Artificial Intelligence (AI) has made much progress over the past decade, and these advances have everyone wondering how far it can go.
Nowadays, Generative AI systems can build images in a myriad of different styles with just text, with DALL·E 2, Midjourney, Stability, and Figma's Ghost Artist as a few examples.
What’s more, Neural Networks like GPT3 can translate, write, answer questions, and code! Of course, this development raises concerns about AI taking over human jobs.
So, how have AI models changed Software Development? Will human engineers be a thing of the past? Let’s take a look at where AI-driven Software Development stands today.
We’ll also review what experts believe and expect the future of AI will bring. Let’s go!
How Far Has Artificial Intelligence Come?
AI has an increasingly pivotal role in our lives, from speech recognition to smart assistants and predictive analytics. It has even made strides in breast cancer diagnostics!
On a more mundane level, you can see Artificial Intelligence when using a chatbot to get help from your bank or any other service. That’s also an AI-driven solution!
Moreover, if you have a smart house, you can enable it to control lights and air conditioning or even send you a notification if you’re about to run out of something in your fridge.
All these breakthroughs beg the question: will machines replace humans? The most sensible and probable answer to this question is no.
As other techs have done throughout history, AI will replace some jobs, yet it will also allow the existence of new ones while enhancing what humans can do.
The popularity of AI will increase as its training costs decrease. As a result, some studies even say that, by 2050, AI will replace 20% of routine jobs.
Yet, this does not mean we will suddenly have a significant rise in unemployment! As in the past, the workforce will retrain to focus on more specific tasks.
Of course, some have a bleaker outlook on the future, as they believe AI will cause us to become over-reliant on machines.
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The Role of AI in Software Development
Regarding the Software Development Lifecycle, AI has proven beneficial in assisting developers with routine tasks.
Some AI tools check code to detect errors and bugs and reduce risk when deploying upgrades, leading to more secure systems and an increase in productivity.
In addition to its application in coding and debugging, AI can also help development teams ease data-driven approaches for more creative tasks such as UX/UI Design.
Below, we'll take a closer look at what AI has brought to the Software Development table.
Artificial Intelligence (AI) Uses in Software Development
1. AI for Software Requirements
Gathering and managing requirements for the Software Development process can be cumbersome.
Yet, some tools allow for cutting human intervention to save time and effort. Great examples of these promising instruments are IBM’s Watson and Microsoft’s Deepcoder AI.
2. AI for Software UX UI Design
By harnessing AI for UX Design, teams can analyze data faster, provide advanced localization, and organize design systems and components.
Likewise, with a data-driven advantage, companies can iterate designs to provide more personalized experiences for each type of user within their audiences.
Examples of AI UXUI tools start with Midjourney, the AI art generator that harnesses Machine Learning to build prompt-text-based images.
Midjourney is available as an interactive "bot" on Discord, and it's particularly useful for creating unique and realistic artwork and images with just a few words.
Likewise, Adobe Sensei powers many programs of the Adobe Creative Cloud, like Photoshop, Lightroom, and Premiere Pro.
Adobe Sensei analyzes images and provides suggestions for quick edits without the need to hop into Photoshop, using a combination of signals to make suggestions.
3. AI for Sofware Development Coding
Several examples of AI-driven development tools for coding include a code generator with an "autocomplete" feature to boost productivity and improve code accuracy.
A code generator is a software tool that automates code generation based on input data. Moreover, it translates an abstract syntax tree into machine-dependent executable code.
GitHub Copilot is a key player in AI-based code generators. The product acts as an AI pair programmer, helping developers code more quickly and accurately.
What’s more, GitHub Copilot seamlessly integrates with Visual Studio Code, Visual Studio, Vim, Neovim, and the JetBrains suite of IDEs to provide devs with smart suggestions.
Another rising tool is OpenAI Codex, which is able to understand and generate code based on natural language inputs.
This OpenAI GPT-3 model descendant allows teams to predict lines and offers context-aware suggestions for completing statements, functions, and more.
It's particularly good at Natural Language Processing to code and supports over a dozen languages, including Python, JavaScript, PHP, Swift, TypeScript, SQL, and even Shell.
4. AI for Software Development Testing
We all know that manual testing can be pretty time-consuming within the Software Development cycle.
Powered by Artificial Intelligence, devs and teams can ease the AI driven development process with quick testing cases, code reviews, and regression testing.
Some existing testing tools that harness AI include Appvance, Testim, and Diffblue.
