As technology advances faster than ever, understanding emerging trends is vital to sustaining competitive advantages. Software 2.0 is one of those disruptive trends gaining traction in this new era.
It has revolutionized how we think about software programming, thus implicating organizations and lives.
What is Software 2.0?
Programmers give explicit instructions to a computer with the conventional Software 1.0. Meanwhile, Software 2.0 integrates the abstract concept of neural networks.
Instead of writing steps in the usual programming languages such as Python, we can feed labelled data into programs and train them to learn and perform as expected.
Software 2.0 comprises machine learning operations (MLOps) and DataOps. Neural networks test, repeat and diagnose the most efficient program to achieve the desired goal using these technologies.
Benefits of Software 2.0
By maximizing the full potential of Software 2.0, organizations can implement codes more effortlessly, efficiently, and intuitively.
Leveraging artificial intelligence (AI), routine programming work can be automated using low-code methods. Programmers will be freed from mundane tasks – providing them with more time to solve more complex problems or produce more creative work.
Furthermore, we can overcome the complexities surrounding AI models and other technical applications. We will no longer require high technical expertise to use several types of software.
Other possible applications of Software 2.0 include the following:
- Autonomous self-driving vehicles
- Entertainment (such as Metaflow by Netflix)
- Risk management systems
- AI-driven applications
The Role of Programmers
If programmers no longer have to code, what will they do? Will machines replace engineers?
The answer is no.
Instead of writing programs, software engineers will focus on data accumulation, visualization, and cleaning. Approaches to data will change, and mastering DataOps will be crucial in gaining a competitive edge.
In addition, Software 2.0 still has some probability of failure, despite reaching high levels of accuracy.
Software engineers can reduce this unpredictability. They can monitor and help the system to increase its accuracy rates. Thus, programmers will play crucial roles in achieving a system accuracy rate closer to 100%.
Visualizing the future, machines and engineers will support one another, offer refreshing perspectives and create new experiences. Such collaborations across multiple industries will inevitably lead to more effective solutions.
With better solutions, we lead better lives.
Written by: Shermine Ong