Machine Learning Applications In Design

Machine Learning Applications In Design

With the advancement of technology, many fields are merging to create better results. Such advancements in technology, particularly in the field of AI and Machine Learning, have proven to be effective in solving age-old problems.

Machine Learning (ML) is a huge part of our digital world. It will automate jobs that most people thought could only be done by humans.

From suggesting music videos to curating a collection of photographs with the same theme, machine learning is much bigger than one can imagine. Machine learning in design has been floating around the internet.

What Is Machine Learning?

Machine learning is a process by which a system grasps knowledge similar to the way humans learn. It is a subdivision of Artificial Intelligence and Computer Science.

Machine learning is the future of data science.

ML works by forcing the system to run through a set of given tasks repeatedly. Thus, allowing it to identify the pattern.

Companies such as Tooliqa, AntWorks and Netguru work on machine learning and computer science to improve the lives of people with some innovative efforts.

How Does Machine Learning help in Design?

In simple terms, when a machine is fed with numerous pictures of an element, it slowly starts to recognize the element. But, to dive deeper into the accuracy of how machine learning works, here are the steps that aid in the process:

  1. Decision-making Process - The system needs data. This data, labelled or not, is then processed by the system. This system creates an algorithm that helps produce an estimate of the pattern.
  2. Error Function - This function backs up the prediction of the model. It also compares the accuracy of the model with the already known examples (if any).
  3. Model Optimization - Some models are bound to have some differences. The algorithm will evaluate and optimize the weights until a threshold of accuracy is reached.

Types Of Machine Learning

  • Supervised Learning

As the name suggests, supervised learning allows a person to provide feedback to the AI system showing the system what conclusions to arrive at and what should have been the conclusion based on the data already tagged.

Supervised learning takes place when the system is trained on a particular thing and needs to make the required prediction. It is widely used in image recognition practices and house pricing.

  • Unsupervised Learning

This learning process trains the AI to find hidden patterns and detailed structures in the given data without any regard for the output. Unsupervised learning is used for problems concerning the detailed exploration of the given data.

  • Semi-supervised Learning

Semi-supervised learning uses small scale data sets to classify and extract larger, unlabeled data sets.

It is a nice mixture of supervised and unsupervised learning.

Importance Of Machine Learning in Designing

Slowly but surely, machine learning is getting into the world of design. But how is it aiding in design? Well, we can do amazing things when teaming up with a nonhuman perception. Machine learning will help the system evolve by taking note of the designers' reactions to their design proposals.

With the teamwork of humans and machines, unachievable things can be designed.

That is why machine learning is going to take the design world by storm.

Albeit it may not be a good one.

ML has granted robots the independence of completing a task without the aid of a designer. That is why designers will have to work harder and depend on humanistic approaches to keep their place in the design world.

Decoding the Various Aspects of Design

Designing is a vast field.

This field consists of so many different subsections that decoding what machine learning does to each is necessary.

  • Graphic Design

Graphic design is a vital part of the design industry. It focuses on creating engaging content, be it physical (newspapers layouts, magazines designs, etc.) or virtual - (Website design, logo design and so on).

The introduction of Machine learning has made the designers lives a lot more uncomplicated. AI and ML are undoubtedly faster than any human-run program, but the thing that stands out the most is their self-learning ability. Therefore, the introduction of machine learning will make the designer's work easier by the lot, sparing some time for more innovative ideas.

ML will help create designs and strengthen research by suggesting changes possible only after extensive research through their understanding of the concepts.

UI/UX design is the future of the design world.

It focuses on providing a better platform for people in the world of technology.

Machine learning can program a computer to help customize the user experience by gathering data and identifying the pattern in them. Apart from this, it also aids in user interfaces regarding voices and adaptiveness. That is why machine learning makes for a personalized and engaging user experience and also helps one present their brand to the customer more effectively.

Product design is a part of the designing world that focuses on designing products with better efficiency. It covers a wide area when it comes to providing products to businesses.

Machine learning along with AI simplifies the steps in the design process and also corrects missed errors.

With the development of machine learning, product designers will get the required aid with utmost swiftness.

ML can help create technologically intelligent designs that are most sought after in today's world. It does this by learning the various scenarios from the input data and adapting accordingly.

Interior designing is a part of the design that focuses on creating aesthetically pleasing interiors of buildings and houses.

As unbelievable as it sounds, ML does play an important part in interior designing. When wanting to arrange something in a particular order (color-wise or other), the designer, instead of planning it out all by themselves, can simply put ML to use and get the desired result in less time. It also helps in giving a designer idea about layouts from previous datasets and predicting any possible roadblocks along the way.

The Downside of Machine Learning on Designers

  1. UI stands for User interface, while UX stands for user experience. If a machine starts programming the user interface, it leaves barely any room for a designer. This is because a machine with its data can more effectively address the problem.
  2. Machine learning, as we know, has the ability to gather data and provide speedy results. When this is inculcated in the graphic design world, it can easily replace the designers in certain aspects of the field.
    With the introduction of free online logo designing software, website builder software and so on, it has already started to become a designer's nightmare.

Also read: ML In Interior Design | Insights - Tooliqa

Tooliqa specializes in AI, Computer Vision and Deep Technology to help businesses simplify and automate their processes with our strong team of experts across various domains.

Want to know more on how AI can result in business process improvement? Let our experts guide you.

Reach out to us at business@tooli.qa.

FAQs

Quick queries for this insight

How can machine learning aid in design?
arrow down icon

Machine learning can help immensely in the design process. It can aid in decision making through efficient data processing and creation of appropriate algorithms. It can help reduce errors by comparing it with already known examples. It improves accuracy through model optimization.

What are the downsides on imbibing machine learning in design?
arrow down icon

Design is wholly a creative aspect which humans are known to excel in. But machine learning would be able to do a much better job at the same when the model is trained. So, designers would have to find a relevance in the coming times to avoid being obsolete.

Which are the various aspects of design where machine learning can be beneficial?
arrow down icon

Machine learning is trained through models and repeated iterations of data. It can help in graphic design - creating visuals based on the target group, UI/UX design - understanding the user's behavior and designing interfaces which the user can easily navigate through, product design - creating product renders, interior design - scanning interior spaces and recommending the appropriate design elements for the same.

Connect with our experts today for a free consultation.

Want to learn more on how computer vision, deep tech and 3D can make your business future proof?

Learn how Tooliqa can help you be future-ready.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Subscribe to Tooliqa

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Similar Insights

Built for Innovators

DICE
With advanced-tech offerings designed to handle challenges at scale, Tooliqa delivers solid infrastructure and solutioning which are built for to meet most difficult enterprise-level needs.​
Let's Work Together

Learn how Tooliqa can help you be future-ready with advanced tech solutions addressing your current challenges