Ai/ml Integration With Low Code And No Code

By Author: vishal Rustagi
Total Articles: 13
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Several well-regarded institutions are working tirelessly to integrate low code/no code platforms with Artificial Intelligence and Machine Learning. Google, H2O, MIT, and others. The integration of two core technologies will make it easy to use AI for everyday purposes and micro-applications.

In this article, we’ll explore the integration of AI and ML with low-code and no-code platforms. We will also overview five approaches to AI/ML integration with low-code and no-code. And finally, evaluate the future of such technologies.

AI and ML and Low Code/No Code
Low-code and no-code platforms are becoming increasingly popular due to their ease of use, speed, and ability to increase productivity.

Codeless development is a rising industry, and AI and ML integration can truly democratize the market in favor of micro-development. The current market cap of $22 Billion as of 2022 will expand to $32 Billion within the next year(2024) with a cumulative CAGR of 26%.

AI and ML could make these new-gen development platforms at par with their coded counterparts. Some of the latest innovations with the integration ...
... of AI and ML with low-code and no-code systems are:

Google AutoML was designed as a no-code platform for Android and iOS developers. The platform allows anyone to deploy ML models for their own use without any expertise. It has an API that can scan faces, label images, and much more.

H2O AutoML: A Low-Code ML platform can help users deploy several ML algorithms such as gradient descent, linear regression, and others. It automates the process of building multiple models at once and deploying them together.

MIT has a Course to teach no-code AI/ML. This system will focus more on building customized data solutions.

ObviouslyAI is yet another no-code platform that can make predictions based on past data without the need for any coding.

The Need for AI/ML Integration with Low Code and No Code
Improved efficiency and productivity: No-code platforms are well known for their time-saving. With AI and ML, these platforms can automate repetitive tasks and save time for other essential activities.
Improved decision-making: These can provide real-time insights for corporate leaders such as C-suite executives. At the same time, any sensitive information will remain safe in their hands.
Enhanced user experience: It can help everyone build customized recommendations without exposing their preferences to others. By doing so, their privacy will remain in their own control.
Reduced development time: Integrating AI and ML technologies into no-code platforms can further accelerate development and reduce the time to market.
Increased accessibility: Anyone who needs AI and ML in their daily lives can use them without exposing their personal information or any sensitive data. This tool is crucial for primary researchers, academics, analytics professionals, etc.
Cost savings: Since the end users can build their own applications, the development cost will be much lower than earlier.