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Last week was a biggie for those of you into tech conferences. First and foremost, of course, there was the 2025 iteration of the Silicon Valley-located Embedded Vision Summit, for which I have both personal interest and professional association. In parallel (and in Taiwan), a “little” computer conference called Computex was going on. And from a single-company-sponsored event standpoint, there were two dueling ones: Google with I/O in Mountain View, CA, which I’ll cover in my next post, and Microsoft, with Build in Seattle, WA, which I’ll detail today.

2024 launches

To begin, however, I’ll rewind two weeks further in the past. Revising my previous year’s (2024) Build coverage, you’ll note as I did at the time that this was the first time Microsoft launched new generations of the consumer-tailored versions of its various Surface family mobile computer products that exclusively leveraged Qualcomm’s Snapdragon X Arm-based SoCs.

And equally, if not more notable, last year was also the first time Microsoft added Arm-based variants to its “For Business” Surface product portfolio:

2025 launches

Fast forward to early May 2025 and, for some unknown reason, Microsoft decided to decouple its new-hardware unveilings from the main Build event, releasing the earlier announcements on May 6. Once again there were Arm-only Surface systems for consumer:

and business users:

Although this time, there weren’t any full-generation upticks. Instead, portfolio expansion and cost reduction (the latter aided by broader product line tweaks, albeit tempered by looming tariff-induced potential price increases) came to the fore. The Surface Pro is now available in both legacy 13” and new 12” form factors, while the Surface Laptop now comes in both legacy 13.8” and 15” and a new 13” size. Both newcomers are more svelte than their precursors: 0.61” versus 0.69” and 2.7 lbs. versus 2.96 lbs. for the Surface Laptop, and 0.30” vs 0.37” and 1.5 lbs. vs 1.96 lbs. (in both cases absent the optional keyboard case) for the Surface Pro.

The Surface Laptop’s hardware

I’d argue that the Surface Laptop’s form factor evolution is the more critical of the two from a competitive standpoint, an opinion which factors more generally into the fundamental reason why I’m devoting so much of today’s writeup to hardware. x86-based systems increasingly seem to me to be an afterthought for Microsoft, despite the fact that AMD and Intel have belatedly caught up with Qualcomm from a neural processor core performance standpoint and thereby gained the right to put the Copilot+ marketing moniker on systems containing their CPUs, too. Why is Microsoft becoming increasingly Arm-centric? Because I’d hypothesize, Microsoft is also becoming increasingly Apple-fixated, as the latter company’s half-decade-back announced transition from x86 to Arm-based Apple Silicon systems bears increasingly bountiful fruit.

The new 13” Surface Laptop pretty clearly has Apple’s MacBook Air in its sights, although whether it’ll actually hit its target (and if so, whether mortally or resulting only in a flesh wound) is less clear. For one thing, it’s based on the 8-core variant of the Snapdragon X Plus, versus the 10-core “Plus” and 12-core “Elite” SoCs found in the slightly larger system (that said, all Snapdragon X variants deliver the same level of NPU performance). The SSD is (slower) UFS in interface, versus NVMe, and tops out at 512 GBytes of capacity. There’s only one DRAM option offered: 16 GBytes. And although the display is only slightly smaller, its image quality specs are more notably diminished: 1920×1280 pixels at 60 Hz versus 2304×1536 pixels at 120 Hz.

The Surface Pro’s hardware

The 12” Surface Pro is similarly processor core count, mass storage capacity, and system memory size-encumbered, as is its display, albeit not as badly: IPS-based with 2196×1464 pixels at 90 Hz versus either IPS- or OLED-based 2880×1920 pixels at 120 Hz. That said, I concur with Ars Technica’s Andrew Cunningham; the return of the first few Surface Pro generations’ flimsy keyboard is baffling, especially when it had just been further reinforced with last year’s offering. Both new systems drop the proprietary Surface Connect port in favor of USB-C, curiously dispensing with MagSafe-like magnetic-connector charging capabilities in the process (I’m guessing the European Union might have had a little something to do with that decision).

Big picture, Microsoft is seemingly increasingly confident in Windows 11 Arm64’s Prism x86 code virtualization foundation’s robustness. Nobody (including me, repeatedly) was realistically saying so just a few years ago, but by focusing development attention on 64-bit- and Windows 11-only emulation, the Prism team has made tangible progress since then. I’ve got three Windows 11 Arm64-based systems here, and rarely do I encounter a glitch anymore (that said, I’m not a gamer). Further improving the situation, not only from inherent compatibility but also performance and power consumption standpoints, is the increasing prevalence of Arm64-native application variants (such as Dropbox: yay!). And the “dark cloud” of looming lawsuits between Arm and Qualcomm that I’d mentioned a year ago, thankfully, also dissipated a few months back.

