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Retro Gaming with Raspberry Pi (3rd Edition) book now available

Retro Gaming with Raspberry Pi (3rd Edition) book now available

Anyone who likes playing retro games or building projects with the Raspberry Pi mini PC will be pleased to know that the official Raspberry Pi Foundation team has released a new book in the form of Retro Gaming with Raspberry Pi (3rd Edition). This 180-page manual is a treasure trove for those who yearn to dive back into the games of the past, using the Raspberry Pi as their time machine.

The guide is is priced at £14 and offers a meticulously crafted resource that appeals to both beginners and experienced gamers. It takes you on a detailed journey through the process of using the Raspberry Pi to emulate beloved gaming systems. Whether you’re a fan of the Nintendo GameCube, Sony PlayStation, or Sega Dreamcast, this book has you covered. It teaches you how to turn your Raspberry Pi into a versatile emulation station, allowing you to play the games that once defined an era.

Retro Gaming with Raspberry Pi (3rd Edition) book

But the book goes beyond just playing old games. It also guides you through the exciting process of building your own gaming hardware. Whether you want to create a portable handheld device or a full-sized arcade cabinet, the instructions are clear and straightforward. By following the steps, you can construct a gaming setup that not only works well but also serves as a personal homage to the golden age of video games.

“Retro Gaming with Raspberry Pi shows you how to set up Raspberry Pi 5 to play a new generation of classic games. In this 180-page book, you’ll build a gaming console and full-size arcade cabinet, install emulation software and download original games with full step-by-step guides. Discover a vibrant homebrew scene packed with new games for original consoles and legal access to all those retro games you remember!”

  • Set up Raspberry Pi for retro gaming
  • Emulate classic computers and consoles
  • Learn to code retro-style games
  • Build a console, handheld, and full-size arcade machine

The authors of the guide are mindful of the legalities surrounding game emulation. They stress the importance of respecting the original creators’ intellectual property. The book provides advice on how to acquire games in a way that’s both legal and respectful, ensuring that your trip down memory lane is not tarnished by ethical concerns.

One of the most vibrant aspects of retro gaming is the community of enthusiasts who continue to develop new games for old consoles. The third edition of the guide shines a light on these passionate developers, who keep the spirit of retro gaming alive by pushing the boundaries of what vintage hardware can do. The book features their work and encourages readers to explore the world of homebrew games.

In addition to technical guidance, the book is filled with inspiring stories from people around the world who have embarked on their own retro gaming projects. These tales offer a window into the creative process and serve as a catalyst for readers to start their own projects. They demonstrate the wide-reaching impact that retro gaming has had on individuals and communities alike.

The guide concludes with a look at the global community of retro gaming fans. This diverse group of hobbyists and professionals is constantly developing new games and tools for old systems, ensuring that the love for retro gaming continues to thrive.

With Retro Gaming with Raspberry Pi, you have everything you need to revisit the classics using today’s technology. Grab your Raspberry Pi and get ready to experience the intersection of nostalgia and innovation, where the games of yesterday meet the possibilities of today. For more details on purchasing options jump over to the official Raspberry Pi Press website.

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Raspberry Pi 5 M.2 SSD HAT+ PCIe Gen 3 board launches for $9

Raspberry Pi 5 M2 HAT PCIe Gen 3

Raspberry Pi users have a new solution to quickly adding solid-state drives (SSD)  to their new powerful Pi 5 mini PCs. Waveshare has just released a new product that’s both affordable and efficient for those looking to enhance their Raspberry Pi 5 experience. The M.2 HAT+ board, priced at a mere $8.99, is a budget-friendly expansion that allows for the integration of M.2 NVMe drive support into Raspberry Pi projects. This is a significant development for enthusiasts who want to boost their device’s data transfer rates and overall performance without spending a lot of money.

Raspberry Pi HAT SSD compatibility

The M.2 HAT+ board takes advantage of the Raspberry Pi 5’s PCIe lane. This is a big deal because it’s the first time a Raspberry Pi model has offered a user-accessible PCIe lane, opening up new possibilities for expansions and upgrades. With this board, users can now use compact and high-speed 2230 and 2242 format M.2 NVMe drives. Even more impressive is the ability to boot directly from these drives, which means faster start-up times and more efficient operation. Here are some other articles you may find of interest on the subject of Raspberry Pi 5 :

Waveshare’s new board is not just about performance; it’s also designed with the user in mind. It features a cooling cutout to help manage the heat generated by the M.2 drive, ensuring that the system remains stable even under heavy use. Additionally, the board doesn’t block access to the Raspberry Pi 5’s GPIO header, which is important for those who want to connect additional expansions. The package comes complete with all the necessary installation accessories, making it accessible for both novices and experienced users alike.

