Gen AI for Software Engineers
Let's talk about Generative AI, or Gen AI for short! It's like a super smart machine that can make all sorts of new stuff, like stories, pictures, music, and videos. But how did it come about? Well, scientists have been working on this for a while, teaching computers to learn from tons of examples of existing content. By doing this, the machines learn how to make new things that look and sound just like the stuff they've seen before.
So, what can Gen AI do?
Lots of things! It can help writers come up with ideas or even write entire stories. Artists can use it to make cool new designs or realistic pictures. Scientists might use it to simulate experiments or design new materials. Even on social media, it can show you stuff you're interested in. But, there are some things we need to be careful about. Gen AI might pick up biases from the stuff it learns from, and sometimes it can make things that aren't true. Still, Generative AI is an exciting technology that's changing how we create and enjoy content. As it gets even better, who knows what amazing things it'll come up with next!
In the world of AI, there are some cool tools to help us out. One of them is Devin AI, which is still being worked on, but people think it could be really powerful. Then there's GitHub Copilot, made by Microsoft and GitHub. It's for programmers and helps them write code faster by giving suggestions. Another tool is AWS Whisper from Amazon. It's great at turning spoken words into written text, which is handy for things like taking notes during meetings or adding captions to videos. Each tool is good at what it does, but which one is best depends on what you need it for. If Devin AI becomes a reality, it could be a big deal in lots of areas. If you're a coder, GitHub Copilot is super helpful, and for dealing with audio, AWS Whisper is fast and accurate. So, pick the one that fits your needs the best!
Meet Devin AI
The world's first AI Software Engineer has been introduced by a US-based AI lab. Claims are made by the creators of Devin AI that practical engineering interviews can be passed by it. It is stated by Cognition that tasks for US-based freelancing platforms and Upwork jobs have been completed. Devin is characterized as tireless, a skilled teammate, and always striving to complete tasks independently. With Devin, even more interesting problems can now be solved by engineers.
What is Devin?
Devin is a super smart computer program that has been built by Cognition. Devin will be utilized as an intelligent assistant for software engineers. In simple terms, the ability to write code, build websites, deploy those websites, and even create software is possessed by Devin. If humans and Devin are brought together, human jobs can be made easier. The uniqueness and specialty of Devin lie in its ability to solve difficult problems and think. It learns from its mistakes and improves over time. Additionally, tools needed by software engineers, such as writing code and browsing the internet, have been mastered by Devin. Devin has already been tested against other AI programs, with excellent performance observed. In comparison tests, 14 out of 100 problems have been solved by it. After testing, tasks on freelancing platforms and upwork jobs have also been completed by Devin. Errors are also fixed by Devin. Devin can be considered a very smart assistant that will help engineers improve and speed up their work. Not only is code written by Devin AI, but also the entire development process is managed and many software applications are released, which cannot be done even by big names like Gemini and ChatGPT.
How does Devin Work?
Such power is possessed by Devin that advanced artificial intelligence algorithms can be understood by it and all tasks related to software engineers can be completed. When a prompt or instructions are given to Devin, they are easily understood it, and its massive database of knowledge is utilized to solve problems, design websites, and develop software. The ability to think and solve difficult tasks is possessed by Devin. The tasks assigned to it are completed, and its mistakes are corrected over time. Devin also has its tools, such as its own code editor and web browser, which assist it in completing tasks from start to finish. New technologies are understood by it, and challenges faced by engineers can also be tackled by it. Additionally, its own AI models can be generated by it, and besides working alongside engineers in the industry, updates are provided and suggestions for design choices are offered it.
Devin impacts software jobs
The software job market has also been significantly impacted by the entry of Devin. Now, it will be assessed whether it is turned into a job killer or simply utilized as an AI tool, or if it is perceived as a blessing for techies who can benefit from it. According to Cognition, Devin is seen as a smart assistant that will simplify the job of software engineers.
