Coding

AI is profoundly impacting the field of software development affecting each step in the software development lifecycle. It is enhancing code quality and efficiency through automated code generation, bug detection, and code review assistance. It is streamlining project management and resource allocation optimizing workflow enhancing execution.

Moreover, AI is enabling intelligent, data-driven decision-making by providing insights from large datasets, aiding in software testing, and improving user experience through personalized recommendations and natural language processing.

  • Coding

    How Generative AI Can Increase Developer Productivity Now

    The New Stack, 10/09/23. Generative AI is a hot topic in the developer community, driven by the need for increased productivity and the growing talent gap in AI engineering. However, organizations must also consider data privacy concerns and implement a generative AI policy. Many organizations are already incorporating AI into their tasks, and those that don’t risk falling behind. Early adopters have found that training large language models on internal documentation and policies can accelerate time to value and increase productivity. Conversational interfaces and advanced individual contributors can also benefit from generative AI. However, it is important to understand the limitations and use cases of generative AI to avoid potential pitfalls. READ THE ARTICLE

  • Coding

    Can AI code? In baby steps only

    ZDNet, 09/28/23. The use of generative AI in programming, exemplified by OpenAI’s ChatGPT, has raised expectations about its ability to generate computer code. However, research shows that while ChatGPT can offer suggestions and help overcome creative roadblocks, its assistance in coding is limited. Studies have found that large language models like GPT-4 perform below human coders in terms of overall code quality and correctness. Challenges in scalability, identifying errors, and effectively solving complex problems still persist. Although generative AI has potential, significant advancements are needed to overcome fundamental limitations and achieve higher levels of proficiency in coding. READ THE ARTICLE

  • Hallucinations

    The hot new thing: AI platforms that stop AI’s mistakes before production

    TechCrunch, 09/28/23. The growing trend of using AI-assisted code generation is giving rise to startups that aim to prevent issues with AI-augmented code. Startups like Digma and Kolena have recently secured seed funding to develop platforms that analyze and test AI-generated code. One such startup is Braintrust, a four-person Bay Area-based company that has just raised $3 million in funding. Braintrust is positioning itself as an “operating system for engineers building AI software.” With the support of notable investors, Braintrust aims to help developers avoid unfavorable outcomes from AI models by providing a reliable platform for testing and evaluation. READ THE ARTICLE

  • Coding

    AI chatbots were tasked to run a tech company. They built software in under seven minutes — for less than $1.

    Business Insider, 09/11/23. A recent study suggests that artificial-intelligence chatbots, like OpenAI’s ChatGPT, can efficiently run a software company with minimal human intervention. The study conducted by researchers from Brown University and Chinese universities tested if AI bots powered by ChatGPT’s 3.5 model could complete the software-development process without prior training. The AI bots were allocated specific roles and stages in the software development, communicating with minimal human input. The experiment found that the AI-powered company completed the process in under seven minutes, costing less than one dollar, with 86.66% flawless execution. While there were limitations, the study highlights the potential of AI chatbots in specific job functions and their applications in various industries. READ THE ARTICLE

  • Coding

    AI is great at coding, but there are some massive caveats

    ZDNet, 09/07/23. The adoption of generative artificial intelligence (AI) models like GitHub CoPilot and ChatGPT has software professionals excited about the possibilities, but there are concerns about intellectual property and security. A recent survey of developers and executives revealed worries about AI tools accessing private information and exposing sensitive data. Copyright concerns topped the list, with concerns about security vulnerabilities and the lack of copyright protection for AI-generated code. However, technologists remain optimistic, with many organizations using AI in software development and experiencing successful outcomes. Training and skills development are important areas to address. Ultimately, human oversight and collaboration with AI are crucial for addressing concerns and ensuring code quality. READ THE ARTICLE