AI-related announcements

Early May wasn’t all about hardware for Microsoft. The company also unveiled a raft of Copilot+-only new and expanded capabilities for Windows 11. And two weeks later, this trend extended even more broadly into Microsoft’s operating system and applications with numerous AI-related announcements at Build. Examples included:

• Web app “hooks” via the Edge browser into on-device deep learning models
• Open-source model support via another set of “hooks”, Windows AI Foundry and its local inference runtime, Windows ML

• Embrace of the Model Context Protocol (MCP), initially unveiled by Anthropic, enabling developers’ AI apps and agents to talk to other apps, web services…even Windows itself

• An AI coding agent offered by Microsoft-owned GitHub
• And even AI “actions” built into File Explorer

Microsoft also revealed a new command-line text editor, an open-source transition for the Windows Subsystem for Linux (WSL), and encryption algorithm enhancements, for example. That said, much of the rest of the keynote (at least; I wasn’t there so can’t speak to the training sessions), was rife with AI technobabble, IMHO, from both Microsoft execs and invited notable guests, complete with innumerable mentions of the “agentic web” and other trendy lingo.

Watch it yourself, or not

See below if you’re up for a slog through the entire 2 hours of oft-tedium:

Conversely, if a 15-minute summary is more to your liking, here’s The Verge’s take:

And with that, having just passed 1,000 words, I won’t force you to slog through any more of my technobabble As always, I’ll end with an invitation to share your thoughts in the comments!

—Brian Dipert is the Editor-in-Chief of the Edge AI and Vision Alliance, and a Senior Analyst at BDTI and Editor-in-Chief of InsideDSP, the company’s online newsletter.

Related Content

• Microsoft’s Build 2024: Silicon and associated systems come to the fore
• Apple on Arm: How did we get here?
• Apple’s spring 2025 part II: Computers, tablets, and a new chip, too
• Microsoft’s Build 2024: Silicon and associated systems come to the fore

The post Microsoft Build 2025: Arm (and AI, of course) thrive appeared first on EDN.

Bosch Digital Fuel Twin documents the use of renewable synthetic fuels

• Digital Fuel Twin enables digital documentation and provides evidence of climate-friendly fleet operation
• The Bosch solution makes all important data on fuel properties and quantities used available via the cloud.
• Digital Fuel Twin paves the way for combustion vehicles to run on carbon-neutral fuels.

Vehicle fleets are a driver of carbon dioxide emissions, particularly for freight forwarders and transport companies. Opting to use renewable synthetic fuels can greatly reduce their carbon footprint – but documenting this, say for sustainability reports, is a challenge. That’s precisely where Bosch’s Digital Fuel Twin comes in: this software solution, integrated into the vehicle, records the use of climate-friendly fuels and documents the reduced carbon emissions. “Bosch’s Digital Fuel Twin makes it easy for companies to prove that they’re using renewable synthetic fuels,” says Thomas Pauer, the president of Bosch’s Power Solutions division. “It gives them auditable proof of the quantities and the carbon footprint of the fuel used per vehicle, which they can then use in their reporting.” In this way, companies not only comply with ever increasing reporting obligations, but can also document their environmental awareness. The Digital Fuel Twin is currently being used on the Tour d’Europe for the first time, which will also stop off at Bosch in Feuerbach on May 28. This rally to Brussels will see a fleet of cars and trucks with combustion engines refueling exclusively with renewable synthetic fuels at public filling stations as they make their way across Europe

“Bosch’s Digital Fuel Twin makes it easy for companies to prove that they’re using renewable synthetic fuels. It gives them auditable proof of the quantities and the carbon footprint of the fuel used per vehicle, which they can then use in their reporting.“
Thomas Pauer, the president of Bosch’s Power Solutions division

A further field of application for the Digital Fuel Twin would open up in the event that it becomes possible to reclassify vehicles with combustion engines as zero-emission vehicles if they use only renewable synthetic fuels. The EU intends to review this option this year. Its current plan starting in 2035 is to fine all manufacturers of combustion vehicles at such a high level as to make it no longer economically viable to sell them. “Renewable synthetic fuels should be a part of the solution. That’s the only way to achieve the climate targets in the transport sector,” Pauer says. “If the EU decides in favor of reclassification, the Digital Fuel Twin can be an important tool in implementing that.”