Software programming has been impacted to some extent by the emergence of generative AI tools like GitHub Copilot, but Devin has taken it to another level. Software projects can be handled independently with ease by Devin, code can be written, bugs can be fixed, and tasks can be executed. However, Devin can also work as an assistant, but it will never be seen as a competitor. Advice has been given by Abhimanyu Saxena, co-founder of Scaler, to software engineers to embrace these tools and gain expertise while using them, rather than considering them as competitors. It has also been stated that these tools have been well-received as developer companions, and even individuals from non-technical backgrounds can easily build applications. Devin is only a part of software development and can never be replaced by software engineers.
While the findings may suggest some relief, it's important to note that complete forgiveness is not guaranteed. The continued development and use of AI are still happening. We're not sure yet about the bigger effects on jobs, income, and fairness in society. We're just starting to understand how these technologies might change our work and society.
The graph titled "Real World Software Engineering Performance (SWE-bench)" compares various AI models' performance on software tasks. It includes models like Devin, Claude 2, SWE-Llama (in two versions), GPT-4, and ChatGPT 3.5. The graph measures the percentage of issues each AI model can resolve, with Devin AI appearing to outperform the others in fixing software problems without human assistance. This suggests that Devin AI might be quicker at addressing software issues independently. However, it's important to consider the limitations of the test when evaluating Devin AI's overall effectiveness.
GitHub Copilot
GitHub Copilot is an AI programmer that facilitates coding in natural language. It is utilized in editors and programming languages. When Copilot is utilized, suggestions are provided for individual lines of code and even entire functions. However, much more can be done by it, as detailed below. Some features of GitHub Copilot may require GitHub Copilot Lab, which is a separate extension for VS Code, for experimental applications. These experimental features are often incorporated into the official product.
How can coding be made easier and faster by GitHub Copilot? There are some special tricks here that can be used with Copilot.
Starting with GitHub Copilot makes programming easier. Autocomplete suggestions are provided just by starting typing, and parts of the existing code are utilized by these suggestions. For example, if a repeated pattern such as the CQRS pattern is used in your code, those patterns and practices are recognized and identified by Copilot, and the code generated will match what you're working on. To achieve better results with Copilot, it is necessary to provide it with open text. The entire codebase cannot be utilized by Copilot, but existing files and other open tabs can be read by it. Prompting GitHub Copilot for suggestions is not required; instead, everyday language can be used to convey what is wanted. For example, a prompt like "Write a RegEx string to validate phone numbers" can be given to Copilot so that the actual code for validating phone numbers can be generated by it. To fulfill this requirement, the code will need to be tested and verified.
Many human languages are understood by Copilot, meaning that natural language does not have to be in English. This is helpful for developers who are not native English speakers. Sometimes, code understanding can be challenging, especially for newcomers to a project or when dealing with unfamiliar code. But do not worry—GitHub Copilot is here to assist you! With the "Explain the Code" feature in GitHub Copilot Lab, you can highlight any block of code and ask Copilot to explain it to you in simple terms. Whether you want an explanation like a senior developer talking to a newbie or just a basic breakdown, Copilot has got you covered. It's like having a helpful coding buddy right at your fingertips!
The translation of your code from one programming language to another programming language is the second Copilot Lab feature. These translations are not always perfect, and it is necessary to thoroughly check them. However, this can be a good starting point for converting a piece of code into a different language.
Mistakes:
The biggest disadvantage of Copilot being an AI is that it is not always accurate. For example, the code generated may be insecure, reference outdated APIs, or sometimes not work at all. This is especially true if a less common programming language is being used. The fact that errors are being given by GitHub Copilot does not necessarily mean it should not be used. In other words, everything can be reviewed and tested on your own.