Raspberry Pi HAT notification LEDs

The introduction of the M.2 HAT+ board by Waveshare is a significant step forward for the Raspberry Pi community. It offers compatibility with the latest Raspberry Pi model and supports the popular M.2 NVMe drives. The ability to boot directly from these drives, combined with the board’s cost-effectiveness and user-friendly design, makes it an attractive option for anyone looking to upgrade their Raspberry Pi 5 without breaking the bank.

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How to build an AI home security system using a Raspberry Pi mini PC

AI home security system using a Raspberry Pi mini PC

If you are looking for a project to keep you busy this weekend you might be interested in learning how to create your very own personal AI assistant by installing artificial intelligence onto a Raspberry Pi mini PC. The latest addition to the line of mini PC hardware is the Raspberry Pi 5, a small yet mighty computer, can now be the brains behind your home security and home automation system, thanks to advancements in artificial intelligence (AI). By combining the Raspberry Pi with the Coral AI Edge TPU, you can create a surveillance system that not only watches but understands what it sees.

AI home security system

To start, you’ll need to connect the Coral AI Edge TPU to your Raspberry Pi. This is done through a special accessory called the Pineberry AI hat, which fits onto the Raspberry Pi and uses the PCIe express bus for fast data transfer. This setup is crucial for handling the demands of AI applications. Once the hardware is in place, you’ll install the Raspberry Pi OS, setting the stage for your AI-powered security system.

The next step is to get the software ready. Docker is a tool that will help you run your AI models without any hiccups. It creates separate environments for each application, so they don’t interfere with each other. You’ll also need to set up MQTT, a messaging protocol that lets different parts of your AI system talk to each other seamlessly.

Running AI on a Pi

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For remote access, you’ll want to connect your Raspberry Pi to your Wi-Fi network and configure SSH. SSH allows you to securely log into your Raspberry Pi from another computer, which is incredibly handy for making updates or changes to your AI applications from anywhere.

When it comes to cameras, you have options. Webcams are a simple, cost-effective choice, while IP cameras offer higher quality and more features. Depending on your needs and budget, you can choose the best fit for your system. These cameras will work with Frigate, an open-source software that’s the heart of your AI surveillance system.

Frigate uses machine learning to analyze video footage in real-time. After installing Frigate on your Raspberry Pi, you’ll set it up with a configuration file written in YAML. This will kickstart your AI surveillance, allowing you to monitor your home with a smart, responsive system.

For those who want even more power, you can add more Edge TPUs to your Raspberry Pi. This means you can process several video streams at once, giving you a more comprehensive view of your home’s security. The Raspberry Pi’s PCIe slot isn’t just for AI, though. It can also be used for other upgrades, like adding NVMe storage, which can speed up your device for a range of projects.

By following these steps, you can transform your Raspberry Pi 5 into a cutting-edge tool for home surveillance. The combination of the Coral AI Edge TPU and the Pineberry AI hat opens up a world of possibilities for tech enthusiasts. This setup allows you to run complex AI models efficiently, making it a powerful and affordable choice for not just home security, but for any AI project you can dream up.

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MyCobot 280 Raspberry Pi robotic arm

MyCobot 280 Raspberry Pi robotic arm

If you have ever dreamt of owning your own precision robotic arm you might be interested in the  MyCobot 280 Pi. An advanced robotic arm that is powered by the Raspberry Pi mini PC and is reshaping the way we think about automation and education. With a price tag of £651/$799, this piece of technology is making sophisticated robotics more accessible than ever before. It’s a tool that’s not just for experts but for anyone with a passion for innovation and learning.

“Using Raspberry Pi microprocessor and Ubuntu Mate 20.04 operating system, myCobot 280 Pi can be used by connecting monitor, keyboard and mouse without PC master control. It is the first choice for building robot arm programming education, control logic development, robot application and ROS simulation experiment class. To help you quickly start the learning and application of six axis robotic arm.”

