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A significant portion of the software landscape in large companies is built on legacy systems. According to a recent report, as much as 70% of the software in use by Fortune 5000 companies was developed over 20 years ago. While there is a compelling business case for modernizing these outdated applications, the process of migration often comes with significant challenges. The complexity of testing older software, the high costs of migration, and the limited knowledge of legacy technologies create barriers that slow down the transition and maintain existing technical debt. These hurdles are particularly evident when dealing with systems that…

“Baidu’s ERNIE 4.5 and ERNIE X1: Shaping the Future of AI Competition” Baidu’s recent unveiling of its ERNIE 4.5 multimodal foundation model and ERNIE X1 reasoning model has stirred the AI landscape, signaling the beginning of a fierce global race in artificial intelligence. These models, which offer a combination of cutting-edge capabilities and cost-efficiency, are expected to lower adoption barriers and drive competition across the industry. According to Thomas Randall, the research lead for AI at Info-Tech Research Group, the success of these models will hinge on how well they perform in real-world applications, developer adoption, and enterprise trust. However,…

“GCC 15: What’s New and What’s Coming for Compilers” The GCC (GNU Compiler Collection) 15 update is progressing smoothly, with several exciting developments set to enhance various programming languages and architectures. Among the most notable changes is the introduction of a new front-end for COBOL, a language still integral to legacy systems in various industries. This update is expected to provide greater flexibility and efficiency for COBOL development, particularly for systems that rely heavily on the language for long-term stability. COBOL’s integration into GCC will allow developers to use a free software compiler for a language that has been deeply…

“GitHub Actions Tool Breach: A Wake-Up Call for App Development Teams” App development teams that rely on GitHub Actions, a popular continuous integration and continuous delivery (CI/CD) platform, are facing a serious security threat. Last week, a widely-used utility, tj-actions/changed-files, was compromised, potentially exposing thousands of repositories to credential theft. The vulnerability, which researchers at StepSecurity discovered, affected all versions of the tool up to version 45.0.7, released on March 14. Typically, tj-actions/changed-files helps developers track file changes in a repository, but following the attack, a malicious Python script was introduced that allows attackers to steal sensitive information such as…

“AI and No-Code: Revolutionizing Business App Development” The emergence of generative AI and no-code development tools is reshaping the software industry in profound ways. These technologies are breaking down traditional barriers, enabling businesses to create sophisticated applications without the need for deep technical expertise. While AI has already been transforming various industries, no-code platforms take things a step further by democratizing access to these powerful capabilities. Now, even those without programming skills can develop highly customized business applications, allowing for faster development cycles and more tailored solutions. This combination of AI and no-code tools offers businesses a unique opportunity to…

“Why AI-Generated Code Falls Short (And How It Can Improve)” The rise of large language models (LLMs) in software development has been swift and transformative. Promises of unparalleled productivity gains and seamless coding assistants sparked a wave of excitement. Developers could now generate multi-line code blocks at the touch of a button, merging complex solutions into their projects with ease. At first glance, it seemed like a magic trick—effortless and flawless. However, beneath the surface, a lingering question remained: Can I really trust this code? While the use of AI in coding has become widespread, many developers still have reservations…

“AI Can Provide Code, But Community is What Fuels Progress” For years, developers have relied on Q&A platforms like Stack Overflow to navigate the intricacies of coding, whether it’s tackling specific bugs, discussing best practices, or brainstorming high-level design patterns. These platforms have long been a hub for human-driven problem-solving, where experienced developers share their insights and solutions, building a treasure trove of collective knowledge. However, with the rise of large language models (LLMs) like GPT, there’s been a shift in how developers seek and consume information—one that promises increased productivity but may also isolate them from the vibrant community…

Java Development Kit (JDK) 25: A Glimpse at the Latest FeaturesScheduled for release in September, JDK 25 is shaping up to be an important long-term support (LTS) version of Java, bringing new features and significant changes. Two of the most notable updates already proposed for this release include the introduction of a preview API for stable values and the removal of the long-deprecated 32-bit x86 port. These updates aim to enhance performance, improve efficiency, and streamline the Java ecosystem for developers. Stable Values: A Boost for Java Application StartupOne of the standout features of JDK 25 is the preview API…

Air-Gapped Python: Setting Up Python Without a Net(work)Sometimes, the internet just isn’t available, or you may need to keep your systems isolated for security reasons. No matter the scenario, you can still set up Python and get your projects running. An air-gapped environment doesn’t have to mean sacrificing functionality. With careful planning and manual downloads, you can install Python and its packages offline, ensuring your projects keep moving forward even without a network connection. Getting Started with Async in PythonWhen you’re handling multiple tasks in Python, efficiency is key. Traditional threading can be heavy and cumbersome, but Python’s async and…

Llama, Meta AI’s innovative family of large language models (LLMs), first made waves in the AI community when it was introduced in February 2023. Unlike other models that were primarily closed-source and developed by giants like OpenAI and Google, Meta’s Llama offered a fresh approach by emphasizing smaller, generic models that could be more easily and affordably retrained for specialized tasks. This made Llama an appealing option for developers and researchers looking for flexibility in creating tailored AI solutions. However, it’s important to note that while Llama models are marketed as “sort-of open-source,” they come with some important limitations, particularly…