Purely digital records, plausibility checks, and documentation

The new Bosch software enables the reliable tracking of all a fuel’s climate-relevant properties: from production through all stages of the supply chain to the filling station and into the vehicle. To begin with, manufacturers of renewable synthetic fuels report to Bosch how much fuel they have sold, to whom, and what the fuel’s carbon footprint is. Transport companies in turn report how much fuel they purchased and when. The Digital Fuel Twin compares this data. If the time and quantity match both in the respective company books and with the recorded pump and sensor data of the transfer interfaces, the fuel properties – the type of fuel, its CO2 content, and reduction potential – are passed on in the supply chain. Any carbon emitted during further transportation is reassigned to the fuel – meaning the shorter the distances, the better for the climate. Finally, at the filling station, a “digital handshake” – an exchange of data between the filling station, vehicle, and cloud – documents exactly how much and what kind of fuel was purchased. Identification is carried out using, for example, a fleet management system. This database provides users of the Digital Fuel Twin with reliable information about the CO2 values of the fuel used as well as auditable proof of use. The fuel data is always mapped digitally as a virtual twin in a protected data room in the cloud. Bosch’s software solution can be used in cars, trucks, and buses, but also in construction vehicles and even ships.

The Digital Fuel Twin is currently undergoing testing in collaboration with many participants along the entire fuel supply chain. The system’s reliability and safety is being tested together with them and with vehicle manufacturers. To date, the Digital Fuel Twin has been retrofitted into vehicles. In the future, however, the plan is to integrate it into the vehicle’s own electronics as a pure software module, thereby ensuring the tamper-proof use of renewable synthetic fuels at the individual vehicle level. “We expect the Digital Fuel Twin to feature in production vehicles as early as 2026,” Pauer says

Renewable synthetic fuels have been available for many years

Renewable synthetic fuels are produced either from plant-based materials or with the help of renewable electricity. In contrast to fuels based on crude oil, they do not release any additional carbon dioxide into the atmosphere. Some of these fuels have been available for years. The most widely used is HVO100 (100 % recycled hydrotreated vegetable oils), which is obtained from waste oils and plant residues. Overall – taking into account the carbon emissions of the fuel itself plus the carbon emitted during its production (“well-to-wheel”) – this diesel fuel offers a CO2 advantage of up to 90 percent compared to its crude oil counterpart. Sales of this fuel have been freely permitted in Germany since 2024, but it has been available for much longer in countries such as Sweden and the Netherlands. For gasoline engines, there is also the ethanol-based fuel E85. Both fuels, HVO100 and E85, are each already available at more than 5,000 filling stations across Europe.

The post Providing seamless proof of sustainability appeared first on ELE Times.

Delta, a global leader in power management and smart green solutions, today unveiled its comprehensive solutions for the AI era with a focus on sustainability under the theme “Artificial Intelligence x Greening Intelligence.” The showcase features the newly launched AI containerized data center solution designed for edge computing. This 20-foot container, which integrates power, cooling, and IT equipment, is on display at Delta’s booth and drawing significant visitor interest. Delta is also announcing new certification for the in-rack CDU solution for NVIDIA GB200 NVL72, delivering more solutions for in-rack cooling for NVIDIA’s customers.  In response to the growing power demands of AI computing, Delta also introduces an innovative 800V High Voltage Direct Current (HVDC) power architecture solutions for AI data centers, along with a microgrid solution that enhances grid resilience. With its comprehensive developments in grid-to-chip power and thermal management solutions, Delta aims to optimize energy efficiency in the AI era and enable a sustainable AI future.

Ping Cheng, Delta’s Chairman and CEO, said, “With the rapid expansion of AI applications, industries worldwide are facing the dual challenge of meeting computing demands while maintaining sustainability. As a global leader in power and thermal management, Delta strives to enhance the energy efficiency of its products and optimize power architectures to reduce the stage of energy conversion and minimize total energy loss. For enterprise users looking to adopt AI, we also address the need for rapid and simplified deployment by offering a highly integrated containerized data center solution, including for NVIDIA GB200 NVL72. Through innovative technology, Delta is helping drive the development of sustainable AI.”

Power Solutions and Thermal Management for AI Data Centers

Benjamin Lin, President, Delta Electronics India said, “As India rapidly advances toward becoming a global technology and data hub, the demand for energy-efficient, AI-ready infrastructure is accelerating. Delta’s containerized data center and HVDC solutions represent our commitment to driving digital innovation while ensuring sustainability at scale. These next-generation technologies not only empower faster deployment and lower operational costs, but also align with India’s green data center and Digital India missions. We are proud to contribute to building a resilient digital future, where high-performance computing and clean energy solutions go hand in hand.”