The MyCobot 280 Pi is a marvel of modern engineering, boasting a 330° working rotation arc and a reach of 280mm. This robotic arm is not just about its physical capabilities; it’s also about the brains behind its operation. At its core is the Raspberry Pi 4, a tiny but powerful computer that provides the MyCobot 280 Pi with its intelligence and connectivity. This integration allows the robotic arm to perform a wide range of tasks with precision and ease, making it an invaluable asset for those looking to delve into the world of robotics.

What sets the MyCobot 280 Pi apart is its six degrees of freedom. This means the arm can move in six different ways, allowing for intricate and precise movements that mimic the dexterity of a human arm. This level of control is essential for tasks that require a delicate touch, such as assembling small components or conducting detailed experiments. The arm’s flexibility is further enhanced by its compatibility with various programming languages and the Robot Operating System (ROS), which is widely used in robotics research and development.

Raspberry Pi robotic arm

The MyCobot 280 Pi is not just about its technical prowess; it’s also designed with longevity in mind. Its durable plastic casings protect the internal components, ensuring that the robotic arm can withstand the rigors of continuous use. This durability is crucial for educational environments, where the arm may be used by multiple users and subjected to frequent handling.

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In terms of design, the MyCobot 280 Pi is both functional and adaptable. Its six joints provide a wide range of motion, and the inclusion of LEGO connectors opens up a world of possibilities for customization. Users can easily attach accessories and bases, allowing the robotic arm to take on new forms and functions. The G-Base 2.0 ensures that the arm remains securely attached to a desk or work surface, providing a stable foundation for all activities.

The MyCobot 280 Pi’s performance is not limited to a single application. It has proven itself capable of handling a variety of tasks with exceptional precision. This versatility has led to its widespread adoption, with over 10,000 units sold in more than 50 countries. The robotic arm supports over 10 accessories, making it suitable for complex projects in commercial exhibitions and educational settings. Its ability to engage and inspire is evident in the diverse ways it is being used around the world.

MyCobot 280 Pi

When it comes to technical specifications, the MyCobot 280 Pi is well-equipped to handle a range of items with its payload capacity of up to 250g. It features multiple connectivity ports, including USB 3.0, USB 2.0, Ethernet, and micro-HDMI, which provide users with the flexibility to connect a variety of peripherals. Additional connectors like Grove and servo ports further expand the arm’s capabilities, allowing it to interface with an even broader array of devices and sensors.

The MyCobot 280 Pi stands out in the robotics market for its robust build, powerful servos, and versatile programming capabilities. It’s an exceptional choice for anyone looking for a sophisticated Raspberry Pi robotic arm that can meet the demands of both educational and professional environments. Whether you’re a teacher looking to bring robotics into the classroom, a researcher exploring new automation techniques, or a hobbyist eager to experiment with cutting-edge technology, the MyCobot 280 Pi offers a unique opportunity to engage with the world of robotics in a hands-on and meaningful way.

Designing and using robotic arms

A robotic arm is a type of mechanical arm, usually programmable, with similar functions to a human arm. The arm may be the sum total of the mechanism or may be part of a more complex robot. The links of such arms are connected by joints allowing either rotational motion (such as in an articulated robot) or translational (linear) displacement. The links of the arm are connected by joints to provide rotational motion.

In their design, robotic arms can vary greatly in size, shape, and capability. They range from small, precise devices used in medical and electronic applications, to large, industrial machines capable of lifting heavy loads. The complexity of the arm depends on the task it is designed to perform, with more complex tasks requiring more sophisticated control systems.

The control of robotic arms involves several key aspects. Firstly, the kinematics, which is the study of motion without considering the forces that cause it. This involves calculating the positions, velocities, and accelerations of the various parts of the robotic arm. Secondly, dynamics, which considers the forces that cause the motion, is crucial for understanding how the arm will react under different conditions. Lastly, control systems are used to manage the arm’s movements in a precise and intentional manner.

Robotic arms are used in numerous applications, including manufacturing, medical surgery, and space exploration. In manufacturing, they can perform tasks like welding, assembly, and material handling. In medicine, they assist in precise surgical procedures, often enhancing the capabilities of human surgeons. In space, robotic arms are essential for tasks like repairing satellites or moving cargo and equipment in environments where human activity is limited or impossible.

The development and use of robotic arms continue to evolve, incorporating advanced technologies such as artificial intelligence and machine learning to enhance their capabilities, efficiency, and adaptability to various tasks.