5. AI for Software Development Debugging
Predictive debugging tools help devs locate and analyze code bugs by providing increased visibility, which makes them particularly useful in ML models to optimize performance.
As for coding, predictive debugging tools can help identify and analyze issues, providing insights into performance comparisons, feature distributions, and other metrics.
A great example of AI for debugging is DrWhy, the R package that provides a framework for explaining the output of statistical models.
The package integrates various statistical models, like linear regression, logistic regression, decision trees, and more, and it's particularly useful for identifying model prediction factors.
Another instance of AI-based debugging is Resharper— a VS extension for .NET devs that analyzes quality, eliminates errors, safely changes code, and ensures standards compliance.
ReSharper is an intelligent add-in to Visual Studio with rich features, including intelligent coding assistance, on-the-fly error highlighting, and quick error correction.
Nonetheless, things can be not-so-shiny: teams should consider that these tools can also deliver false positives.
Real Examples of Artificial Intelligence in Software Development
We've seen how AI-assisted development is changing the game in the realm of Software Development— let's turn to some more real-life examples of AI-powered products.
The first example, of course, is GPT3, the third-generation Machine-Learning system and text-generating Neural Network created by OpenAI.
This system uses an algorithm based on 45TB of data with 175 billion ML parameters to produce human-like text— ten times larger than any other model.
Though imperfect, the GPT 3 system is expected to take over mundane tasks and eventually help cut bottlenecks in software production.
Our next example is DeepCoder AI. Built by Microsoft and the University of Cambridge, the system is able to learn from millions of open-source programs.
This Neural Network predicts program properties through a Deep Learning model to solve a variety of potential issues and generate code.
While DeepCoder's capabilities are currently limited, the system is expected to be able to automate code generation considerably in a handful of years.
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The Future of AI Driven Development
AI-powered solutions tools have already begun revolutionizing how we conceive and build applications - making it possible to create faster and safer solutions.
This tech possibility already provides developers, Project Managers, and UX UI Designers with more efficient ways to create better applications and systems that serve their users.
Moreover, as AI driven development tools become more sophisticated and powerful in the coming years, more opportunities to harness their power will arise!
Teams will even be able to create software using less code (Low-Code Development Models) or maybe even no coding (No-Code Development Models)!
But how drastic will these paradigm shifts be? Will AI completely replace Software Developers and Software Engineering? Let's explore what the future may bring.
Can AI take over Software Development?
Opinions on this topic are somewhat divided. According to Andrej Karpathy, for instance, integrating AI will bring a new age of development called Software 2.0.
From this stand, the software will be more abstract and won't need human involvement, so instead of code, programmers will find, curate, and make training data-driven decisions.
Some experts likewise trust that AI will empower Software Developers instead of replacing them. This POV focuses on AI taking over more repetitive tasks.
The most likely scenario is that, while the role of programmers will shift as they have done over the last few years, it's unlikely that AI will replace human work anytime soon.
Instead, it will most likely become an influential tool for developers to gather knowledge and optimize procedures.
What are some AI Trends for Software Developers?
If you’re worried about staying relevant as AI evolves, there are some skills you can work on. Developers skilled in math, statistics, and security standards can benefit from AI projects!
Big Data, Machine Learning, Data Science, Natural Language Processing (NLP), and LLMs are also gaining momentum. There’s also training data, data mining and cognitive computing.
Don't worry; you don't need to become an expert in all these fields! Yet, general knowledge will be helpful, and specializing in a specific area will prove valuable.
Software Development vs Artificial Intelligence vs Cyber Security
Should I study Software Development, AI, or Cyber Security? While we can't tell you which option is better, it's essential to consider a few elements:
Software Development favors creative and innovative people, as devs are often comfortable working both on teams and on their own and tend not to be afraid of hands-on approaches.
Artificial intelligence revolves mainly around data, so skills in data engineering and exploratory data analysis are required.
People better suited for this field don't only love data— they have excellent communication and interpersonal skills! They're also often creative and have good problem-solving skills.
Finally, cybersecurity also requires excellent communication skills, yet it also needs strengths like high resistance to anxiety and a passion for puzzle-solving.
Conclusion
We'll leave the theory of machines taking over to science fiction writers for now.
AI has brought a wide range of benefits to the dynamic landscape of the Software Development Industry.
We can say that, over the following decades, AI will focus on increasing productivity and helping programmers with repetitive and time-consuming tasks.
The future of Artificial Intelligence Software Development is bound to change and adjust as technology evolves, and we are looking forward to seeing what the future brings!
