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Swift’s deliberate design choices over the years has resulted in a language that showcases how flexibility and compatibility does not need to come at the cost of usability. One of these design choices was Swift’s focus on native interoperability with other languages. The flexibility that this enables makes it a joy to build rich, native experiences in Swift across a variety of environments. By Saleem Abdulrasool.

Swift embeds a copy of clang, the C and C++ compiler, which is able to directly translate between the languages avoiding penalties in code size and runtime performance. This level of interoperability composes wonderfully with existing systems and enables building complex software atop existing C libraries. You will also learn about:

• The Windows API
• Component Object Model (COM)
• COM support in Swift with C Interop
• COM support in Swift with C++ Interop
• Improving Swift language support for COM
• Interoperability on Windows

Swift’s arsenal of interoperability tools makes it a potent language for building rich, native applications and libraries on existing platforms, and provides a great alternative to C and C++ with its improved memory safety and ergonomics. On Windows particularly, the interoperability features allow us to gain access to a very large set of the system’s API. Best of all, since COM is used outside of the Windows ecosystem, improvements to Swift’s integration with Windows system APIs, such as the native COM bridging described above, would also help other platforms! Nice one!

Until recently, the applications of artificial intelligence have remained in the hands of scientists, engineers and big business. But for the first time in history, anyone with an internet connection and keyboard can harness this technology. AI-powered tools – like OpenAI’s ChatGPT – have well and truly captured the public’s attention. By Alex von Schirmeister.

In 2024 and beyond,four factors will underpin the development of AI and its impact on small businesses:

• AI costs will need to be managed
• Consolidation could impact accessibility
• Control will lead to questions on accountability
• Copyright, creativity and commercially safe AI

The likes of Microsoft and Google are heavily subsidising the generative tools we play around with, without them making any money from AI – yet. On top of this, 2023 set a record for investment in generative AI startups, with equity funding exceeding $14 billion across 86 deals as of the second quarter of the year, much of which startups are spending on building the infrastructure needed to build, train and run their AI models. AI must now become a self-funding endeavour, as its economics are currently higher than the cost of labour. Good read!

HGX H200 systems and cloud instances coming soon from world’s top server manufacturers and cloud service providers. NVIDiA supercharged the world’s leading AI computing platform with the introduction of the NVIDIA HGX™ H200. Based on NVIDIA Hopper™ architecture, the platform features the NVIDIA H200 Tensor Core GPU with advanced memory to handle massive amounts of data for generative AI and high performance computing workloads. By @nvidia.

The NVIDIA H200 is the first GPU to offer HBM3e — faster, larger memory to fuel the acceleration of generative AI and large language models, while advancing scientific computing for HPC workloads. With HBM3e, the NVIDIA H200 delivers 141GB of memory at 4.8 terabytes per second, nearly double the capacity and 2.4x more bandwidth compared with its predecessor, the NVIDIA A100.

The introduction of H200 will lead to further performance leaps, including nearly doubling inference speed on Llama 2, a 70 billion-parameter LLM, compared to the H100. Additional performance leadership and improvements with H200 are expected with future software updates. Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure will be among the first cloud service providers to deploy H200-based instances starting next year, in addition to CoreWeave, Lambda and Vultr. Interesting read!

The rapid proliferation and increased volume of data across industries has magnified the need for organizations to have a solid strategy in place for processing and managing real-time data. Improving overall data capabilities enables teams to operate more efficiently, and emerging technologies have even created a smoother pathway for bringing real-time data closer to business users, which plays a critical role in effective decision-making. By Miguel Garcia.

In this article you will learn:

• Beyond the architecture
  • Data challenges
  • Performance
  • Security and compliance
• Architecture patterns
  • Stream-to-stream
  • Batch-to-stream
  • Stream-to-batch
  • Lambda architecture
  • Kappa architecture
  • Streaming architecture
• Reference Architecture: Streaming architecture with Apache Kafka and Apache Druid

… and more. There are several key data architecture patterns — each one with its strengths, limitations, and use cases. The architecture we choose plays a pivotal role in determining performance, adaptability, and business impacts. However, the knowledge of these architectures alone won’t guarantee success because there are other factors to consider, such as adequate training, team size, cost, or even organizational culture, that may affect decision-making. Good read!

If you are struggling to come up with your app idea, it’s okay. You’re not alone. It is common for app developers to face this type of challenge given the millions of apps in the App Store. Also, thinking of an app idea isn’t always as easy as it sounds. By Pat Enriquez.

Most ideas are born from putting together old and existing ideas. So don’t be discouraged if you find an app in the App Store with the same idea as yours and don’t just scrap that app idea.

The article then describes these strategies:

• The remix strategy
• Scratch your own itch
• Improve what already works

When it comes to app development, oftentimes, apps are made by thinking about how they can solve the problems of app developers themselves. Interesting read!

Spring Supports GraphQL requests over HTTP, Websockets and RSockets. Securing an Spring GraphQL application does not differ from securing a Web application. Mainly, Spring GraphQL needs to ensure context propagates from WebFlux to the data fetching layer so that we can use Security annotations or access the authenticated principal in @SchemaMapping methods. This should work for HTTP and WebSocket. By Ruchira Madhushan Rajapaksha.