As part of its HVDC solution, Delta showcases its Core Shell Liquid-Cooled Busbar and HVDC Air-Cooled Busbar, supporting up to 50VDC/8000A and 800VDC/1000A power capacity to ensure stable system operation. In advanced liquid cooling, Delta’s liquid-to-liquid cooling systems can provide up to 1,500 kW of cooling capacity. Delta also features rack-level coolant distribution units (CDUs) with cooling capacity up to 200kW, along with liquid-cooled cold plate modules designed for GPUs and CPUs, delivering robust thermal support for next-generation chips.

ICT and Energy Infrastructure Solutions for AI Data Centers

Kelvin Huang, VP and General Manager of Delta’s ICT Infrastructure Business Group, said, “In response to the high power consumption and high-density computing demands of AI servers, we showcase our AI containerized data center solution. Compared to traditional data centers, it can be deployed within weeks, significantly shortening construction time and reducing costs. It allows flexible deployment in remote areas, making it ideal for AI computing, enterprise edge nodes, and telecom facilities.”

Additionally, Delta also highlights that data centers are rapidly adopting microgrids and renewable energy solutions. With key technologies such as hydrogen energy and energy storage, Delta can integrate diverse power sources and dynamic load demands. Through intelligent energy dispatching, Delta’s solutions enable optimal energy allocation and stable power supply.

The post Delta Presents Comprehensive Solutions for AI Data Center with Containerized Data Center & HVDC Power Solution at COMPUTEX 2025 appeared first on ELE Times.

While autonomous technology, the electric vehicle (EV) and increasing expectations of environmental sustainability and fuel economy change the nature of the automotive industry, CFD (Computational Fluid Dynamics) remains the heart of these technologies: an instrument of great power that allows an engineer to model, analyse and optimise fluid flows inside and outside of automobiles. This article discusses, in detail, the latest developments in automotive CFD, where CFD is applied, and in what new ways the scope is being stretched, and also delves on the key contribution Cadence has made toward breaking the frontiers of automotive simulation and design Cadence being the world leader in computational software.

Why CFD is Important in Automotive Design

CFD involves the numerical simulation of fluids flows by employing mathematical models and computational algorithms. In the automotive sector, CFD is used extensively in the modeling of airflow over the vehicle body, thermal management systems, engine cooling, aerodynamics, underhood airflow, HVAC etc. Being able to recreate complex fluid behaviors virtually offers a lot of advantages. It can help cut costs on building physical prototypes, speed up the design process and lead to better vehicle performance and efficiency. Plus, it can make rides more-comfortable and safe for passengers, all while shortening the development time.

Major Uses of CFD in the Automotive Sector

1. Aerodynamic Optimization

Shaping the vehicle to minimize drag and save fuel.

Reducing wind noise and lift forces for better ride quality and handling.

Optimization components like spoilers, grilles and underbody panels.

2. Thermal Management

Modeling airflow in the engine compartment to achieve best cooling.

Regulating battery temperatures for electric vehicles.

Improving cabin climate control and occupant comfort.

3. Combustion and Powertrain Simulation

This involves the modeling of air-fuel mixture and vehicles using I/C (Internal            Combustion) engines.

Simulating and analyzing lubrication and heat-dissipation in engine components.

4. EV and Battery Cooling

Cooling lithium-ion battery packs in a uniform manner to avoid further degradation and ensure safety.

Cooling inverter and electric motor loadings.

5. HVAC and Cabin Comfort

Modeling air distribution and temperature control within the cabin.

6. Water and Contaminant Management

Predicting the interaction between rain, snow or dirt with a car exterior.

Ensuring visibility to drivers and protection of sensitive components.

Technological Developments in Automotive CFD

With greater computational power comes the need for punishingly extended computations with highly detailed simulations, the domain of CFD is quickly changing with time. Few trends are:

High-Fidelity Simulation Modern solvers can tackle huge simulations with high mesh resolutions to give detailed insights into complex mechanisms such as turbulence, transient flows.

Machine Learning and AI Integration AI algorithms have been extended to predict fluid performance, optimize design parameters and automate parts of CFD workflow, thus reducing turnaround time.

Cloud Computing and HPC (High Performance Computing) Cloud-based simulation platform rendered CFD scalable and cost effective while speeding-up iterations and collaborative work among dispersed teams.

Digital Twins CFD plays a critical role in creating digital twins- virtual representations of physical systems that monitor, simulate and optimize performance dynamically.

Multiphysics and System-Level Simulation Integrating CFD with other physics disciplines such as structural, thermal and electromagnetic simulation allows for comprehensive system-level optimization.

With the automotive sector under transformation due to electrification, autonomy and sustainability, very high-fidelity fluid simulations are now in demand. Several big names like ANSYS, Altair, Cadence Design Systems have moved into leadership in computational fluid dynamics (CFD), each with a set of capabilities all their own.

