Episodios
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In this episode of Embedded Frontier, Jacob Beningo discusses the top trends in embedded systems for 2025. He highlights the increasing role of AI and machine learning, the dominance of open-source software, the critical importance of security, and the ongoing relevance of programming languages like C and C++. Beningo also emphasizes the rise of simulation technologies, the integration of DevOps and observability, and the expansion of edge AI, providing insights into how these trends will shape the future of embedded systems development.
Takeaways· AI will enhance embedded systems development.
· Machine learning applications are still underutilized.
· Open-source software is becoming increasingly dominant.
· Security is a top priority for embedded systems.
· C remains the most widely used programming language.
· Simulation technologies will modernize development processes.
· DevOps practices are essential for improving software quality.
· Edge AI will allow for local data processing.
· Modern programming languages will see increased adoption.
· 2025 will bring significant changes to embedded systems.
Keywordsembedded systems, AI, machine learning, open source, security, programming languages, DevOps, edge AI, simulation technologies
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Curious about the future of embedded systems? In this episode, Jacob Beningo is joined by Shawn Prestridge from IAR Systems to tackle the pressing challenges developers face today. From real-world insights into AI’s role in embedded devices to the overlooked pitfalls of security in connected systems, Shawn shares practical lessons learned from his decades in the field. Whether you’re interested in how AI can transform your development process, or you're navigating the complexities of modern code quality and security, this conversation offers actionable strategies that every embedded developer needs. Don't miss this chance to learn from the cutting edge of embedded systems development.
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In this episode, Jacob Beningo interviews François Baldassari, Memfault CEO, about IoT security compliance demands. They discuss embedded manufacturers' readiness for new security regulations, the challenges they face, and potential solutions.
Embedded manufacturers are not fully ready for new IoT security compliance demands.Regulatory frameworks like the EU's Cyber Resilience Act and the US's Cyber Trust Mark are coming into effect and will require certification of cybersecurity guidelines.Challenges include the uncertainty of the regulations, the additional costs and effort required, and the lack of established infrastructure and best practices.Recommendations for compliance include implementing OTA updates, using open-source software, adopting SBOM scanning, and ensuring observability of devices.AI is not currently a solution for compliance, but it may play a role in the future as more data is collected and analyzed.Joining the conversation around open-source products and following security best practices can help improve device security.
They also explore the differences between the EU's Cyber Resilience Act and the US's Cyber Trust Mark. François emphasizes the importance of OTA updates, using open-source software, and building security teams within hardware companies. He also highlights the need for collecting the right data and observability to improve security posture.
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Summary
In this conversation, Jacob and Daniel Situnayake discuss the future of AI and machine learning in embedded software development. They explore the challenges and opportunities of implementing AI and machine learning at the edge, and how tools like TensorFlow Lite for Microcontrollers and Edge Impulse are making it easier for developers to deploy models on resource-constrained devices. They also discuss the importance of balancing model accuracy with resource constraints and the potential for AI-generated models in the future. Overall, the conversation highlights the growing interest and potential of AI and machine learning in the embedded space.Keywords
AI, machine learning, embedded software development, TensorFlow Lite, Edge Impulse, resource constraints, model accuracy, AI-generated modelsTakeaways
AI and machine learning are being increasingly applied to embedded software development, opening up new possibilities for edge devices.Tools like TensorFlow Lite for Microcontrollers and Edge Impulse are making it easier for developers to implement AI and machine learning on resource-constrained devices.Balancing model accuracy with resource constraints is a key consideration in embedded AI development.The future of embedded AI and machine learning holds the potential for AI-generated models and more sophisticated applications at the edge. -
In this episode, Jacob Beningo discusses the importance of debugging in embedded development and shares several techniques to decrease debugging time. He highlights the statistic that development teams spend 20-40% of their time debugging, which equates to 2.5-4.5 man-months of development. Beningo emphasizes the use of test-driven development (TDD) as a way to prevent bugs and decrease debugging time. He also recommends mastering debugging techniques for microcontrollers, using profiling and monitoring tools, employing assertions, and utilizing on-host simulation. Beningo concludes by encouraging listeners to track their debugging time and implement strategies to decrease it.
