The acronym, AI has become a trend that most people tend to find out what
it truly means and what makes it so special to the point that everyone is
talking about it. AI stands for Artificial Intelligence and it is software that can
perform several task including improving existing workflows, predicting
customer behavior, and many others.
Meanwhile, AI technology has been in existence since the era of IBM’s
Deep Blue, a computer created to play chess against humans. Today, AI is
increasingly shaping the marketing landscape. You just have to make your
team adapt to its tech stack to be able to compete. This article will be
exposing, however, briefly, what AI is and how it works.
All about AI (Artificial Intelligence)
Definition
Widely known by its acronym (AI), Artificial Intelligence is an advanced
technology, significantly operated by a series of algorithms, computers, or
robots, which adopt real-time data to stimulate human intelligence. It is a
wide variety branch of computer science that has to do with creating smart
machines that can perform functions, which require human intelligence.
Again, through AI, machines can model, or even improve upon what the
human mind is capable of. Ever since its creation, it has increasingly
upgraded from developing self-driving cars to the proliferation of generative
AI tools such as ChatGPT and Google’s Bard. Hence, making the software
a part of daily life and an investment area for several companies.
Artificial Intelligence is an interdisciplinary science that has vast
approaches, improvements in machine learning and particularly, deep
learning, which create a paradigm shift in almost all sectors of the tech
world. The AI software is capable of replicating human intelligent thinking
and creates real-time decisions.
Overall, AI is programmed in such a way that it can think, act, and respond
in the same way humans do. However, you shouldn’t confuse this software with automation. Both may be requiring real-time data to function, however,
they have completely different mechanics and output.
For instance, automation needs manual data to function in a given task. As
long as it uses an algorithm, the function will repeat, irrespective of what
the data implies or if an error occurs. Invariably, AI is machine learning;
hence, can only function with a data input. During its data processing, it can
detect behavior patterns and errors, before adjusting its functions and
algorithms as required.
History
It is totally understandable how much interest so many people show in
knowing how AI came about, owing to how rapidly it has enveloped the
tech world. We would be giving you a brief history and origin of the Artificial
Intelligence. It has been a significant part of SAS software for many years.
In 1956, the term Artificial Intelligence was first initiated, but today is
increasingly trending, because of its improvement in data volumes,
advancement in algorithms, and improved computing power and storage.
Researches, especially during the 1950s looked at topics such as problem
solving and symbolic methods.
Then, the US Department of Defense became drawn to this type of work
during the 1960s and started training computers to imitate basic human
reasoning. For instance, long before Siri, Alexa, or Cortana became
household names, the Defense Advanced Research Projects Agency
(DARPA) carried out street mapping projects during the 1970s and created
intelligent personal assistances in 2003.
The early works of these agencies today, played a key role in the
automation and formal reasoning functions we now witness in computers.
These functions include decision support systems and smart search
systems, which can be created to complement and replace human abilities.
Types of AI
For a better understanding of Artificial Intelligence (AI), it has been divided
into four major categories, based on the type and the complexity of the
tasks a system is capable of performing. They include Reactive Machine,
Limited Memory, Theory of Mind, and Self Awareness. Let’s briefly discuss
each of these AI types.
1. Reactive Machine
As its name suggest, the reactive machine is a type of AI that can respond
or react to real-time data. However, it functions are limited, because it can’t
store information or create a memory bank. Owing to its inability to store
memories, the AI can hardly use previous experience to analyze data
based on current data behavior.
As long as reactive machine technology is concerned, it is best suitable for
repetitive tasks created for simple results. You can also use this tool when
organizing new client information or filter spam from your inbox.
2. Limited Memory
The functions of limited memory are opposed to that of the reactive
machines, because the former can store and use information to learn new
tasks. If you want to set a limited memory machine in motion, you need
pre-programmed data. Immediately the information has been processed,
it’ll analyze real-time data to predict and observe.
Meanwhile, limited memory technology is the most commonly used AI
technology in business. It makes self-driving cars to work. A good example
of this technology is the chatbot, which uses pre-programmed data to
interact with customers and predict what they need based on their actions
and inquiries.
3. Theory of Mind
Another category of AI on our list is the Theory of Mind, which is more
advanced than limited memory. It works more like the latter by storing
information and making observations based on real-time data it observes.
However, it presents a more advanced option, which means it can react to
human emotions.
As long as theory of mind is concerned, it must be built to understand the
complex nature of humans, alongside individual though patterns and past
experiences affecting how they react to a given stimulus. This feature is the
reason why the theory of mind technologies is not yet completely
developed. Currently, AI cannot completely react to people in human way.