In this tutorial, we will develop a Reactive Spring boot application that secures an exposed GraphQL API using JWT authentication. We will be having a separate rest endpoint to generate the JWT, which we will use to validate the GraphQL endpoint. For more information about JWT, just refer to the following guide.

Further in this article you will find information on:

• Application Setup with SpringBoot
• JWT Utility
• Spring Security Configuration
• SecurityContextRepository
• AuthenticationManager

To apply more fine-grained security, we can add Spring Security annotations such as @PreAuthorize or @Secured to service methods involved in fetching specific parts of the GraphQL response. This should work due to Context Propagation that aims to make security, and other contexts, available at the data fetching level. Interesting read!

Single-board computers (SBCs) can be a powerful tool for education. Here are some of the things that SBCs can do for education. SBCs can promote various subjects and topics for educators. SBCs can be a powerful tool for education, helping to equip students with the skills and knowledge they need to succeed in the 21st century, such as collaborative learning, creativity and innovation, technical skills, etc. By DFRobot.

When choosing a single-board computer (SBC) for education, here are some factors to consider: price, ease of use, performance, detailed documentation and tutorials, offer easily expandable hardware interfaces, integrate cloud services, stability, flexibility.

The article then lists these:

• The most popular SBC - Raspberry Pi
• The powerful SBC - BeagleBone Black
• IoT Python Single Board Computer with Touchscreen - UNIHIKER
• The smallest x86 windows SBC - LattePanda
• The entry-level AI SBC - NVIDIA Jetson Nano

If you wish to purchase a board solely for teaching basic entry-level programming subjects, then the Raspberry Pi will suffice. If you intend to use it for building more complex projects such as robots or IoT devices with your students, Lattepanda with its onboard Arduino support would be more convenient. If you plan to guide your students in studying the field of AI, then Jetson Nano would be a suitable choice. Ultimately, your choice of SBC should be based on your budget and requirements. Nice one!

From the humble beginnings of a single microchip, the microprocessor emerged as a catalyst for technological advancement and a key driver of computing evolution. Its invention marked a turning point in the history of computing, igniting a revolution that continues to shape our digital world today. By Marcin Wieclaw.

The significance of microprocessors cannot be overstated. These innovative chips, also known as CPUs (central processing units), have transformed the way we interact with computers and electronic devices across all scales. From the smallest consumer appliances to the most powerful supercomputers, microprocessors have revolutionized the way we live, work, and connect with the world.

The article also deals with:

• A brief history of the microprocessor
• Advantages of microprocessors
• Disadvantages of microprocessors
• Transformation of computing through microprocessors
• The future of microprocessors: Unlocking infinite possibilities

As we enter the next era of computing, the future of microprocessors is poised to redefine the limits of technology. One of the most exciting advancements on the horizon is quantum computing. Quantum microprocessors, based on the principles of quantum mechanics, have the potential to revolutionize computing power by performing computations at speeds exponentially faster than traditional processors. These quantum machines can tackle complex problems that were once thought to be unsolvable, opening doors to breakthroughs in cryptography, optimization, and scientific research. Good read!

In June 2023 an IBM computing executive claimed quantum computers were entering the “utility” phase, in which high-tech experimental devices become useful. In September, Australia’s Chief Scientist Cathy Foley went so far as to declare “the dawn of the quantum era”. Obviously, quantum computers are having a moment. But – to step back a little – what exactly are they? By Christopher Ferrie.

In the 1990s, physics and computer science collided when it was discovered that some problems could be solved much faster with algorithms that work directly with complex numbers as encoded in quantum physics. The next logical step was to build devices that work with light and matter to do those calculations for us automatically. This was the birth of quantum computing.

The article explains:

• What is a quantum computer?
• Why does quantum computing matter?
• What is the current landscape?
• Superconductors, ions, silicon, photons
• Where will the quantum future take us?

Commercial spin-offs of technology such as quantum sensing are also on the horizon. The demonstration of a genuine “quantum advantage” will also be a likely development. This means a compelling application where a quantum device is unarguably superior to the digital alternative. Super interesting read!

Building on the AI PC use cases shared at Innovation 2023, Intel recently launched the AI PC Acceleration Program, a global innovation initiative designed to accelerate the pace of AI development across the PC industry. By Intel PR.

Intel’s AI PC Acceleration Program will enable artificial intelligence (AI) on more than 100 million PCs through 2025, propelled by the upcoming launch of Intel® Core™ Ultra processors on Dec. 14. The AI PC Acceleration program will provide access to Intel’s deep bench of engineering talent for targeted software optimizations and tuning based on ISV needs, core development tools and software developer kits like OpenVINO™, and go-to-market opportunities.

Working with more than 100 ISVs and more than 300 AI-accelerated features, Intel will enhance PC experiences across audio effects, content creation, gaming, security, streaming, video collaboration and more.

Program includes Adobe, Audacity, BlackMagic, BufferZone, CyberLink, DeepRender, Fortemedia, MAGIX, Rewind AI, Skylum, Topaz, VideoCom, Webex, Wondershare Filmora, XSplit and Zoom. Interesting read!