How Deep Learning Represents A New Paradigm In Software Development

How Deep Learning Represents A New Paradigm In Software Development

Deep Learning is the domain of Artificial Intelligence that revolves around neural networks. That is to say, it is the part of Artificial Intelligence based on neurons (to act more like our brain). Using algorithms, we can replicate some functionality of neurons and brain functions. But what is the impact of such a complex field on software development? Some are calling it the next version of programming or “Software 2.0”. But, this isn’t true as it is just another buzzword trend. According to AI developers, it definitely represents a shift in coding but it is not some massive upgrade. Using deep learning for software development is another way of coding and not an upgrade. With earlier coding languages like Python, C, C++, coding development followed by deployment. In case of neural networks, it has a much more interesting approach. In the case of deep learning and neural networks, we teach the framework to the neural network. By showing it examples of what is correct and what isn’t, a neural net learns. This is the shift from conventional coding. Instead of doing everything ourselves, we teach the neural networks by using a few lines of code and examples. As we know, the greater the amount of data you feed a neural network, the more it learns. Of course, the data has to be labeled and cleaned earlier.

Why Deep Learning
Correlation between neural networks and amount of data
Image source: https://machinelearningmastery.com/what-is-deep-learning

Coming back to software development, neural networks can create machines that learn. Tesla’s AI director Andrej Karpathy also enforces that DL is the new software development method. This method is here to stay and will replace handwritten code. This is the reason why Deep Learning Development is being thrown around as “software 2.0”. It is not like it will replace entire areas of coding and development. The previous “software 1.0” has several advantages which neural networks cannot really overlook. Fixing bugs, regular maintenance, long term support are not addressed by neural networks. This traditional “software 1.0” functions on logical and binary operations. Neural networks use complexities and functions not possible at such a small scale. Also, it is not like the neural network’s process is completely automated. Even that requires coding but much less than handwritten. Inputting data and tweaking data sets are required besides a few lines of code.

Artificial Intelligence is here to help
Neural networks in the brain
Image source: https://paulvanderlaken.com/2017/10/16/neural-networks-101

 

Conclusion:

The Deep Learning frameworks and techniques do not completely get rid of coding. Software development in this area is underway by the “software 2.0” methods. Soon, companies like Amazon, Uber and Google will be using this method. For this type of software development, modeling will not focus on function design. Instead, it will be more oriented on feeding them data and manipulating these models. Data scientists and AI developers worldwide will be working on “software 2.0”. As a result of this development, data scientists will not have to model functions. Instead they can feed the data and tune the model with tools. In its own way, DL software development will have its advantages. Traditional handwritten coding will have its own until that isn’t automated. You can learn Deep Learning in our institutes. Deep Learning & Software Development are also related and one can look for more insight here as well.

 

Resources:

https://analyticsindiamag.com/does-deep-learning-represent-a-new-paradigm-in-software-development/

 

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