This robotic arm is more than just a tool; it’s a gateway to understanding and harnessing the power of robotics. It’s an invitation to explore, to create, and to innovate. The MyCobot 280 Pi is not just about what it can do today but about the potential it unlocks for tomorrow. As we continue to push the boundaries of what’s possible, the MyCobot 280 Pi stands ready to be a trusted companion on that journey, bringing the future of robotics within reach for all. If you enjoyed Raspberry Pi projects you might also be interested in knowing how to run artificial intelligence (AI)  on a Raspberry Pi 5 using Ollama.

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Using Ollama to run AI on a Raspberry Pi 5 mini PC

Using Ollama to run AI Raspberry Pi 5 PC

Imagine having the power to process human language and interpret images right in the palm of your hand with a Raspberry Pi Ai, without relying on the internet or external cloud services. This is now possible with the Pi 5, a small but mighty computer that can run sophisticated language models using a tool called Ollama. This setup is perfect for those who value privacy, have limited internet access, or are simply fascinated by the potential of compact computing.

The Raspberry Pi 5 comes with 8 GB of RAM, which is quite impressive for its size. This memory capacity allows it to handle large language models (LLMs) such as Tiny Llama and Llama 2. These models are designed to understand and generate human language, making them incredibly useful for a variety of applications. Ollama is the key to unlocking these capabilities on the Raspberry Pi 5. It’s a tool that integrates smoothly with the language models, providing a straightforward interface that makes it easy for users to operate the LLMs on their device.

When you start using these language models on the Raspberry Pi 5, one of the first things you’ll notice is how it performs in comparison to more powerful computers, like a MacBook Pro. While the Raspberry Pi 5 may not have the same level of processing power, it still holds its own, delivering respectable performance at a fraction of the cost. This makes it an attractive option for hobbyists, developers, and anyone interested in exploring the world of language processing without breaking the bank.

Running AI on a Pi 5

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Monitoring the performance of your system is crucial when running LLMs on the Raspberry Pi 5. By keeping an eye on CPU usage and how quickly the system generates responses, you can fine-tune your setup to make the most of the Raspberry Pi’s resources. This not only enhances the functionality of your LLMs but also ensures that your device runs efficiently.

Raspberry Pi Ai using Ollama

One of the most exciting aspects of LLMs is their ability to make sense of images. With the Raspberry Pi 5, you can put this feature to the test. This capability is especially useful for developers who want to create applications that can process visual information without sending data over the internet. Whether you’re working on a project that requires image recognition or you’re simply curious about the possibilities, the Raspberry Pi 5 offers a unique opportunity to experiment with this technology.

But the functionality of the Raspberry Pi 5 and Ollama doesn’t stop at running language models. Ollama also supports API integration, which means you can connect your models to other software systems. This opens the door to more complex applications and uses, allowing you to build sophisticated systems that can interact with various software components.

Open-source LLMs (large language models)

Open-source large language models are a significant area of interest in the field of artificial intelligence. These models are made publicly available, allowing researchers, developers, and enthusiasts to explore, modify, and utilize them for various applications. The open-source nature fosters a collaborative environment, accelerates innovation, and democratizes access to advanced AI technologies.

  • GPT-Neo and GPT-NeoX: Developed by EleutherAI, these models are direct responses to OpenAI’s GPT-3. They aim to replicate the architecture and capabilities of GPT-3, offering a similar autoregressive model for natural language processing tasks. GPT-Neo and GPT-NeoX are part of an ongoing effort to create scalable, open-source alternatives to proprietary models.
  • GPT-J: Also from EleutherAI, GPT-J is an advancement over GPT-Neo, featuring a 6-billion parameter model. It’s known for its impressive performance in various language tasks, striking a balance between size and computational requirements.
  • BERT and its Variants (RoBERTa, ALBERT, etc.): While not exactly like GPT models, BERT (Bidirectional Encoder Representations from Transformers) and its variants, developed by Google, are pivotal in the NLP landscape. They are designed for understanding the context of a word in a sentence, offering strong performance in tasks like question answering and language inference.
  • T5 (Text-To-Text Transfer Transformer): Also from Google, T5 reframes all NLP tasks as a text-to-text problem. It’s a versatile model that can be applied to various tasks without task-specific architecture modifications.
  • Fairseq: This is a sequence modeling toolkit from Facebook AI Research (FAIR) that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text generation tasks.
  • XLNet: Developed by Google and Carnegie Mellon University, XLNet is an extension of the Transformer model, outperforming BERT in several benchmarks. It uses a permutation-based training approach, which is different from the traditional autoregressive or autoencoding methods.
  • BlenderBot: From Facebook AI, BlenderBot is an open-source chatbot model known for its engaging conversational abilities. It’s designed to improve the relevance, informativeness, and empathy of responses in a dialogue system.

