Augmented Reality VS Artificial Intelligence VS Machine Learning: What’s the Difference?

Have
you ever wondered why machines were invented in the first place? The
answer is simple, ‘to ease human lives. This simple context led to
many technological evolutions – from eCommerce software for online
shopping to virtual medical consultations, AR-guided traveling
experiences, and so on.

Since
then, our lives have changed drastically as digital software
solutions and smart gadgets have sneaked into our daily itinerary.
This gives more scope to entrepreneurs investing in digital products.
With cutting-edge technologies like artificial intelligence,
augmented reality, and machine learning, one can further create
unique user experiences.

However,
you need to
hire
AR app developers

or AI, and ML developers to implement the right features and create
unique solutions. But before you do so, it is at most essential to
know the difference between these terms and what can be best for your
project.

Here,
we will talk about three such technologies that are most talked about
in recent times – Artificial intelligence, Machine learning, and
Augmented reality & how they are different from one another.

Let’s
dive right into it!

AR,
ML, & AI – An Introduction

  1. Artificial
    intelligence

As
the term indicates, it is the intelligence possessed by machines,
much similar to the intelligence of human beings or animals.
Artificial intelligence or AI allows machines (software) to simulate
human-like intelligence so they can perform certain tasks.

Applications

There
are multiple applications of artificial intelligence, such as –

  • AI
    in eCommerce for virtual assistants or chatbots, personalized
    shopping, etc.

  • Smart
    content creation, automation of administrative tasks, personalized
    learning, and voice assistants in the education sector.

  • AI
    to build facial recognition systems, smart NPCs for sports, and
    disease-detecting software in healthcare.

  1. Machine
    learning

is
considered a subset of AI or artificial intelligence. The process of
machine learning allows machines/systems to learn how to
perform/behave without being pre-programmed. As part of the process,
the systems are fed with numerous data and data patterns and machines
act based on these knowledge graphs, data input, training data, etc.

Such
information help systems analyze the entities and domains along with
the connection between them. Much like a human brain, these systems
learn more as their data knowledge and experience grow.

Applications

  • Used
    widely in retail and finance for the development of AI-powered
    product recommendation engines.

  • For
    building accurate disease detection and diagnosis systems in
    healthcare.

  • Development
    of automated trading systems.

  • Detection
    of vulnerabilities in data security.

  1. Augmented
    reality

AR
or Augmented reality enables adding digital information (visual,
sensory, sound) to the real world through technology. While AI and
machine learning work under the hood of any system, AR can be
accessed with digital gadgets like smartphones, smart watches, etc.

Applications

  • One
    of the most popular utilization of AR is augmented reality mobile
    app development. It became popular with a gaming app named Pokemon
    Go where players could catch virtual Pokemons in real-life places.

  • Trying
    eyeglasses and sunglasses on popular apps like Lenskart is possible,
    thanks to AR.

  • When
    trying to shop furniture online, you can open the AR-guided camera
    to check how the furniture will look in the foreground space of your
    home.

AR,
ML, and AI – Similarities & Differences


While
the above points discuss what AR, AI, and ML are, it doesn’t help
us understand the similarities and dissimilarities between these
terms. Here, we will discuss based on numerous factors mentioned
below.

  • Popularity

AI

AR

  • In
    2015, there were a noted 200 million AR devices found globally,
    which is likely to increase to 1.7 Billion by the end of 2024 as per
    a
    Statista
    report.

Machine
learning –

  • As
    reports, leading streaming platform Netflix has saved about $1
    Billion, courtesy of machine learning in personalized content
    recommendations.

  • As
    per a Refinitiv survey, about 20% of C-suite executives believe that
    machine learning is a crucial part of their business operations.

  • App
    examples

AI

AR

Machine
learning

App
Examples

  • Google
    Assistant

  • Siri

  • Alexa

  • Cortana

  • Databot

  • Google
    Lens

  • GIPHY
    World

  • ROAR

  • Augment

  • IKEA
    Place

  • Snapchat

  • Dango

  • ImprompDo

  • LeafSnap

  • MigraineBuddy

  • Differences

AI

AR

Machine
learning

Principle/
elements

Fairness,
explainability, human-centeredness, transparency, and privacy and
security.

3D
identification of real & virtual objects, augmentation of the
physical and real-world, and real-time interactions.

Evaluation,
optimization, and representation.

Advantages

Useful
in converting data into knowledge, improved work efficiency, and
accurate computations.

Illustrative
real-time experiences improved user information and knowledge

Identification
of trends/patterns, continuous improvement, and automation.

Disadvantages

High
implementation costs, accurate development is slow, may remove
many job opportunities.

An
AR app development company might find its implementation costly,
or it might not be appropriate in certain scenarios.

Error-prone,
and time-consuming, identifying the best algorithm is difficult.

Now
that we have walked you through these terms one by one, you should be
able to differentiate amongst them. It will also help you implement
the right strategies in your mobile app or web solution. Accordingly,
you can opt for AR development services or AI/ML services as your
software demands.

Make
sure to take an informed decision!

Summary

Artificial intelligence, machine learning, augmented reality – We
often come across these technical terms and might even know them.
But, we tend to mistake one for another as we aren’t well
frequented with it. In this blog, you will learn more about these
terms and how they are different from one another.

Author
Bio:
Maulik Shah is the CEO of
BiztechCS, a development
company. He often takes the front seat in the company’s development
projects, because he enjoys solving problems through technology. When
it comes to writing for any blog, his contribution is priceless.
Maulik ensures that his interaction with development is frequent
enough, and his industry knowledge is ever-evolving so that he can
share it. Despite his packed days, Maulik’s door is always open and
he is generous with sharing this knowledge and experience.

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