Info World

In less than a month Microsoft will end support for .NET’s first major cross-platform UI tool, Xamarin Forms. Instead of developers having to build separate UIs for Windows, iOS, and Android, Xamarin Forms gave us a set of cross-platform UI controls we could use to build one code base that compiled to all target platforms, without any device-specific code. It was a big hit, but now it’s fading away.

Microsoft has been developing a follow-on to Xamarin Forms in the shape of MAUI, the Multi-platform App UI. MAUI supports Windows, macOS, iOS, and Android, again allowing you to continue to develop code using the same tools and techniques as Xamarin, working with the latest .NET releases. MAUI is still very much under development, with some differences that make it hard to simply swap out one set of controls for another.

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In less than a month Microsoft will end support for .NET’s first major cross-platform UI tool, Xamarin Forms. Instead of developers having to build separate UIs for Windows, iOS, and Android, Xamarin Forms gave us a set of cross-platform UI controls we could use to build one code base that compiled to all target platforms, without any device-specific code. It was a big hit, but now it’s fading away.

Microsoft has been developing a follow-on to Xamarin Forms in the shape of MAUI, the Multi-platform App UI. MAUI supports Windows, macOS, iOS, and Android, again allowing you to continue to develop code using the same tools and techniques as Xamarin, working with the latest .NET releases. MAUI is still very much under development, with some differences that make it hard to simply swap out one set of controls for another.

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The Apache Software Foundation develops and maintains open source software projects that significantly impact various domains of computing, from web servers and databases to big data and machine learning. As the volume and velocity of time series data continue to grow, thanks to IoT devices, AI, financial systems, and monitoring tools, more and more companies will rely on the Apache ecosystem to manage and analyze this kind of data.

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With the third preview of the planned Visual Studio 2022 17.10, Microsoft has “unified” the GitHub Copilot experience in the IDE, combining Copilot and Copilot Chat into a single extension.

Introduced April 9, Visual Studio 2022 17.10 Preview 3 combines the features of GitHub Copilot and Copilot Chat into one package, eliminating the need to install two separate extensions and will provide a more integrated AI experience in the future, Microsoft said. Developers can activate a GitHub Copilot subscription at github.com.

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It wouldn’t have taken a billion-parameter large language model (LLM) to predict that the dominant theme of this year’s Google Cloud Next conference would be generative AI—indeed, it will probably be the dominant theme of the year for most enterprise software developers.

At the event, Google introduced a host of updates to its cloud platform to make working with LLMs easier, and added generative AI-based assistants to many of its offerings. Here are six key takeaways from the conference:

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The Go programming language is viewed by developers who build AI-powered applications and services as a strong platform for running those workloads. Nevertheless, Python is viewed by Go developers as the language to use when starting AI-powered work, according to a recent survey of Go developers.

In the semi-annual Go Developer Survey for 2024, conducted in January and February  by the Go team at Google, survey respondents who build AI-powered applications and services shared a sense that Go was a strong platform for running these types of workloads in production. A majority of respondents working with AI-powered applications already use Go or would like to migrate to Go for AI workloads.

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In “Retrieval-augmented generation, step by step,” we walked through a very simple RAG example. Our little application augmented a large language model (LLM) with our own documents, enabling the language model to answer questions about our own content. That example used an embedding model from OpenAI, which meant we had to send our content to OpenAI’s servers—a potential data privacy violation, depending on the application. We also used OpenAI’s public LLM.

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In the first half of this article, we set up a web development stack and created a simple example application using Bun, HTMX, Elysia, and MongoDB. Here, we'll continue exploring our new stack while cleaning up and abstracting the example application's data access layer and adding more complex HTMX interactions. We'll also add another component to the tech stack: Pug, a popular JavaScript template engine that works well with HTMX and helps with configuring DOM interactions.

Our example application currently consists of a form and a table. The form lets users enter quotes along with their authors, which can then be searched and displayed using the application's user interface. I've added a bit of CSS to the interface to make it look more modern than what we left off with in Part 1:

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Synopsys has introduced Black Duck Supply Chain Edition, a software composition analysis (SCA) package that helps organizations mitigate upstream risk in software supply chains, including from AI code.

Announced April 9, Black Duck Supply Chain Edition is intended to address a rise in software supply chain attacks targeting vulnerable or maliciously altered open source and third-party components. Due April 25, the product combines open source detection technologies, automated third-party software bill of materials (SBOM) analysis, and malware detection to give a view of software risks inherited from open source, AI-generated code, and third-party code, Synopsys said. Security and development teams can track dependencies across the application life cycle to find and resolve security vulnerabilities, malicious packages, and license violations and conflicts, the company added.

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Google at Google Cloud Next 24 unveiled three open source projects for building and running generative AI models. The company also introduced new large language models to its MaxText project of JAX-built LLMs.