Each of these models has unique characteristics, strengths, and limitations. Their open-source nature not only facilitates broader access to advanced AI technologies but also encourages transparency and ethical considerations in AI development and deployment. When utilizing these models, it’s crucial to consider aspects like computational requirements, the nature of the task at hand, and the ethical implications of deploying AI in real-world scenarios. For many more open source large language models jump over to the Hugging Face website.

The combination of the Raspberry Pi 5 and the Ollama tool provides a powerful platform for anyone interested in running open-source LLMs locally. Whether you’re a developer looking to push the boundaries of what’s possible with compact computing or a hobbyist eager to dive into the world of language processing, this setup offers a wealth of opportunities. With the ability to manage system resources effectively, interpret images, and integrate with APIs, the Raspberry Pi 5 and Ollama invite you to explore the full potential of local language models. Embrace this versatile technology and unlock a world of creative possibilities.

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Raspberry Pi 5 vs N100 PC performance comparison

Raspberry Pi 5 vs N100 PC performance comparison

When it comes to selecting a compact computer, the market offers a variety of options, each with its own set of strengths. Among these, the Raspberry Pi 5 and the N100 PC stand out as two notable choices. These systems are designed to cater to different user needs, and understanding their capabilities is crucial for making an informed decision. This article delves into the nuances of both machines, comparing their performance, cost, and suitability for various tasks.

The Raspberry Pi 5 is a small yet capable device that balances performance with energy efficiency. It’s designed to handle a variety of tasks without consuming excessive power, making it an attractive option for those looking to save on electricity costs. Its processor, while not as powerful as some alternatives, is adept at managing everyday computing needs. The device is also known for its quick boot times and smooth operation of applications, which is impressive given its size and price.

In contrast, the N100 PC is built with a stronger focus on performance, particularly in the realm of video rendering. Its more powerful GPU gives it an edge for multimedia projects, where rendering speed and quality are paramount. This makes the N100 PC a go-to choice for users who require more robust graphics capabilities.

Raspberry Pi 5 vs N100 PC

Check out the fantastic video once again created by ExplainingComputers and Christopher Barnatt to learn more about the differences between the Raspberry Pi 5 and the N100 PC and see how they compare when pitted against each other Running Ubuntu Linux operating system.

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Memory and storage are essential for any computer, and both the Raspberry Pi 5 and the N100 PC offer configurations that can accommodate the needs of most users. The N100 PC, however, typically allows for greater expansion, which could be a deciding factor for those who anticipate needing more space or memory in the future.

Connectivity is another critical aspect of modern computing. The Raspberry Pi 5 impresses with a wide range of ports and wireless options, ensuring that it can connect to various peripherals and networks with ease. The N100 PC also boasts strong connectivity features, although the exact offerings can depend on the specific motherboard used in the system.

For budget-conscious consumers, the Raspberry Pi 5 emerges as the more cost-effective solution. It provides a solid computing experience at a price point that is hard to beat. The N100 PC, on the other hand, tends to be pricier, especially once additional components such as a case or solid-state drive are factored in.

When evaluating performance, benchmarking tools reveal that the N100 PC typically outperforms the Raspberry Pi 5. This is particularly evident in tasks that demand more from the computer’s GPU. Despite this, the Raspberry Pi 5 holds its own, offering a level of performance that is more than adequate for many users, especially when its lower cost is taken into account.

Both systems are capable of streaming media effectively, which means they can serve as entertainment hubs in addition to their other functions. This versatility is a significant advantage for users looking to maximize the utility of their compact computing devices.

Other factors to consider include the ease of replacing parts, the availability of software, and the risk of malware. The Raspberry Pi 5, with its ARM-based architecture, tends to be less vulnerable to malware compared to the N100 PC’s x86 architecture. This could be an important consideration for those concerned about security.

