What is Low-Code & No-Code AI?

And Can You Take Advantage?

August 15, 2022
AI in IT Software, AI Tools

And Can You Take Advantage?

Not long ago, working in computing required extensive expertise. If you wanted to create a program or an application yourself, it was imperative that you could code. However, as the age of computing has continued to evolve, so has access to this ability. Today, and in the age of artificial intelligence, we have low-code and no-code options.

Coding is the writing of programming, it is the script of instructions that a computer follows to achieve a certain goal. But not all computers use the same scripts, otherwise known as programming languages. Examples of these languages are Python, Javascript, and Java. Expertise in these languages easily equates to a full-time job.

Complex programs and applications still require coding, but low-code and no-code systems allow users to build their own websites, design their own applications, and even deploy AI and machine learning without code.

Coding workstation by Farzad

As the name suggests, low-code refers to systems that require less coding, while no-code are systems without the need for code at all. Both approaches are popular and targeted towards professionals and business people. And they are used in artificial intelligence and machine learning models, outside of regular computing.

Additionally, both approaches are typically used to serve specific business purposes, like data classification, or the definition of a workflow. Low-code goes hand in hand with no-code, but these platforms are also frequently used by developers themselves. Often, these experienced programmers take advantage of these tools to make their jobs easier, by avoiding writing extra code. While no-code is most often used by managers in different industries and departments.

Ease of Use

Development is simplified. Without the need to write code, users can quickly learn how to bring their creations to life. As such, it gives the users more time to actually focus on determining what they want their development or algorithm to do.

Fast Development

Programming is a meticulous process that requires attention and persistence to achieve good results. But using platforms that allow for low-code and no-code development means that users can easily switch around pre-made components. This means that users can go through the process of trial and error more quickly, which in turn speeds up overall development.

Lower Costs

For the bottom line of any professional or business, the reduction of cost in any way can be truly beneficial. Using a no-code or low-code system for development can reduce time requirements and the necessity of heavy maintenance. Moreover, it can allow businesses to try out new ideas inexpensively, thereby increasing productivity.

Security

Given that the program or algorithm isn’t built by an outside AI engineer or consultant, the data is handled by the professional or business itself. In this case, any sensitive data is kept within the walls of the ultimate user. In this way, using no-code and low-code platforms is secure as it keeps third-party developers out. However, there is the issue of platform security. Some platforms may fail to design secure access protocols. And so users must take care to research the terms and conditions.

Lack of Customization

Despite the speed of low-code and no-code platforms, their use cases and functionalities are often limited. Given that most platforms are designed to address specific problems, it’s difficult to use them for creating more complex solutions.

Requires Training

Even if the creation of models, algorithms, or applications is made easy by low-code and no-code AI, the deployment still requires a certain degree of understanding. Such understanding needs to be taught to the management team, or the people that will mainly use the finished product.

By Joshua Golde

Google AutoML

A Google-backed platform that allows developers with limited ML expertise to train high-quality models specific to their business needs. The platform focuses on image and video annotation and labeling. As well as semantic text analysis and classification.

Create ML

An Apple-backed no-code platform that uses a Mac OS framework. It allows users to easily build ML models with an easy-to-use app interface and no code. The platform can train a variety of models, from image recognition to sentiment and regression analysis.

Levity

A no-code platform that allows users to train and build AI models. The platform focuses on image, text, and document classification. It enables users to train custom models on their use-case-specific data. Custom models also have a human-in-the-loop option, which means the model asks for input where it is unsure. Some use cases are automated data iteration, and classification of images, texts, and documents.

Obviously AI

A no-code AI platform that builds ML algorithms for data prediction. Users can take a bird’s-eye view of existing data, understand it and draw conclusions. The platform also suggests ready-made datasets, so you can test them out and get predictions right away. Some business-case usage would be personalisation of marketing campaigns, forecasting of company revenue, and supply chain optimisation.

SuperAnnotate

A leading platform designed to build the highest quality training datasets available for computer vision and natural language processing. This platform has advanced tools, like automation features, data curation, offline access, and integrated annotation services. It allows ML teams to build incredibly accurate datasets 3-5x faster.

In the end, low-code and no-code AI solutions have their advantages and disadvantages alike. Much like anything else. And their use might be the solution for some of your professional or business problems. If it is the case that you or your business requires a more tailored solution for a more complex problem, then do contact us at Sparkd.ai.

Work with Sparkd today for your AI needs.

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Author: Michelle Diaz

Photos: Unsplash
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