Why is Hybrid Low-code Development Trending？
How AI software can help
Did you know that AI doesn't always have to be complicated or expensive? By adopting hybrid low-code artificial intelligence tools, your team can leverage AI to solve specific problems and create value.
What is hybrid low-code development?
Hybrid low-code development is a software development process created from the concept of low-code development. Low-code development focuses on visual development and interface. It allows developers to complete an application with drag-and-drop features and a graphic user interface, minimizing the workload of hand-coding.
According to Havard Business Review, compared to traditional hand-coding, low-code development enables faster development. However, low-code development also has potential drawbacks, such as functional flexibility or shadow IT limitation. Thus, the concept of hybrid low-code development is created. The hybrid low-code development process balances the need to accelerate the development process and customize functionality. It preserves the critical idea of low-code: higher accessibility and shorter development time. At the same time, it prevents sacrificing the level of control by accommodating the graphic user interface and hand-coding environment.
Figure. 1 Comparsion of hybrid low-code, low-code, no-code and traditional hand coding
Benefits of using hybrid low-code development tool
According to Gartner's latest Magic Quadrant for Enterprise Low-Code Application Platforms, by 2023, over 50% of medium to large enterprises will have adopted a low-code development process to pursue higher productivity strategically. By implementing AI with hybrid low-code development, companies can:
1. Leverage the resources to create business efficiency
Hybrid low-code artificial intelligence tools can help companies leverage the data team, even a small one, to drive a big AI project and make a significant impact. A hybrid low-code artificial intelligence tool provides the team drag-drop features to deal with tedious and time-consuming issues, like environment configuration and software and hardware integration. As a result, the team can save time and focus on designing algorithms, pursuing better predictions, and being more productive.
As leveraging a small data team has been especially crucial in recent years, companies should seriously consider putting some effort into it. Based on Mastercard's AI strategy white paper published in 2021, the demand for qualified data scientists is far greater than supply in the job market, driving intense competition among companies to recruit talents. For instance, in SMEs, it is difficult to compete with internal enterprises and recruit sufficient talent. Under the circumstances, hybrid low-code artificial intelligence tools can be the choice to address the shortage of human resources.
2. Launch the AI-powered project quicker
A hybrid low-code artificial intelligence tool enables quicker AI development. In this hybrid development process, the team can integrate manual coding and flexibly adjust the algorithms, the project's core, while quickly finishing the rest of the work like environment configuration through the graphic user interface. Consequently, the team can shorten the development cycle and launch the AI-powered product or service faster without compromising the quality.
3. Scale-up artificial intelligence easily
Once a model is trained and tested, the team can automatically deploy the model on thousands of edge devices in one step with the hybrid low-code artificial intelligence tool. The team can also monitor the predictive results with the artificial intelligence tool and dynamically adjust and re-deploy the model. Based on the company's needs, deploying on the cloud is also supported.
In summary, hybrid low-code artificial intelligence tools make AI solutions accessible, flexible, and scalable while ensuring prediction quality. It also allows agile and dynamic adjustment according to the current needs. It is probably the best way for companies, especially SMEs, to start utilizing AI.
How to use hAIsten to build up successful AI projects?
Figure.2 AI software for quicker development
hAIsten provides the developers with an optimized AI infrastructure and development environment to build their deep neural networks and train the model without prior environment configuration. As traditional coding environments and graphic user interfaces are accommodated and integrated, the team can build their projects flexibly.
More importantly, hAIsten provides multiple built-in functions that accelerate the model training process through distributed training techniques. It means data scientists can experiment with more algorithms within a shorter time, which leads to quicker development. Once the model training is completed, the team can deploy it on a large scale by the built-in functions within a few steps. To leverage deep learning, hAIsten could be your partner (Learn more about AI software hAIsten).
｜About Author - Avalanche Computing｜
We provide a
low code AI software that leverages the power of multi-GPUs and rapidly speeds up the model training and model deployment for small or medium data teams. Within our AI software platform, dashboards for visualizing the status of all models and GPUs are also available.