4. Self-Awareness
With time, the AI creators were able to create another AI technology
category, known as Self-Awareness, as an upgrade on the theory of mind
type. In other words, it is a one-step further on the theory of mind, as the
self-awareness is capable of processing information, storing it, using it to
inform decision-making processes.
You can also use this type of AI technology to understand human emotions
and feelings, and is also self-aware on a human level. This means that it
functions like human consciousness and can have their thoughts and
feelings. Even though it is still far from being fully developed, reaches are
ongoing to that effect.
Key Examples of AI (Artificial Intelligence)
As long as AI is concerned, it comes in various tools including chatbots,
navigation apps and wearable fitness trackers. The following are examples
illustrating the breadth of potential AI applications.
ChatGPT
ChatGPT is a basic example of the AI technology that can produce written
content in various formats such as essays, code, answers, and simple
questions. ChatGPT was released in November 2022 by OpenAI and
powered by a vast language model, which lets it to closely imitate human
writing. It was also seen as a mobile app for iOS and Android devices in
May 2023 and July 2023, respectively.
Google Maps
Google Maps is another great example of AI. It monitors the ebb and flow
of traffic and assesses the fastest route of journey, using location data from
smartphones and user-reported data on things such as construction and
car accidents.
Smart Assistants
Tools like Siri, Alexa, and Cortana use natural language processing, or
NLP, to get instructions from users to set reminders and search online
information, as well as control lights in people’s houses. Most times, these
assistants are created to learn a user’s preferences and improve their
experience over time, alongside better ideas and more tailored responses.
Wearables
In certain industries like healthcare industry, you will find the wearable
sensors and devices that apply deep learning to assess the health
condition of the patient. In other words, they can assess blood sugar levels,
blood pressure and heart rate. These tools can also borrow patterns from a
patient’s medical data and use it in anticipating any future health cases.
MuZero
Created by DeepMind, the Muzero is a computer program that I aiming to
attain true artificial general intelligence. It has succeeded in mastering
games that it hasn’t even be taught to play, such as chess and all kinds of
Atari games, using brute force, playing games numerous times.
Snapchat Filters
AI also has Snapchat filters, which use ML algorithms to differentiate an
image’s subject from the background. It also tracks facial movements and
positions the image on the screen based on what the user is doing.
Self-Driving Cars
Another significant example of deep learning machine is the self-driving
cars, primarily because they use deep neutral networks to identify objects
around them, determine their distance from other cars, and even detect
traffic signals, amongst others.
Importance of AI
In recent years, Artificial Intelligence (AI) has been a key part of SAS
software. As it stands, customers in almost all industries has continued to
capitalize on advancements in AI, and AI tools such as machine learning
and deep learning is increasingly used to solve problems across the SAS
portfolio. The following are basic benefits of the AI technology:
- AI automates repetitive learning and discovery using
data. Rather than automating manual tasks, AI performs frequent,
high-volume, computerized tasks. It does so without stress, and you
can count on it to deliver perfectly. However, humans still play vital
roles in setting up the system and asking the right questions. - AI adds intelligence to existing products. Of course, it is not called
Artificial Intelligence for nothing. Several products you already use
will be notably enhanced with AI capabilities. For instance, Siri was
inputted as a feature to a new generation of Apple products. Also,
automation, conversational platforms, bots and smart machines can
be used with large amounts of data to improve lots of technologies.
There are certain upgrades made at home and in the workplace,
which use security intelligence, smart cams, investment analysis. - AI adapts through progressive learning algorithms to allow the
data do the programming. AI explores certain structures and
regularities in data to enable algorithms to acquire skills. Just as an
algorithm can equip itself to play chess, it can also teach itself what
product to recommend next online. And the models adapt when given
new data. - AI analyzes more and deeper data through neural networks that
have multiple hidden layers. Before now, it was almost impossible to
create a fraud detection system with five hidden layers. But today, it
has changed, thanks to incredible computer power and big data.
Large data is required to train deep learning models since they learn
directly from the data. - AI achieves incredible accuracy using deep neural networks. For
instance, your interactions with Alexa and Google are all dependent
on deep learning. And the more you use these products, the more
accurate they become. In the medical field, you can now use AI
techniques from deep learning and object recognition to ascertain
cancer on medical images with improved accuracy. - AI gets the most out of data. When algorithms are self-learning, the
data itself is an asset. You’ll find the answers you need in the data.
All you need to do is just to apply AI to find them. Since the role of the
data is now more important than ever, it can create a competitive
advantage. Note that the best data in a competitive industry will
always come out trumps, even if everyone is applying the same
techniques.
Problems & Disadvantages of AI
Despite the numerous benefits that come with the advent of the Artificial
Intelligence, including its evolving assets, a closer look will show you that it
also has some challenges and limitations.