Development teams spend 20-40% of their time debugging, which can equate to 2.5-4.5 man months of development.Test-driven development (TDD) can help prevent bugs and decrease debugging time.Mastering debugging techniques for microcontrollers and utilizing profiling and monitoring tools can improve debugging efficiency.Using assertions and on-host simulation are additional techniques to decrease debugging time.Tracking debugging time and implementing strategies to decrease it can lead to increased productivity and innovation.
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Summary
In this episode, Jacob Beningo interviews Frank Herta, the CEO of Curtail Incorporated, about the risks of zero-day attacks in open source software. They discuss the importance of DevSecOps and the need for comprehensive security measures. Frank shares his background in security and how his company is working on detecting zero-day bugs.
They also explore the vulnerabilities of open source software and the potential for third-party supply chain attacks. Open source software testing differs from proprietary software testing in terms of who is responsible for testing. Open source projects have their own testing processes, but it's important for software developers to test the open source software in the context of their own applications.
DevSecOps is a cultural shift that aims to integrate security and testing throughout the software development process. It involves early testing, collaboration between teams, and a focus on security from the beginning. The nature of threats in open source software is changing, with third-party attacks on repositories becoming a major concern. Complacency and slow response times are also issues that need to be addressed.
Developers and managers using open source software should follow security best practices, stay updated on vulnerabilities, and actively test their software. Curtail is working on innovative solutions to analyze and compare different open source packages for better security.Keywords
embedded systems, open source software, zero-day attacks, DevSecOps, security measures, vulnerabilities, supply chain attacks, open source software, testing, proprietary software, DevSecOps, third-party attacks, complacency, response time, security best practices, Curtail
Open source software is prevalent in the industry, with 70-90% of software being open source-based.Companies and their customers are at risk of zero-day attacks due to the widespread use of open source software.Historical examples like Heartbleed and Apache Struts have demonstrated the vulnerabilities of open source software.DevSecOps is crucial for integrating security measures throughout the software development lifecycle.Comprehensive testing, documentation, and active involvement in open source communities can help mitigate security risks.Comparing different versions of open source software and monitoring network behavior can help detect changes and potential vulnerabilities. Open source software should be tested in the context of the specific application it will be used in.DevSecOps is a cultural shift that integrates security and testing throughout the software development process.Third-party attacks on open source repositories are a growing concern.Complacency and slow response times can lead to security vulnerabilities.Developers and managers should follow security best practices and actively test their software.Curtail is working on innovative solutions to analyze and compare different open source packages for better security.
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In this episode, Jacob Benningo discusses the importance of DevOps in the embedded software development industry. He emphasizes the need for DevOps to improve project delivery, efficiency, and product quality. Jacob provides insights into the principles of DevOps, the implementation of CI/CD pipelines, and the impact of DevOps on software development processes. He also shares actionable steps for implementing DevOps in embedded software development.
Takeaways
Embedded DevOps is crucial for improving project delivery, efficiency, and product quality in embedded software development.The principles of DevOps include incremental value delivery, improved collaboration, automation, and continuous improvement.Implementing a CI/CD pipeline is essential for automating software development processes and improving code quality.DevOps transforms how embedded systems are developed, leading to cleaner and more efficient software development processes.Actionable steps for implementing DevOps include defining an ideal pipeline, creating a roadmap, and setting up a DevOps framework for remote software building. -
Carsten Gregerson shares his background in the embedded systems industry and how he got into it. He discusses his work at Nabto, a company that provides remote access to small devices using peer-to-peer technology. Carsten then delves into the topic of real-time operating systems (RTOS) and the battle for open-source RTOS. He explains the difference between a real-time operating system and a high-end operating system and how the introduction of the internet into embedded devices has increased the need for RTOS. He also discusses the consolidation happening in the industry with the acquisition of RTOS by big tech companies. Jacob shares his thoughts on Zephyr, an open-source RTOS, and its place in the market. He also explores the challenges of adopting Zephyr for embedded developers and the potential future of embedded development with the integration of interpreters and AI.