Ultimately, the choice between the Raspberry Pi 5 and the N100 PC will hinge on the specific needs and priorities of the user. The Raspberry Pi 5 is a strong contender for those who value cost-efficiency, energy savings, and a lower risk of malware. Meanwhile, the N100 PC is better suited for users who need enhanced video rendering capabilities and are willing to invest in a higher level of performance for demanding applications.

Both the Raspberry Pi 5 and the N100 PC offer a range of features that make them suitable for a variety of compact computing projects. Whether you’re a hobbyist looking to experiment with a new setup, a professional in need of a reliable small-scale computer, or someone who simply wants a secondary device for media consumption, these systems have much to offer. By carefully considering the factors outlined above, you can choose the compact computer that best aligns with your requirements and ensures a satisfying computing experience.

Image Credit : ExplainingComputers

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Raspberry Pi 5 tablet made using a RasPad 3

Raspberry Pi 5 tablet made using a RaspPad 3

If you have previously purchased a RasPad 3 tablet powered by the previous generation Raspberry Pi 4 mini PC. You might be interested in this overview of how leepspvideo. Imagine having the power of a Raspberry Pi computer in the palm of your hand complete with a touchscreen display. This is the promise of the RasPad 3, a device that allows you to convert your Raspberry Pi into a touch-screen tablet. This transformation is not only possible but also relatively straightforward, providing you with a portable and versatile tool that combines the functionality of a Raspberry Pi with the convenience of a tablet.

It seems to be that the latest Raspberry Pi 5 and more powerful mini PC is compatible with the RasPad 3. Although the RasPad 3 was originally designed with the Raspberry Pi 4 in mind. As you can see in the video below it is possible to equip the tablet case with a Pi 5 although you will need to pay close attention to the alignment of the screw holes and make sure that the Raspberry Pi 5 is secure in the casing. This will help avoid any unnecessary modifications that could complicate the process.

Raspberry Pi 5 tablet

Next, you’ll need to align the connection ports. The Raspberry Pi 5 comes equipped with a variety of ports, including Ethernet, HDMI, and USB. These need to match up with the cutouts on the RasPad 3 to ensure that you can easily connect any peripherals and power the device. It’s important to double-check this alignment to prevent any future connectivity issues that might arise.

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Another critical aspect to consider is the power supply. The Raspberry Pi 5 has specific power needs that must be met by the RasPad 3. It’s essential to verify that the power supply provided with the RasPad 3 is sufficient for the Raspberry Pi 5. This step is vital to avoid any potential performance problems, such as system instability or overheating, which could hinder your experience with the device.

Once you’ve taken care of compatibility, alignment, and power requirements, it’s time to start the installation process. Begin by removing the existing Raspberry Pi 4 from the RasPad 3, if necessary. As you disassemble the components, keep track of them to ensure a smooth reassembly process. Then, proceed to install the Raspberry Pi 5, carefully aligning it with the screw holes and ports. Secure it in place with screws, following the instructions provided to avoid any damage to the delicate components.

After the Raspberry Pi 5 is installed, the next step is to power up the device and check the boot sequence. This is when you’ll test the touchscreen functionality. It’s crucial that the touchscreen accurately registers your inputs, as this is a key feature of your new tablet. If the touchscreen responds well to your touch, you’ve reached a significant milestone in the conversion process.

The final step in this transformation is to assess the system’s performance. Launch applications and navigate through the interface to make sure that the system responds quickly and reliably. A well-performing system should not exhibit any lag or crashes during regular use. This will ensure that your new tablet is not only functional but also a pleasure to use.

By following these steps, you can successfully convert your Raspberry Pi 5 into a tablet using the RasPad 3. This process requires careful planning and attention to detail, but the result is a unique and powerful device that offers both the advanced capabilities of a Raspberry Pi and the user-friendly experience of a tablet. Whether you’re a hobbyist, a developer, or just someone who loves tinkering with technology, this project is an opportunity to create something truly special that you can take with you wherever you go. Enjoy the new level of functionality and convenience that your Raspberry Pi 5 tablet brings to your projects and daily activities.

Image Credit : leepspvideo

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Installing Proxmox 8.1 virtualization platform on a Raspberry Pi 5

Installing Proxmox on a Raspberry Pi

If you’re looking to transform your Raspberry Pi 5 into a powerful server virtualization platform, installing Proxmox 8.1 is a smart move. Proxmox is a powerful and efficient open-source software to simplify your server management.  This guide will walk you through the process, ensuring you can set up your Pi mini PC to handle a variety of advanced computing tasks.