How Cadence is shaping Automotive CFD

Cadence Design Systems, once considered and electronics design automation (EDA) powerhouse, now includes system-level modeling, including CFD, with acquisition of NUMECA and Pointwise. Since then, they have continuously expanded their CFD offerings into a powerful suite, disrupting how automotive engineers think fluid simulation.

Key Offerings of Cadence Automotive CFD

• Fidelity CFD Platform The Cadence proprietary CFD platform – Cadence Fidelity CFD, gives a complete and accurate solution for simulating complex fluid dynamics in automotive and aerospace systems. Included are the following capabilities:

-Unstructured and structured meshing (via Pointwise)

-Advanced turbulence models (RANS, LES DES)

-High-order numerical solvers

-Multi-domain and multi-physics simulation

-Automated workflows for design exploration

• Omnis Simulation Environment Cadence’s Omnis environment binds different simulation technologies into a single platform. It supports aerodynamics, acoustics, combustion and multiphase flows with AI-based mesh generation and user-friendly automation.
• Superior Meshing Using Pointwise Quality of meshing is vital to obtaining a good CFD solution. Pointwise offers the best meshing tools in the industry, with high-quality hexahedral and hybrid meshes to guarantee accuracy even for the most challenging automotive geometries.
• Faster Experiments with HPC and Cloud Link using Cadence CFD tools, big tests can run very fast because these tools are made to work well with HPC systems and easily use extra space in the cloud. This helps learn new things quickly while making designs.
• Works with ECAD for Electronic Cooling as cars get more electric wiring it is very important to keep parts like ECUs and power electronics from getting too hot. Cadence helps link ECAD and CFD which makes it easier to check electronic cooling.

Real-World Impacts

CFD tools provided by Cadence are being adopted by leading automotive OEMs and suppliers the world over. Some of them are:

• Reducing aerodynamic drag of next-generation electric vehicles
• Optimizing thermal management systems in battery electric buses
• Stimulating underbody airflow for race cars
• Managing cabin comfort and HVAC systems in luxury sedans

Challenges and The Road Ahead

Yet, all the advances still come with challenges:

• CFD simulations remain expensive, in terms of computing requirements and also time-consuming.
• Accurate representation of turbulence and multi-phase flows continues to be one intricate problem.
• Interdisciplinary collaboration between thermal, mechanical and electronic teams needs better integration.

However, companies like Cadence are actively working to address these gaps through Mesh refinement and solver tuning driven by AI, End-to-end automation of CFD workflows, Better user interfaces and learning tools for new users.

Conclusion:

CFD goes far beyond being just a means of simulation; it acts as a stepping stone toward innovation for the automotive industry. The whole new paradigm that CFD helps realize sits downstream of energy efficiency and safety improvements-for growing and realizing a modern-day vehicle design with the right set of parameters.

Cadence is playing a key role in CFD development through its development of next-generation Fidelity CFD, intelligent meshing, and integrated simulation environments. As the industry goes toward a more sustainable and connected form of mobility, CFD will become more inseparable, keeping Cadence ahead of the computational curve.

The post Designing the Drive: CFD as the Engine of Automotive Innovation appeared first on ELE Times.

At the IEEE’s 75th Electronic Components and Technology Conference (ECTC 2025) in Dallas, TX, USA (27–30 May), nanoelectronics research center imec of Leuven, Belgium is highlighting the performance and flexibility of its 300mm RF silicon interposer platform, which enables seamless integration of RF-to-sub-THz CMOS and III/V chiplets on a single carrier, achieving a record-low insertion loss of just 0.73dB/mm at frequencies up to 325GHz. This is said to pave the way for compact, low-loss and scalable next-generation RF and mixed-signal systems...

I've been hacking away lately, and I'm now proud to show off my newest project - The Icepi Zero! In case you don't know what an FPGA is, this phrase summarizes it perfectly: "FPGAs work like this. You don't tell them what to do, you tell them what to BE." You don't program them, but you rewrite the circuits they contain! So I've made a PCB that carries an ECP5 FPGA, and has a raspberry pi zero footprint. It also has a few improvements! Notably the 2 USB b ports are replaced with 3 USB C ports, and it has multiple LEDs. This board can output HDMI, read from a uSD, use a SDRAM and much more. I'm very proud the product of multiple weeks of work. (All the sources are at https://github.com/cheyao/icepi-zero under an open source license :D) submitted by /u/cyao12 [link] [comments]

I opened up my Eizo EV2316W and soldered two connections to the secondary stage of the internal power supply. Then, I connected a USB-C power supply and injected 15V DC — and it works! Now I can add a USB-C port and a PD trigger to power the monitor using a power bank. submitted by /u/Malsate [link] [comments]