For instance, in 2021, The Pew Research Center carried out a survey on
10,260 Americans to ascertain their attitudes towards AI. Its founding
showed 45% of respondents to be excited and concerned in equal
measure, and 37% to be more concerned than excited, and finally over
40% said they see driverless cars as bad for society.
Still, the idea of using AI to identify the spread of fake news on social media
was better received, thanks to almost 40% of respondents, who labeled it a
good idea. Even though AI is a vessel for enhancing productivity and
reduces the potential for human error, it also comes with disadvantages.
Some of the most obvious disadvantages of the AI include development
costs and the possibility for automated machines to replace human jobs.
However, you must also consider the fact that the AI industry is built to
create jobs, even though some of them have not been invented yet.
How Artificial Intelligence (AI) Works
Given the recent hype in the AI technology, a lot of businesses have been
fighting to promote its usage in their products and services. Most times,
what these vendors see as AI is just a sector of the technology like
machine learning. AI needs a foundation of specialized hardware and
software for writing and training machine learning algorithms.
But how does the AI work? Generally, AI technologies work by ingesting
numerous training data, analyzing the data for correlations and patterns,
and the use of these patterns to predict future states. Through this means,
a chatbox, in which examples of text are loaded, can learn to generate
lifelike interactions with people.
OR an image recognition tool can learn to identify and describe objects in
images through the review of numerous examples. Recent fast improving
generative AI systems can create realistic text, images, music and other
media.
Meanwhile, there are certain cognitive skills in which AI programming
focuses on. Below are the basic skills:
Learning: This particular skill has to do with acquiring data and creating
rules on how you can change it into actionable information. The rules,
otherwise known as algorithms, offer computing devices alongside detailed
instructions on how to finish a certain task.
Reasoning: It involves choosing the most suitable algorithm that can help
you reach a desired outcome.
Self-correction: It is an aspect of AI programming that is created to
steadily fine-tune algorithms and ensure they yield the most accurate
results possible.
Creativity: This particular aspect uses neutral networks, rules-based
systems, statistical techniques and other AI methods in generating new
images, new text, new music and new ideas.
How to Create Basic Artificial Intelligence (AI)
Most people often think see AI, its techniques and its applications to be
overly complicated; hence, prove difficult to benefit from. But that is not
usually the case, as several companies have used AI to carry out repetitive
functions that often drain their workers of their valuable time, especially,
time they would’ve used to strengthen client relationships or making sales.
If you want to use AI technology, you must think about the processes and
workflows to take out from your worker’s plates. Most importantly, you can
consider processes you can automate and will not have to tweak as AI
performs its duties. Below are the basics of how to implement AI in your
workflow:
- Define the Problem
The first thing to do if you want to incorporate AI into your workflow is to
consider the processes your teams use every day, and make sure they are
time-consuming and repetitive. The basic questions should surround the
amount of time your team spend to sort out data used for finding contact
information for potential clients.
Secondly, you must consider if your workers can use their time better by
negotiating to potential clients and onboarding new customers. Also, try to
identify time-consuming tasks and create a list, through which a process
that is straightforward and repetitive. - Define the Outcomes
Another interesting thing AI does is to improve already established
processes. After making a list of processes and workflows that’ll be most
beneficial from AI, the next thing to do is to define your desired outcomes.
For instance, AI can gather and sort client base.
But before AI can perform this task, you must tell it what to find and how it
can sort the information. Again, ensure you define the outcomes of your AI
processes clearly. Don’t forget AI functions best when you have an end
goal in mind. - Organize the Data Set It is very important to have a large, organized, data set to input into AI technologies. In situations where you don’t have an already kept data in a
centralized location, then you must do so before implementing AI. You
wouldn’t want your program to lack an essential data set due to the
different system it was housed. The best CRM to organize your data is the HubSpot’s, as a clean data that the algorithm can read is required; hence, giving the AI system a better understanding of the data set and recognizing its patterns and behaviors. - Picking the Best Technology
Out of the numerous AI algorithms to select from, each perform a task with
different efficiency and quality. Therefore, you must understand that not all
algorithms will work well with your data set, problem, or desired outcome.
Hence, you must take your time to research the most appropriate AI
technology and picking the one that’s best suitable for your needs. Then
run the data to create a model. - Test, Simulate, and Solve
After picking the right technology and creating a model, you can now rerun
that data to test it. This action will enable you to notice any kinks that need
to be worked out. Immediately you’re ready to implement AI, input it into
your workflows and it will duly perform its task admirably. You and your
workers can now channel your time for more pressing and valuable tasks.
Conclusion
Artificial Intelligence (AI) is one of the most popular technologies that has
taken over the modern world, and has evolved to provide many specific
benefits in every industry including health care, retail, and more. You can
share your thoughts about this post in the comment section concerning
what you think about the advent of AI technology and its functions.