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<p class="text-box-left">Have you ever wondered about the fascination with creating lifelike entities from inanimate objects?</p>
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<p class="text-box-right">Absolutely, the concept of giving life or intelligence to non-living things has intrigued humanity for ages.</p>
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<p class="text-box-left">It's interesting how the origins of modern AI can be traced back to classical philosophers' attempts to understand human thinking as a symbolic system.</p>
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<p class="text-box-right">True, but the term "artificial intelligence" itself wasn't coined until a conference in 1956 at Dartmouth College.</p>
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<p class="text-box-left">That's a significant milestone. So, what's this article about?</p>
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<p class="text-box-right">This article delves into how AI is actually supporting software development. It's a fascinating journey that begins with the historical context of AI's origins.</p>
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<p class="text-box-left">Sounds like a great read. Let's explore how AI has evolved and how it's shaping the field of software development.</p>
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<h2>The Birth of Artificial Intelligence (AI)</h2>
<p><br>After AI was founded and coined at that gathering in Hannover, there was optimism that the innovation would pick up and rapidly develop. But this was not to be the case. MIT cognitive scientist Marvin Minsky, who attended that conference, was optimistic.</p>
<blockquote>
<p>&ldquo;Within a generation [...] the problem of creating 'artificial intelligence will substantially be solved," Minsky is quoted as saying in the book "AI: The Tumultuous Search for Artificial Intelligence.&rdquo;</p>
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<p>There would be a lot of criticism to come for AI&rsquo;s progress. Government interest fell off rapidly between 1974 to 1980, and that period became known as the &ldquo;AI winter.&rdquo; Eventually, the field came back to life in the late 1980s, with the British government funding it partly to compete with the Japanese. The field experienced, again, another great winter from 1987 to 1993.</p>
<p>Research returned again in 1997 with a bang. The world witnessed IBM&rsquo;s Deep Blue beat a chess champion when the computer defeated Russian grandmaster Garry Kasparov. In 2011, the question-answering system, Watson, won the quiz show Jeopardy!, beating reigning champions Brad Rutter and Ken Jennings.</p>
<p><img src="https://api.luida.dev.crane-a.co/storage/articles/August2023/Picture102.png" alt="" width="1089" height="613"></p>
<h2>A Brief History On Software</h2>
<p>Software is the interface between computer systems and the users of computer systems. It is a series of programming instructions and data that instructs the computer on executing various tasks. Today, Software development has seen instructions written in a higher-level language. It is easier to use for human programmers and then converted into low-level machine code that the computer can directly understand.&nbsp;</p>
<p>The computer scientist Tom Kilburn wrote the first piece of software at the University of Manchester in England. The software ran at 11 a.m. on June 21, 1948. Kilburn had built one of the earliest computers, the Manchester Small-Scale Experimental Machine (known as Baby), with his colleague Freddie Williams.</p>
<p>Softwares is everywhere today, from obvious devices like smartphones to completely unexpected places like nuclear submarines. Languages have evolved through that time, although some, like C and Cobol, have lent themselves to time. Others like Java and Python are newer and more ubiquitous, but the gist is that you hardly go a day without encountering software today.</p>
<p><img src="https://api.luida.dev.crane-a.co/storage/articles/August2023/Picture113.png" alt="" width="976" height="732"></p>
<h2>Important Things to Know About Software Development</h2>
<p>Software development entails the process of building software, from its conceptual stage to execution. This is a careful, gradual process called a Software development life cycle (SDLC). Software developers use coding languages, the most popular being JavaScript, C, and C++ when developing their software.&nbsp;</p>
<p>Typically, the Software development lifecycle covers the following stages:&nbsp;</p>
<ul>
<li>&nbsp;Requirement analysis</li>
<li>&nbsp;Planning</li>
<li>&nbsp;Software design, such as architectural design</li>
<li>&nbsp;Software development</li>
<li>&nbsp;Testing</li>
<li>&nbsp;Deployment</li>
</ul>
<p>SDLC has evolved in varying, flexible forms to deal with complex business systems development that require lots of data processing and analysis. The Software development life cycle (SDLC) goal is to provide proficient software development within a predetermined timeline and budget. This means each software&rsquo;s progress is unique despite following the same development process.</p>
<p>Throughout history, the software development life cycle changed. The most utilized software development algorithm in the last century was the Waterfall framework. And now, a shift has occurred since the 90s that&rsquo;s allowed for a transition from Waterfall to the Agile methodology.</p>
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<h2>Software and Artificial Intelligence</h2>
<p>As we have established, the development of Artificial Intelligence is in its golden years. We have never been able to blend machines and the human mind so seamlessly in the history of innovation. It then goes without saying that we would try to make a mix of Artificial Intelligence with the other equally important computing innovation, software.</p>