Scintil Photonics of Grenoble, France (a fabless firm developing and commercializing silicon photonic integrated circuits with integrated lasers for AI data centers) has appointed Jim Theodoras as VP of product development. This strategic hire comes, as the firm scales operations to support exponentially increasing volume demands for advanced photonics in AI data centers...

submitted by /u/chanuth360 [link] [comments]

Semiconductor laser diodes (SLDs) are often packaged with a photodiode. The output current from this photodiode can be monitored to regulate the output power intensity of the laser diode. SLDs, however, are prone to pathological drifts, such as temperature variations and mode-hopping, that can alter the output intensity. A popular approach to stabilize the output intensity is to first convert the photodiode current to voltage. This voltage can then be read by a microcontroller, where logic can be programmed to adjust the current supplied to the laser diode. This method is illustrated in Figure 1.

Figure 1 Using a microcontroller to regulate laser diode output power by sensing photodiode current.

Wow the engineering world with your unique design: Design Ideas Submission Guide

Figure 2 provides an alternative implementation that uses a single operational amplifier. When the circuit is powered on, there is initially no photodiode current. The voltage at the positive input of the op-amp is pulled to VCC, and the op-amp powers the laser diode. This induces current in the photodiode, which creates a voltage drop across R1, setting the positive input of the op-amp to: Vcc – Iphotodiode ∗ R1.

Figure 2 A single op-amp solution using negative feedback to provide output power regulation.

The op-amp buffers this voltage and feeds it to the laser diode. The system stabilizes at an operating point determined by:

1. The laser diode’s VI-intensity curve
2. The coupling efficiency between the laser diode and photodiode
3. The current-intensity response of the photodiode
4. R1

Thereafter, negative feedback stabilizes any variations in output intensity. If the laser intensity increases, the photodiode responds by generating a higher current, which in turn creates a larger voltage drop across R1. This reduces the output voltage of the op-amp, subsequently decreasing the laser intensity. The opposite behavior is seen with a drop in laser output power.

This circuit was built on a breadboard using the OPV314 850-nm VCSEL and the OPA551P op-amp from Texas Instruments (Figure 3). R1 was set to 68 kΩ, and VCC was set to 5 V.

Figure 3 Components assembled on a breadboard using the OPV314 850-nm VCSEL and the OPA551P op-amp.

The oscilloscope trace captured from the positive node of the op-amp is shown in Figure 4, demonstrating the stable output from the laser (arbitrary units). R1 can be used to control the output power intensity.

Figure 4 Oscilloscope trace of positive node of op-amp (proxy for output laser intensity).

Anirban Chatterjee is a biomedical engineer with 10 years of experience in the consumer electronics industry. He holds a master’s degree in electrical engineering and is a member of IEEE. He holds a keen interest in biomedical sensors and associated signal processing techniques.

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• LASER Diode – How it Works
• Debugging with a LASER
• Looking inside a laser measurer

The post A single op-amp solution to stabilize laser output appeared first on EDN.

Just add a bit of epoxy and you're done. submitted by /u/ThermionicRectifier [link] [comments]

The embedded systems landscape is evolving rapidly in demand for AI/ML capabilities, real-time data processing and security, coasting microcontroller manufactures down a path to deliver solutions that perform high on price of power and lower cost. Hence Microchip Technology Inc. the global leader in embedded control solutions, had to rise to the challenge with its latest PIC32A series of microcontrollers.

In an exclusive interview with ELE Times, Pramit Nandy, Product Marketing Manager at Microchip’s dsPIC Business Unit, focused on motor control applications and having earned a master’s degree in electrical engineering from Arizona State University, discusses key insights into technological innovation, market strategies, and applications landscape for PIC32A MCUs.

ELE Times: What prompted the launch of the PIC32A series of MCUs? Was it based on specific market demands or technological trends?

Pramit: The launch of the PIC32A series of MCUs was prompted by specific market demands and technological trends, including the need for advanced processing capabilities for complex algorithms and data management, high-speed analog peripherals for precise measurements, robust safety and security features driven by automotive, industrial, and consumer segments, and the ability to handle software complexity with model-based designs.

ELE Times: How does the addition of 64-bit FPU enhance PIC32A MCU applications in AI/ML? Could you share any use cases or test data?

Pramit: The integration of a 64-bit Floating Point Unit (FPU) in the PIC32A MCU, operating at 200MHz, can help enhance AI/ML applications by accelerating complex mathematical operations, improving precision, enabling faster data processing, and supporting more sophisticated neural networks. Additionally, the 72-bit Multiply-Accumulate (MAC) unit in PIC32A MCUs facilitates faster algorithm processing, further boosting the capabilities required to run AI/ML-based algorithms, making it ideal for developing intelligent systems. Potential use cases include real-time data analysis, gesture recognition, predictive maintenance, and autonomous systems.