The Raspberry Pi 5 has the capability to boot from UEFI, which opens up a new realm of possibilities, including running Proxmox 8.1. This is a significant step forward for those who want to push the boundaries of what the Raspberry Pi can do.

Before you begin the installation, you’ll need to gather some hardware: a Raspberry Pi 5, an SSD for Proxmox, a USB drive for the Proxmox ISO, an SD card for UEFI boot files, and an external Ethernet adapter since the built-in Ethernet won’t work with UEFI boot. On the software side, you’ll need the Proxmox 8.1 ISO file and flashing software like Etcher to write the ISO to your USB drive.

Raspberry Pi 5 Proxmox 8.1 install

The installation process starts with preparing the SD card with the UEFI boot image, which will allow your Raspberry Pi to boot from the SSD. Next, use Etcher to flash the Proxmox ISO onto the USB drive. Once that’s done, connect the SSD, USB drive, and external Ethernet adapter to your Raspberry Pi. Power up your Raspberry Pi and follow the on-screen instructions to install Proxmox onto the SSD.

After Proxmox is installed, you’ll need to manually download container images and install additional packages to support various virtual environments. This step is crucial to ensure that your server can handle a wide range of tasks.

It’s not uncommon to run into some issues during installation. For instance, the Proxmox status menu might not display correctly on the Raspberry Pi 5, or you might need to tweak network settings to get the external Ethernet adapter working properly.

Proxmox Virtual Environment 8.1 features :

  • Support for Secure Boot: This version is now compatible with Secure Boot. This security feature is designed to protect the boot process of a computer by ensuring that only software with a valid digital signature launches on a machine. Proxmox VE now includes a signed shim bootloader trusted by most hardware’s UEFI implementations. This allows installing Proxmox VE in environments with Secure Boot active.
  • Software-defined Network (SDN): With this version the core Software-defined Network (SDN) packages are installed by default. The SDN technology in Proxmox VE enables to create virtual zones and networks (VNets), which enables users to effectively manage and control complex networking configurations and multitenancy setups directly from the web interface at the datacenter level. Use cases for SDN range from an isolated private network on each individual node to complex overlay networks across multiple Proxmox VE clusters on different locations. The benefits result in a more responsive and adaptable network infrastructure that can scale according to business needs.
  • New Flexible Notification System: This release introduces a new framework that uses a matcher-based approach to route notifications. It lets users designate different target types as recipients of notifications. Alongside the current local Postfix MTA, supported targets include Gotify servers or SMTP servers that require SMTP authentication. Notification matchers determine which targets will get notifications for particular events based on predetermined rules. The new notification system now enables greater flexibility, allowing for more granular definitions of when, where, and how notifications are sent.
  • Support for Ceph Reef and Ceph Quincy: Proxmox Virtual Environment 8.1 adds support for Ceph Reef 18.2.0 and continues to support Ceph Quincy 17.2.7. The preferred Ceph version can be selected during the installation process. Ceph Reef brings better defaults improving performance and increased reading speed.

By following this guide, you’ll be able to set up a robust server virtualization management platform on your Raspberry Pi 5, ready to take on a diverse set of tasks. This installation will significantly enhance the capabilities of your device, making it a valuable tool for your computing needs.

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Building a Raspberry Pi 5 retro emulation games console

Building a Raspberry Pi 5 retro emulation games console

The Raspberry Pi 5 has arrived, and it’s making waves among enthusiasts of classic video games. This new addition to the beloved line of miniature computers brings with it a host of powerful features that are sure to delight those looking to recreate the magic of retro gaming. Despite its small size, the Raspberry Pi 5 packs a punch with significant enhancements that elevate the gaming experience.

At the heart of the Raspberry Pi 5 is a robust quad-core Broadcom ARM v8 Cortex-A76 processor, which operates at a speed of 2.4 GHz. For those who crave even more power, the processor can be overclocked to an impressive 3.1 GHz. This increase in processing capability is complemented by the Broadcom VideoCore 7 GPU, which supports 4K video at 60 frames per second. These advancements are particularly appealing to gamers and multimedia enthusiasts who demand high-quality performance.

When pushing the device to its limits, especially through overclocking, it’s wise to use an active cooling system to prevent overheating. The Raspberry Pi 5 is available in two models: one with 4 GB of RAM priced at $59.99, and another with 8 GB of RAM for $79.99. This pricing strategy provides options to suit different preferences and financial considerations.