<p>The main goal of artificial intelligence is to optimize an existing program or process. AI merging with software development means it can, for example, take over dull and repetitive tasks, giving the developers more free time for other complex problems to solve. This is just one of the numerous ways AI optimizes software development.&nbsp;</p>
<p>It has been purported, rather expectedly, that AI would replace software engineers. However, numerous industry experts have asserted that this won&rsquo;t be the case; artificial intelligence&rsquo;s automation ability is expected to optimize the developer&rsquo;s efficiency. So how exactly does AI aid software development?&nbsp;</p>
<h3>&nbsp;Changing Developers Roles:</h3>
<p>Artificial Intelligence can and has been designed to take over mundane and repetitive tasks. Development time is reduced considerably. The gaps created this way makes room for more software to be created and to hire more developers for these roles.&nbsp;</p>
<h3>&nbsp;Better Planning and Estimation of Budget:</h3>
<p>&nbsp;Software development companies plan and estimate every step before starting a project. They do not commence on any project without many elements in place. Due to this, software development takes time and a chunk of money, depending on the project scope.</p>
<p>However, with the help of AI, the project's estimation of time and cost is assessed quicker. AI gathers previous projects and data and then predicts the outcome and overall cost of the current project. This way, organizations can decide whether the project is worth pursuing at all or not.</p>
<p>AI tools for planning can predict outcomes when new requirements are introduced into its system, all but canceling out potential human error. AI can also help companies see if they are on track with their budget and plans.</p>
<h3>Manages Bugs and Errors:&nbsp;</h3>
<p>Software errors are common. When developers are overwhelmed with tasks, they make mistakes and suffer oversight. This is generally not a problem.</p>
<p>Developers usually cross-check the software design looking for issues they might have overlooked. However, the catch is that this process takes time and can also, ironically, lead to errors. It is a catch-22 of sorts.</p>
<p>Adding artificial intelligence to the mix optimizes it because it searches for errors and hastens the process quicker than it would have taken manually. Also, when AI detects any error, it fixes the bug automatically. Such a process cuts down work time exponentially.</p>
<p>AI tools can also predict future errors by simply looking through databases. Once informed, the AI tool then passes on this knowledge of how to avoid them in future projects to developers.</p>
<h3>Faster Coding:&nbsp;</h3>
<p>AI-enabled software tools (Tara and Kite) can help reduce developers' coding time. AI suggests optimized code or completes some of the code while developers create it. They work no differently from how autocorrect or auto-suggestion works on a mobile phone. These tools also educate amateur developers, and they can learn how to code in less time than before.</p>
<p><img src="https://api.luida.dev.crane-a.co/storage/articles/August2023/Picture13.png" alt="" width="1379" height="918"></p>
<h2>AI-Powered Tools for Software Development</h2>
<p>Various software developers now utilize AI to assist the development process. We have also noted the advantages that AI brings to that development process. If you are curious about what AI tools they use, here are some of them.</p>
<ul>
<li>Google ML Kit &ndash; This tool is for mobile applications and optimization. It is an easy-to-use and powerful package with the advantage of ML expertise powered by Google. It helps customize models according to the project&rsquo;s specifications.</li>
<li>TensorFlow &ndash; It helps developers deploy ML-enabled applications with its end-to-end open-source platform. It aids researchers with its comprehensive tools and libraries, and community resources for faster development.</li>
<li>MxNet &ndash; It is a tool for deep learning with a rich ecosystem of libraries and tools. It is an open-source framework ideal for all types of developers. It provides distributed training and deep integration with other languages such as Python, C++, and others.&nbsp;</li>
<li>Infosys Nia &ndash; It helps developers to transition from artificial intelligence experimentation to production. It is a good tool for decision-making as it derives insights from the project&rsquo;s documentation. It manages siloed data assets generated from legacy systems.</li>
<li>H2O &ndash; It is a framework with autoML functionality. It runs algorithms and hyperparameters to produce the most optimal model. It supports statistical and machine learning algorithms to create accurate predictions.</li>
</ul>
<h2>&nbsp;<br>Conclusion</h2>
<p>Artificial Intelligence uses various techniques, tools, and practices to build better software. It is, doubtlessly, the future of software development, as ordinary, repetitive tasks now belong to AI. Programmers will only focus on more relevant tasks.</p>
<p>AI provides benefits, but there are critical limitations. For example, it is wired to focus on a simple task, and design limitations mean it lacks the human ability to fully comprehend how certain complex systems work. This creates a greater challenge in developing an integrated platform without algorithmic biases.</p>
<p>This is one of the critical reasons it cannot completely replace human involvement in software development. Artificial intelligence cannot decide which is right or wrong. However, it can aid humans who can design optimal software models.</p>

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