ELE Times: The PIC32A MCUs integrate a 40 Msps 12-bit ADC, a 5-nanosecond high-speed comparator and a 100 MHz GBWP operational amplifier. How do these devices work together to improve efficiency? How do you balance high-performance analog peripherals with power consumption during design time?

Pramit: The integrated 40 Msps 12-bit ADC, 5-nanosecond high-speed comparator, and 100 MHz GBWP operational amplifier in PIC32A MCUs work together to improve efficiency by enabling fast and accurate signal processing, reducing latency, and enhancing performance. The ADCs support up to 22 channels, enabling rapid and accurate data collection crucial for real-time applications. The DACs with high-speed comparators provide fast and precise signal generation, while the high-frequency op-amps ensure stable and efficient signal processing. The PIC32A family of MCUs are optimized for performance and not for low power consumption. Balancing high-performance analog peripherals with power consumption is achieved by optimizing the use of analog peripherals based on application requirements, leveraging power-saving modes, and efficient design practices.

ELE Times: How do hardware security features such as ECC, MBIST, and I/O integrity monitoring ensure the security of embedded systems? In which application scenarios are these functions particularly critical?

Pramit: Features such as ECC (Error-Correcting Code), MBIST (Memory Built-In Self-Test), and I/O integrity monitoring ensure the security of embedded systems by providing robust mechanisms to detect and correct errors, verify memory integrity, and monitor input/output operations for anomalies respectively. These functions are particularly critical in applications such as automotive systems, medical devices, and industrial control systems, where safety, security, reliability and data integrity are paramount.

ELE Times: The PIC32A MCUs are priced at less than $1 per unit, making them highly competitive in the 32-bit MCU market. How does Microchip achieve such a low cost while maintaining high performance?

Pramit: Microchip achieves low costs for PIC32A MCUs through efficient manufacturing processes, economies of scale, and optimized design that balances performance with cost-effective production.

ELE Times: How do you view the market prospects of the PIC32A MCUs in the coming years? What are Microchip’s market strategies for sectors in intelligent edge sensing, AI/ML and automotive electronics?

Pramit: The market prospects for PIC32A MCUs are promising, driven by increasing demand in intelligent edge sensing, AI/ML, and automotive electronics. Microchip’s strategies include enhancing product performance, expanding software and development tools, and forming strategic partnerships to address these growing sectors.

ELE Times: With the rapid development of IoT, AI/ML and intelligent edge computing, what new technological trends do you foresee in the MCU market, and how is Microchip responding to these trends?

Pramit: With the rapid advancement of IoT, AI/ML, and intelligent edge computing, the MCU market is experiencing new technological trends, including increased processing power, enhanced connectivity, and improved energy efficiency. In response, Microchip is developing MCUs that offer superior performance for efficiently running AI/ML algorithms, robust security features, and support for edge computing as well as IoT applications.

The post Microchip’s PIC32A Microcontrollers Empowering the Next Generation of Embedded Systems appeared first on ELE Times.

Reverse polarity protection is essential in battery-connected automotive systems. So, while reverse polarity is a risky, how do we prevent it? This article delves into reverse polarity protection circuits built around standard and Schottky diodes, as well as high-side P-channel and N-channel MOSFETs. It also offers design ideas on how to implement these protection circuits efficiently.

Read the full article at EDN’s sister publication, Planet Analog.

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• Protecting against reverse polarity: Methods examined, Part 1
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• Schottky barrier rectifier targets power management, reverse-polarity protection applications

The post How reverse polarity protection works to safeguard car battery appeared first on EDN.

Expansion of the Multi Line platform with high-resolution color camera module and oblique view cameras for the inspection of protective coatings (CCI)

Protective coatings ensure the reliability of electronic assemblies. Errors in the coating can therefore have serious consequences for their function. Malfunctions or field failures cannot be tolerated, especially when used under changing climatic conditions and in safety-relevant automotive, military, avionics and telecommunications applications. Painting defects and deviations from the painting plan can now be detected automatically and reliably with the new CCI inspection system from GOEPEL electronic – for the first time simultaneously on both sides, which significantly reduces the inspection time in production.