Building a Pi 5 retro gaming console

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The emulation capabilities of the Raspberry Pi 5 are noteworthy. It can handle more complex gaming systems that were challenging for earlier models, such as the GameCube, Nintendo Wii, Nintendo Switch, and PlayStation 2. For example, Sega Saturn games can now run smoothly at 60 frames per second without any modifications, which is a testament to the device’s improved performance.

Dolphin Emulator

When it comes to emulating GameCube games using the Dolphin emulator, the results can vary. Some games run well, while others may not perform as expected. PlayStation 2 emulation also shows mixed outcomes, which can depend on the specific game and the emulator settings used. However, Sega Dreamcast and Sony PSP games generally run well on the Raspberry Pi 5, although the most demanding titles might stretch the device to its limits.

Arcade game emulation is another area where the Raspberry Pi 5 shines. Games like Killer Instinct and the Cave CV1000 series of bullet hell shooters run quite well, with only occasional minor hiccups. This is particularly impressive considering the device’s cost-effectiveness. The Raspberry Pi 5 offers an appealing mix of power and affordability for those passionate about retro gaming. While there are more powerful mini PCs on the market that may surpass the Raspberry Pi 5 in certain respects, this device stands out as a versatile and economical option for those who want to enjoy classic games.

It’s a piece of technology that promises to deliver hours of nostalgic fun to both seasoned gamers and those new to the world of game emulation. For those looking to expand their setup, options like SSD storage solutions and custom cases are available to enhance the Raspberry Pi 5’s capabilities. Whether you’re building a desktop PC, a tablet, or a dedicated gaming machine, the Raspberry Pi 5 is a solid foundation for a variety of projects. And with the right software, the possibilities are virtually endless.

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Easy way to run speedy Small Language Models on a Raspberry Pi

Easy way to run a speedy Small Language Model on a Raspberry Pi

Imagine transforming your Raspberry Pi into a smart conversational partner. If you have tried previously to run AI models on your Raspberry Pi been disappointed with the speeds of its responses. You will be pleased to know that there is a faster way, by installing a small language model, which can turn your mini PC into a miniaturized AI chatbot. In this article, we’ll walk you through the process of setting up the Tiny LLaMA 1.1 billion chat version 1.0 on your Raspberry Pi. This model is tailored to work within the modest power of the Raspberry Pi, making it an ideal choice for those looking to experiment with language processing without needing a supercomputer.

First things first, you’ll want to make sure your Raspberry Pi is fully updated. Having the latest software is crucial for a hassle-free installation. You’ll be cloning a specific version of the llama.cpp repository, which is a necessary step to ensure everything runs smoothly. Compiling this code is a key part of the setup, as it gets your Raspberry Pi ready to handle the language model.

Once your device is prepped, it’s time to download the Tiny LLaMA 1.1 billion chat version 1.0. This model has been trained on diverse datasets and is designed to be efficient. Understanding the model’s training, architecture, and the data it was trained on will help you grasp what it can do and its potential limitations.

Running AI models on the Raspberry Pi

Check out the fantastic tutorial created by Hardware.ai below to learn more about how you can run small language models on a Raspberry Pi without them taking forever to answer your queries. Using TinyLLaMA loaded onto Raspberry Pi using a simple barebones web server for inference.

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The real magic happens when you fine-tune the model’s quantization. This is where you balance the model’s size with how fast it processes information. Quantization simplifies the model’s calculations, making it more suitable for the Raspberry Pi’s limited power.

AI Raspberry Pi

To make sure the model is performing well, you’ll need to benchmark it on your device. You may need to adjust how many threads the model uses to get the best performance. While attempts to speed up the process with OpenBLAS and GPU support have had mixed results, they’re still options to consider. Initial experiments with lookup decoding aimed to speed up the model, but it didn’t quite hit the mark. Trying out different quantization methods can shed light on how they affect both the speed and the quality of the model’s output.

After you’ve optimized the model’s performance, you can set up a simple web server to interact with it. This opens up possibilities like creating a home automation assistant or adding speech processing to robotics projects.

But don’t stop there. The Raspberry Pi community is rich with tutorials and guides to expand your knowledge. Keep learning and experimenting to discover all the exciting projects your Raspberry Pi and language models can accomplish together, such as building a DIY arcade joystick or creating a wearable augmented reality display.

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