The new LLM models in MaxText include Gemma, GPT-3, Llama 2, and Mistral, which are supported across both Google Cloud TPUs and Nvidia GPUs, the company said. 

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Teradata is partnering with Anaconda to add packages of popular programming languages Python and R to its multi-cloud analytics platform offering, VantageCloud Lake.

The partnership will see Teradata integrate the packages from Anaconda’s repository into its self-service data analytics offering, ClearScape Analytics, which comes packaged inside VantageCloud Lake.

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Google has added new large language models (LLMs) and a new agent builder feature to its AI and machine learning platform Vertex AI at its annual Google Cloud Next conference.

The LLM include a public preview of the Gemini 1.5 Pro model, which has support for 1-million-token context.

The expanded support for context allows native reasoning over enormous amounts of data specific to an input request, the company said, adding that it has received feedback from enterprises that this expanded support can eliminate the need to fine-tune models or employ retrieval augmented generation (RAG) to ground model responses.

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Google Cloud is adding capabilities driven by its proprietary large language model, Gemini to its database offerings, which include Bigtable, Spanner, Memorystore for Redis, Firestore, CloudSQL for MySQL, and AlloyDB for PostgreSQL, the company announced at its annual Next conference.

The Gemini-driven capabilities, which are currently in public preview, include SQL generation, and AI assistance in managing and migrating databases.

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Google’s cloud computing division, Google Cloud, at its annual Google Cloud Next conference has introduced Gemini Cloud Assist, an AI-powered assistant designed to help enterprise teams manage applications and networks in Google Cloud.

Gemini Cloud Assist, now available in private preview, can be accessed through a chat interface in the Google Cloud console. It is powered by Google’s proprietary large language model, Gemini.

“Gemini’s contextual and personalized AI guidance understands your Google Cloud resources to help you craft new designs, deploy workloads, manage applications, troubleshoot issues, and optimize performance and costs,” Google said.

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Google’s cloud computing division, Google Cloud, has changed the name of its previously released Duet AI for Developers offering to Gemini Code Assist and added new features to make code generation easier.

Gemini Code Assist is based on the Gemini 1.5 Pro model, Google’s most powerful generative AI model. Earlier in December, the company in a blog post had said that it would make its Gemini model available to developers.

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Parasoft has launched a tool to enhance safety testing for C and C++ applications. The tool comes at a time when the two venerable programming languages have come under fire over safety concerns.

Announced April 8, the C/C++test CT (Continous Testing) tool is intended to empower large developer teams to build reliable and dependable embedded systems. It provides a comprehensive solution for large teams engaged in the development of safety-critical and security-critical C and C++ products, Parasoft said. C/C++test CT integrates with developers’ desktop environments such as Visual Studio Code, unit testing frameworks such as GoogleTest, Boost.Test, and CppUnit, and CI/CD workflows for continuous testing and efficiency, according to Parasoft.

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Environmental, social, and governance (ESG) factors have gained significant traction recently. Giving yourself a ranking to prove your worth as a good citizen of the planet seems like a great idea.

These tools are worth looking at, but the reality is they may be reporting a false positive. They don’t look at the total inefficiencies of the overall cloud architecture, only at specific tactical metrics that could prove meaningless. Indeed, it provides good scores for enterprises underperforming in sustainability and using public cloud providers.

The increasing pressure on cloud providers to enhance their ESG performance is a testament to the growing awareness of the environmental impact of data center growth. I live in northern Virginia, where data centers are scattered everywhere.

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Chip manufacturers are producing a steady stream of new GPUs. While they bring new benefits to many different use cases, the number of GPU models available from each manufacturer can overwhelm developers working with machine learning workloads. To decide which GPU is right for your organization, a business and its developers must consider the costs of buying or renting the GPU to support the type of workload to be processed. Further, if considering an on-premises deployment, they must account for the costs associated with data center management. 

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Charlie, a senior architect at a medium-sized software development organization, sat at his desk going over the specifications for the latest development project at his company. As he was taking a high-level look at how to break down the work for the first phase of the project, Janice, a hard-charging, early-career developer walked into his office.

Janice doesn’t hesitate. “Hey—I see that our new project is going to require some encryption. I’d like to take a stab at writing the encryption library for the project. I’ve been looking at various algorithms lately, and I’d like to give it a go.”

Charlie, of course, admires the enthusiasm, but knows right away that this isn’t going to happen. 

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PHP, long a popular server-side scripting language for web development, has dropped to its lowest position ever in the monthly Tiobe index of programming language popularity, ranking 17th in the April 2024 edition of the index.

When the Tiobe index started in 2001, PHP was about to become the standard language for building websites, said Paul Jansen, CEO of software quality services vendor Tiobe. PHP even reached the top 3 spot in the index, ranking third several times between 2006 and 2010. But as competing web development frameworks such as Ruby on Rails, Django, and React arrived in other languages, PHP’s popularity waned.

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