The new Multi Line CCI for conformal coating inspection (CCI) extends the Multi Line machine platform from GOEPEL electronic. This fully automatic CCI system can inspect both from above and optionally from below. For example, dip-coated assemblies can be inspected on both sides simultaneously without having to turn the assembly over.  Fully automatic return of the assemblies below the inspection level is also possible. The CCI camera module of the Multi Line CCI is equipped with a high-resolution color camera (resolution 8 µm/17 µm), telecentric optics and high-power UV LEDs for illumination from several directions with a wavelength of 365 nm. The camera module can also be equipped with four or eight angled-view cameras in order to inspect connector pins reliably from multiple viewing directions.

The upper component clearance is a comfortable 120 mm; assemblies weighing up to 15 kg can be transported. Inspection can therefore also be carried out directly in product carriers. For seamless protective coating inspection, fluorescent coatings are illuminated by the UV LEDs in the Multi Line CCI. In conjunction with the color camera, the high-resolution, telecentric optics provide high-contrast images and enable inspection within seconds.

Programming the CCI inspection is designed to be extremely user-friendly: The system is set up within a few minutes using CAD data and painting plans. Both the painted and unpainted areas of the assembly are inspected. The new system is based on the Multi Line platform with an operating system and housing optimized for professional production applications. The tried-and-tested Pilot 7.1 operating software now features the new CCI inspection function. This covers all requirements for an all-encompassing protective coating inspection and also enables the import of a painting plan. The overarching hardware and software platform character enables flexible employee scheduling and optimizes the exchange of knowledge within the company, as the AOI is operated centrally and almost identically on all Multi Line systems, without the need for extensive training.

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An Integrated Tool Tailored for Engineers, Enabling Fast AI Model Deployment to MCU

As AI technology rapidly integrates into various embedded systems, how to efficiently deploy trained AI models onto resource-constrained microcontrollers has become a significant challenge for engineers. To help developers quickly implement AI solutions, Nuvoton Technology has launched the NuML Toolkit. This tool integrates model conversion, project generation, deployment, and debugging processes. It is specially optimized for the NuMicro M55M1 microcontroller platform and has received widespread acclaim from users.

The NuML Toolkit offers comprehensive process support, including:

• Model Conversion and Deployment

Automatically converts Full-INT8 quantized models into .cpp files and integrates them into Arm Keil project templates.

• Toolchain Support

Supports both Keil (μVision 5 / Arm Compiler 6) and GNU Compiler Collection (make / gcc).

• High Integration

Automatically opens the Keil project and performs flashing after deployment, enabling immediate inference result viewing.

• Flexible Expandability

Developers can adjust Tensor Arena, input / output handling, and other parameters based on model needs.

• Cross-Platform Support

Uses Miniforge to set up the environment, simplifying dependency management and quickly introducing toolchains.

Three Key Advantages of NuML Toolkit:

1. Fast and Simple Model Conversion

Through command-line operations, users can generate corresponding AI MCU projects with just a few parameters, without writing complex code manually.

2. Integrated Workflow

From model quantization → project building → microcontroller flashing → result verification, the toolkit provides a fully integrated workflow that is easy to use for both beginners and experienced engineers.

3. High Flexibility and Maintainability

The generated Keil project contains a modular code architecture (such as Application, Model, Device), making it easy for customers to modify and maintain according to actual needs. Model management is flexible—large models can be configured to use SD cards or HyperRAM, with memory usage strategies automatically adjusted based on resource allocation.

The NuML Toolkit is a highly efficient tool designed for AI applications on microcontrollers, helping customers complete AI model deployment and validation in the shortest time. It has already been widely applied in applications such as smart desk lamps, posture recognition, sound recognition, image detection, and other scenarios, becoming one of the preferred tools in the Nuvoton NuMicro AI MCU developer community.

The post Nuvoton Launches Highly Efficient AI MCU Deployment Tool “NuML Toolkit” to Accelerate Embedded Intelligent Application Implementation appeared first on ELE Times.

This is an old kid's electronics kit that I modded to a drum machine. It's based on "#106 Digital Rhythm" experiment from here: https://radioshackcatalogs.com/flipbook/m-science_fair_kits_200-in-1_electronic_project_kit_28-249.html It appears to be using flip-flops to count out the beats and then play the "beeps". Main mods I did: added kick drum sound, generated by LED flashing on a solar cell added snare/white noise sound from hacked FM radio module replaced pitch-resistors with pots for control. added filters which are simply capacitors on top of the sound generation. These produce frequency filtering as well as the "pew-pew" pitch-drop effect. submitted by /u/Useful-Bullfrog-730 [link] [comments]

Sivers Semiconductors AB of Kista, Sweden (which supplies RF beam-former ICs for SATCOMs and photonic lasers for AI data centers) has provided additional details on the debt financing with a US-headquartered bank, established to fully refinance the company’s existing debt, while also supporting ongoing growth and financial strategy...

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