Everybody can build AI solutions. That’s not for only developers.
Why no-code is the future of AI?
Building and solving problems without coding knowledge is really a game-changer.
No-code is significantly changing the world. The promise of no-code platforms is that they’ll make software development just as easy as using Word or PowerPoint so that the average business user can move projects forward without the extra cost (in money and time) of an engineering team. When we look closely at some no-code companies, you understand why I’m saying that. Webflow is a no-code website creation tool, and the valuation is $2B. Zapier is a no-code automation tool, and the valuation is $5B. These are just some samples and there are some other startups that we will hear about their success in a short time.
According to recent research from Gartner, 70% of new applications developed by organizations will use low-code or no-code technologies by 2025. None of this should be surprising. Skill shortages in the technology industry have been well documented, and in terms of application and platform development, the problem has become urgent. No-code/low-code technologies are healers of the development ecosystem.
The bottom line is that every business has become a software business pushing towards digital transformation. While software might be taking over the workplace, there isn’t an endless supply of developers. On the other side, companies realized the need to be faster than their competition, build and offer new digital applications, and improve existing applications with speed and agility. At this point, the importance of no-code platforms comes;
- Faster go-to-market.
- Increased customer satisfaction.
- More successful product development.
- Lower IT infrastructure cost.
How do no-code platforms affect AI development?
First of all, we need to open a new window here. The latest research showed us that %87 of AI applications never reach production. That’s a terrible number when we think about how much money waste every year. The latest decade is the rising of AI technologies. It was great to understand the data and create human-like decision mechanisms. But the speed also created a bottleneck to find talented people with domain expertise in AI. It’s the biggest problem of failure reason. The only way to destroy the gap is through no-code/low code platforms.
Before the deep dive, we need to understand the steps of AI application development. Natural language processing (NLP), Computer Vision, and Natural language understanding (NLU) are parts of the AI world. All of these approaches have the capability to solve real-world problems with minimum human effort (sometimes without humans). But the development of these technologies is not simple as their values.
For example, you will create a Computer Vision project to detect an object in a video stream. The steps are;
- Collecting the data and labeling them manually to teach the machine your selected object.
- Selecting a framework like Tensorflow, MXnet, Pytorch, etc.
- Training your modal and testing.
- Continuously improve the performance of the modal.
- Running on production with high speed (less than 100ms)
Cloud providers like Google Cloud, Azure, and AWS see the problem (and opportunity, of course) and start to offer some ready-to-use services for developers. But they have only limited features for fundamental cases and low customization skills. But it’s a signal for the future. You can train your model and serve it on Google Cloud without leaving it. The same thing goes for others too. Some startups like Voiceflow.com and Cameralyze.co offer end-to-end solutions, not only model creating or serving. They include ready-to-use integration and make a complete solution without writing code.
These tools help companies integrate custom AI solutions without causing a high investment.