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Summary
This podcast episode discusses using bare metal and real-time operating systems (RTOS) in embedded systems development. It highlights the steady adoption of RTOS in the industry and the continued relevance of bare metal development, particularly in 8-bit microcontrollers. The episode explores the future of RTOS, including the rise of open-source options like Eclipse ThreadX and Zephyr. It also discusses different models for designing RTOS-based applications, such as the independent, dependent, and POSIX interface models. The episode concludes by encouraging listeners to stay informed about RTOS advancements and learn how to architect applications using RTOS effectively.Takeaways
Bare metal development and real-time operating systems (RTOS) are both relevant and widely used in embedded systems development.RTOS adoption has remained steady, with about two-thirds of embedded systems using an RTOS and the remaining third using bare metal techniques.The future of RTOS includes the rise of open-source options like Eclipse ThreadX and Zephyr, which offer commercial-quality RTOS at open-source costs.Different models for designing RTOS-based applications include the independent model, dependent model, and POSIX interface model. -
In this conversation, Max (Clive) Maxfield discusses his journey into embedded systems and the industry's evolution. He highlights the fascinating developments in AI and its impact on embedded systems. Max also explores how AI can benefit embedded software and hardware developers and the potential applications of AI with sensors. He discusses the advancements in semiconductor technology to keep pace with AI. Finally, Max shares recommendations for managers and developers on adopting AI technologies into their development workflows. In this conversation, Max the Magnificent discusses various aspects of AI and its applications in embedded systems and beyond. He emphasizes the importance of understanding the power of data and cloud computing and the potential of generative AI. Max also shares insights on simplifying website chatbots using AI and highlights the need for managers to stay informed about AI advancements. The conversation concludes with discussing the future of AI collaboration and the importance of viewing AI as a tool rather than a replacement.
Embedded systems have evolved significantly over the years, with AI becoming a prominent feature in the industry.AI offers exciting possibilities for embedded software and hardware developers, enabling them to enhance their products and improve efficiency.Sensors are crucial in integrating AI into embedded systems, allowing for advanced functionalities and applications.The semiconductor industry is continuously advancing to meet the demands of AI, with smaller technology nodes and specialized chips.To adopt AI technologies effectively, managers and developers should stay updated on the latest developments, explore available tools and resources, and consider their projects' specific needs and applications. Tiny ML is a valuable introduction to embedded systems and can be used for applications such as predictive maintenance.Data is a crucial asset, and leveraging cloud computing and AI can enhance its value and provide powerful insights.Partnering with companies specializing in AI implementation can help navigate the complexities of AI integration.Generative AI is becoming increasingly prevalent, with applications ranging from chatbots to automated summaries.AI tools like Chat Simple can simplify the process of implementing chatbots on websites.
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In this episode, Jacob discusses trends in the embedded software industry and provides techniques and practices for staying relevant and successful. The trends include leveraging AI to develop embedded systems, improving CI/CD processes, phasing out C for C++ or Rust in 32-bit applications, adopting developer-centric workflows, moving to higher levels of abstraction, and using POSIX APIs in real-time operating systems. The techniques covered are model-based design, containerizing and virtualizing development processes, and adopting DevOps and CI/CD.
Leveraging AI can improve efficiency, code generation, debugging, and code reviews in embedded software development.Improving CI/CD processes can enhance automation, reliability, and deployment of embedded software.Phasing out C for C++ or Rust in 32-bit applications can provide more modern and scalable development options.Adopting developer-centric workflows allows for customization and efficiency in the development process.Moving to higher levels of abstraction enables hardware independence and scalability in embedded software development.Using POSIX APIs in real-time operating systems provides flexibility and portability in application code.Model-based design, containerization, and virtualization are effective techniques for efficient and scalable development processes.Adopting DevOps and CI/CD improves collaboration, automation, and efficiency in embedded software development.
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