s.
Deep Blue can identify the pieces on the board and make predictions. However,
he has no memory, so he does not learn from his past experiences. Just analyze
the possible moves and choose the most strategic one. Therefore, Deep Blue
cannot be applied to other situations.
Limited storage: Your AI systems
can use past experiences to make future decisions. Some decision-making
features of self-driving cars are designed this way. However, these
observations are not archived indefinitely.
Theory of mind: A kind of AI that doesn't exist yet.
This psychological term refers to understanding the beliefs, desires, and
intentions of others that influence your decisions.
Self-awareness: What is not yet available? That is,
artificial intelligences with a sense of self and consciousness. This would
allow them to understand their current state, but also to infer what others are
feeling.
Examples of AI technology:
Artificial intelligence is incorporated
into various types of technologies, of which six examples are listed here.
1. Automation
It is what makes a system or process
work automatically. For example, robotic process automation (RPA) can be
programmed to complete repetitive tasks faster than humans.
2. Machine learning
Machine learning is the science that allows a computer to
do things without programming it. Deep learning is a subset of this, which can
be considered the automation of predictive analytics. There are three different
types. First, supervised learning, where the records are marked so that the templates are
recognized and then reused. So, unsupervised learning, where the records are not labeled but ordered by
similarity or difference. And finally,
enhanced learning, where the records are not labeled but the AI receives
feedback after taking action.
3. Computer vision
It is a technology that captures and
analyzes visual information using a camera. It is used in signature recognition
or medical image analysis.
4. NLP (Natural Language Processing)
Natural language processing is the processing of human
language by a program. Spam detection is an old example. However, current
approaches are based on machine learning. Therefore, they include translations
of texts, sentiment analysis and voice recognition.
5. Robotics
It deals with the design and
manufacture of robots. They are then used on car assembly lines or by NASA to
move large objects in space. The researchers are now looking to incorporate
machine learning to build robots that can interact in social settings.
6. Autonomous car
These vehicles combine artificial
vision, image recognition and deep learning. This is how artificial
intelligence develops an automated ability to drive a vehicle. And all this
while staying in a given lane and avoiding unexpected obstacles such as
pedestrians.
How companies can benefit from artificial intelligence:
Consequence of this democratization: all companies,
regardless of their size and the amount of data they manage, can benefit from
artificial intelligence. And all sectors are affected or will be tomorrow.
Automatic
translation, predictive maintenance, chatbots and other virtual assistants are well-known examples... Even today you can expand the
capabilities of your employees by freeing them from repetitive tasks and low
added value, ensure that your customers, drivers, do not fall asleep at the
wheel and even improve your business model to combine data, artificial intelligence
and human skills.
As for the sales force, thanks to algorithms, they have
the opportunity to better target the right prospects and meet the customers who
need to pamper them, thanks to the automatic analysis of conversations. In
short, where there is digital, there is (or there will be). ) artificial
intelligence. What can give you a real competitive advantage... Many companies
have understood this well.
TOWARD: All sectors affected
Many companies around the world are now using artificial
intelligence to be more productive, efficient and innovative.
Artificial Intelligence in
industry
Networked machines are increasing on assembly lines Speed,
reliability and number of compliant parts: the winning triplet of a production
line. The integration of artificial
intelligence in the food industry further expands this triptych by using
production data proactively and not just in case of failure. The button: fewer
accidents, better machine availability and last, increased productivity.
This preventive or predictive maintenance is based on
some key steps: data collection through sensors; centralize and analyze; Model
error patterns and implement algorithms that learn to recognize warning
signs... To achieve operational benefits, reduce risk and improve maintenance.
Artificial Intelligence in
after-sales service
We also know chatbots available 24/7, capable of
informing, advising, engaging or entertaining. Chatbots
have been your best customer service allies in recent years- and even assets for the employees of some companies,
with the appearance of numerous artificial intelligence software.
Artificial intelligence in health
care
But the producers are not the only ones who are seduced. Health
professionals have understood the interest in artificial intelligence and have
begun to use it. Doctors improve the diagnosis of
oncological diseases and pave the way for preventive and not only curative
medicine.
Ethical and safety concerns:
The concept of autonomous vehicles
raises questions about safety and ethics. Vehicles can be hacked. And in
relation to an accident, the responsibility is not clear. Additionally,
self-driving cars may find themselves in a situation where an accident is
unavoidable, forcing the AI to make an ethical decision on how to minimize
the damage. Another big problem is the risk of misuse of artificial
intelligence tools.
In fact, hackers are starting to use
sophisticated machine learning tools to break into sensitive systems. This
further complicates the security issue. Ultimately, deep learning-based video
and audio creation tools were quickly redirected to deep fake creation, that
image synthesis technique that enables the intelligent permutation of faces.
Despite the potential risks, there is
little regulation when it comes to artificial intelligence. The GDPR (General
Data Protection Regulation) sets strict limits on the use of consumer data by
companies. This regulation therefore hampers learning and some artificial
intelligence functions aimed at consumers.
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