History of No Code and No Code AI

In this post, I want to talk about the history of No Code and No Code AI, how they were started and their evolution in the current day. To understand the history of No Code AI, we first need to understand the history of programming and the history of No Code programming tools.?

We begin by understanding how the programming was started and then look at the present day programming. The first known programmer is believed to be Lady Ada Lovelace who created the first program (or algorithm) almost 200 years ago to be used on the Analytical Engine (which was created by Charles Babbage). This was somewhere in the 1840s where the Analytical Engine was made of metal gears and was able to execute decision statements (if-else commands) and store information.?

In the 1940s the first programmable digital computer was developed which was called the ENIAC (or full Electronic Numerical Integrator and Computer) and was completed in 1945. This was a massive 30-ton computer and the programmers primary responsibility for this computer was to find and fix bugs. ENIAC could be programmed to execute loops, branches and subroutines but the programming used physical switches making it very complex to write even simple programs onto this machine.

After World War II, somewhere in the 1950s new programming languages were developed where people could write code using the English language and a compiler was used to turn the code into binary so that the computer could understand and execute the code. Short Code developed by John Mauchly was one of the first high-level programming languages to be developed for electronic computers. The first programmed language developed for non technical users is FLOW-MATIC which used around 30 verbs to describe the program in plain English language.

In the 1960s came COBOL (or Common Business-Oriented Language) which is a high level programming language for business applications and could run on computers built by different manufacturers.? It is still in use by some of the financial and business applications today. Many of the early programming languages were designed to be used by non-technical users. However from the 1960s to 1990s, the programming languages became more technical and required specific knowledge. As the complexity of digital products increased, so did the complexity of the programming languages. One of the technical languages invented in 1972 was “C” which was difficult to learn and required a huge amount of technical knowledge.

C gave birth and inspired many other technical languages such as C++, C#,? Python, Java, JavaScript, Perl, PHP, Verilog, etc. These coding languages are still in use today and are used to develop the majority of the applications by different companies all over the world. This gave rise to many programmer related jobs and people having specific technical skills became high in demand for jobs in the 20th century.

From the 1960s till 2010s most of the programming was done by technical people and the technical languages like “C” ruled this space. However, from the beginning of 2010s the “low-code” tools started coming to the market with the term “low-code” referring to the platforms that enable rapid development of applications. These tools required minimum technical knowledge and led to exponentially speeds up in development and maintenance of the applications.

No Code tools soon started after the “low-code” tools and the No Code tools could be used by any business user with no requirement of technical knowledge. Instead of writing code, the non-technical user can use the auto generated components and drag-and-drop features to achieve the required functionality. The users just need to onboard the tool in their organizations and understand how to use the tool to achieve the required outcome for their business. For small to medium enterprises (SMEs) no-code tools enabled them to use the latest technology and do amazing things with limited resources. For large enterprises no-code tools enabled them to develop and ship new features and applications at an exponential speed.

The no-code tools are democratizing technology and with no-code AI the skill gap is minimized and the power of AI is given in the hands of everyone. No-code AI tools became popular in the 2015s and are now used by many organizations around the world to add AI into their applications. With no-code machine learning, users can quickly experiment with their data and quickly build appropriate supervised and unsupervised learning models without the requirement of coding the machine learning algorithm from scratch.?

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