To use GitHub Copilot and enjoy its advantages, you need to pay for it. For individuals, it costs $10 each month or $100 for a whole year after a free trial of 30 days. For businesses, it's $19 per user every month. Also GitHub Copilot can help you learn new things. For instance, when you see what Copilot suggests, you can learn about new features in a programming language, different ways to write code or fresh ideas for solving problems. If you use the translate feature, you can practice a programming language you're not very familiar with. Also, by observing how GitHub Copilot understands your requests, you can discover new ways to achieve your goals. And if you're stuck on something in the code, you can ask Copilot to explain it to you
At Emergent Software, we've embraced AI technology to boost our productivity. Our whole development team uses GitHub Copilot regularly. For instance, Zach Green, one of our Senior Software Architects, uses Copilot to create database schemas and generate code for tasks like defining foreign keys and indexes. He also uses it for tasks like creating views, temporary tables, and user-defined table types or selecting columns from tables. Copilot is handy for Zach when he needs to make unit converters to switch between metric and imperial measurements. We believe AI like Copilot isn't a threat to tech jobs; instead, it helps us work faster and cheaper, allowing us to develop more software than ever.
GitHub Copilot assists coders by analyzing their code and suggesting what to write next. It examines the programming language and other components of the code to provide suggestions such as new lines of code or complete functions. The coder can then choose the suggestions they prefer and disregard the ones they don't. With continued use, Copilot learns the coder's writing style and improves its suggestions accordingly. It acts as a helpful friend, speeding up coding and simplifying the process.
AWS whisper:
The tool is talked about, which the IT community has made waves - AWS whisper. This service (AWS) has been provided by Amazon Web Service, which makes developers' lives easier and does a fantastic job. Now let's look at some of its features. In today's world, AI is becoming more common. Making sure that the code is fair and unbiased is important. That's where AWS Code Whisperer’s Responsible AI feature helps. The code is checked using smart technology to find any biases or ethical problems. Developers can code with confidence, knowing that the digital world is being made fairer and more equal.
Easy Coding on the Move:
Have you ever been in a rush to meet deadlines and felt like there was never enough time to write all the code? Well, say hello to AWS Code Whisperer’s auto code generation feature. This handy tool uses machine learning to study your existing code and create new code based on it. It's like having a personal assistant who understands your coding style perfectly and can generate the code you need, whenever you need it. This feature is a real lifesaver for busy projects or when tackling tough coding challenges.
More than Just a Whisper:
AWS Code Whisperer offers more than just Responsible AI and auto code generation. It comes with various features to enhance the software development process. Real-time code analysis helps identify and fix errors quickly, and code review capabilities make collaboration easy. Teams can collaborate with their managers to ensure code quality is maintained. Moreover, AWS Code Whisperer is highly customizable. Custom rules for code analysis can be created or the tool can be set up to work with the preferred programming language. The goal is to make the tool adapt to the users' needs, rather than the other way around.
In simple terms, AWS Code Whisperer is a versatile tool for developers. It helps with Responsible AI, auto code generation, and real-time code analysis. It's great for developers who understand coding well. Remember, AI works best when used by skilled developers.
Whisper listens to sounds from phones or videos and uses smart tech to turn the talking into writing. This writing can be used for making subtitles or writing down what's said in meetings. But if it's too noisy or hard to hear, Whisper might not get it all right. Amazon keeps making Whisper better. Even though we're not sure how it works with Amazon Connect, it could help answer calls by writing down what people say and sending the calls to the right person.
Determining the best tool among Devin AI, Github Copilot, and AWS Whisper depends on your specific needs.
Devin AI although it's a bit mysterious if it materializes, it could potentially excel in various tasks. However, currently, there isn't much information available about it. Github Copilot this tool is tailor-made for programmers. It accelerates your coding process by providing suggestions and even entire code blocks. If you're a coder, this tool is perfect for you. AWS Whisper this tool excels in converting spoken words into written text accurately. It's particularly useful for tasks like note-taking during meetings or adding captions to videos.
Looking forward, tools like Devin AI hold promise, but for now, if you need to write code, GitHub Copilot is your go-to option. If you're dealing with spoken words, AWS Whisper is the ideal choice. Each tool performs exceptionally well in its respective area, so your decision should be based on your specific requirements.
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