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Embedded Systems & Future



Embedded Systems & Future

 In today’s digital world, our life is surrounded by Embedded Systems. From brewing your morning coffee to microwaving your breakfast to driving your car (with its smart digital features), getting to the office where you take an elevator to get to your smart (auto adjustable) desk.

Systems, Embedded in Our Life

From the auto adjustable desk, you use your laptop for work until you tell Alexa to turn off your smart lamps and head to bed — all the while using your smartphones.

Welcome to the world of Embedded Systems.



The devices you use are getting smaller, faster, and smarter every day. It’s all happening due to their tiniest component, a semiconductor “Chip,” embedded inside the device. These microchips are smaller than our fingernails. Moreover, almost all the modern-day embedded devices use these Microchips. It’s hard even to imagine a world without them.

The “Brain” in the System 

The components of embedded systems consist of Sensors to capture the input signals, a Processor (Microcontroller or “Logic”) to manage the sensors, a memory to store the data, and an actuator or the output device to trigger or capture the results seamlessly. It’s quite the same as our human body. We have sensors (like ears, nose, eyes, etc.), a “Brain” to Process and Memorize, and the rest of our bodies that react.

The semiconductor “Chip” (Microcontroller, Processor & Memory) is the “Brain” of the embedded systems. These semiconductor chips are classified as the “Logic” (also known as Processors) and the “Memory.”

The “Need for Speed”

The newer technologies (such as IoT, Machine Learning, Artificial Intelligence, Big Data, and cloud computing) use complex algorithms and need a high-speed processor and faster memory.

The computation speed and memory requirements are increasing rapidly from supercomputers to smartphones. The first supercomputer, CDC (Control Data Corporation-6600), had a top speed of 40 MHz, which is painfully slow in today’s world.

The first version of a Raspberry Pi (the most straightforward microcontroller, costing less than $50) has a 700-MHz processor. MHz is the ‘clock’ speed of a processor. One million decisions made in a second is one MH. The latest supercomputer can compute 200,000 trillion calculations per second. The iPhone-13 uses an A15 Bionic processor chip having 15 billion transistors.


This also applies to personal computers and laptops. On October 27, 2021, Intel announced its 12th generation processor family, “Core i9-12900K,” the best gaming processor (5.2 GHz), having as many as 16 cores and 24 threads. The new desktop processors reach new heights of multi-threaded performance for enthusiast gamers and professional creators.

Evolution of the next-generation computing

The evolution of advanced semiconductor chips helps devices achieve high-end algorithms. These complex algorithms have been in existence for decades. However, they could not be implemented to their fullest extent in the real world due to the lack of specialized computational tools.

One of the most revolutionary signal processing concepts, the “Fourier Transform” (included in the Top 10 Algorithms of 20th Century by the IEEE) and one of the most critical algorithms used in image processing and telecommunication, has existed for a long time.

Fourier Transform was first discussed in 1805. It’s a mathematical function that transforms a signal from the time domain to the frequency domain. It is a very powerful transformation that gives you the ability to understand the frequencies inside a signal.

However, due to the lack of in-depth computational tools, scientists could not explore it further (until ~1970) or use it in any commercial systems. But now, it’s widely used in image processing and signal processing in many commercial and critical systems (including RADAR & SONAR).

It’s all Happening here, Moore’s law

Gordon Earle Moore is an American engineer and the co-founder and chairman emeritus of Intel Corporation. In 1965, he authored Moore’s law and, using existing data, extrapolated that the number of transistors in integrated circuits (IC) would double about every two years with the reducing costs.

Advancements in the semiconductor manufacturing process (especially the lithography machines) keep Moore’s law alive. In the last few decades, these chips are getting more condensed, efficient, and economical with an increasing number of transistors fabricated in a single monolithic Chip, and the trend continues.





The latest technologies evolve in parallel with the semiconductor “Chip” evolutions. As a result, the embedded systems world is getting advanced, smart, and more affordable.

The semiconductor technology revolution produces high-computational, high-speed processors and faster-access memory semiconductor chips. These revolutions are the reason behind the success of the latest technologies, including smartphones.

The success is because the need for critical and optimized signal processing algorithms evolved the concept of “System on Chip” (SoC), where the entire digital and analog signal processing algorithms are done inside the hardware (semiconductor chip) itself.

SoC has managed to make embedded systems more efficient. In addition, these SoC have helped tremendously in overcoming network incompatibility, integration, and reliability issues in IoT, especially in wireless connectivity and 5G capabilities.

These advancements in semiconductor chips have significantly impacted our human life. Their contribution to medical science, from the most straightforward contactless thermometer to the sophisticated life-saving devices, is vast. These advancements have made a tremendous impact in the medical world.

The Chip Shortage, A Current Problem

In recent years, the world has witnessed high-speed digitization and, further boosted by the pandemic, a massive surge in demand for laptops, smartphones, automobiles, and servers. Unfortunately, this has led to a significant problem: a shortage in the chips that control everything.

In addition, the evolving technologies are more demanding, creating the need for smaller, faster processors and more available memory. It’s almost a chicken and egg problem that works to meet production needs.

The current pandemic impacted semiconductor manufacturing in an unprecedented way. However, smart embedded devices have helped keep life going. Our kids continued their education remotely using chrome books, cameras, and headphones, and many workers continued to work remotely without hiccups.

The role of contactless temperature scanners, smart contact tracing using mobile data, and other technologies played an instrumental role in confining the spread of COVID-19. Without these smart embedded systems devices, our life could have been much worse in the past few years.

The Journey and Evolution of the Semiconductor Chip

The semiconductor chip journey started with the “vacuum tubes.” Ancient computers used vacuum tubes. A vacuum tube is a glass tube with electrodes for controlling electron flow, acting as a switch or an amplifier.

In 1947, the University of Pennsylvania made a computer using vacuum tubes almost the size of a building. In the following years, scientists William Shockley, John Bardeen, and Walter Brattain collaborated to invent transistors, to replace the vacuum tube, offering a more effective way for the computer to process information.


The invention of “Transistors” was a huge milestone and revolutionized semiconductor technology. In addition, it helped in making the integrated circuits smaller, faster, and more affordable. The great researchers “Shockley,” “Bardeen,” and “Brattain” made a considerable contribution to semiconductor research and the development of the transistor and were awarded Nobel Prize in Physics in 1956.

These transistors started getting used in the Integrated Circuits, which are also called “microelectronic circuits,” “microchips,” or “chips.”

The chips are an assembly of electronic components, fabricated as a single unit, in which miniaturized active devices (e.g., transistors and diodes) and passive devices (e.g., capacitors and resistors) along with their interconnections are built upon a thin substrate of semiconductor material (typically silicon).

The resulting circuit is thus a small monolithic “Chip” that we know today.

Chip Manufacturing, Impossible is Past

A chip is a set of electronic circuits where the transistors turn a current on or off. Microchips are made by building up layers of these interconnected patterns of transistors on a silicon wafer. The latest monolithic chips can support more than 100 layers containing a billion transistors each, each aligning at atomic (nanometer), which needs to align with nanometer precision (called ‘overlay’).

The manufacturing process of these semiconductor chips has several steps. Using various automation processes, it can take months from design to mass production in the cleanrooms of the chipmakers’ fabs (fabrication facilities). There are four unique phases in production.

Design Phase: Circuit Design

Development Phase:  Printing circuit to a Silicon wafer

Pilot Phase:  Critical Production criteria (based on the overlay, critical dimensions, etc.) matching

Mass production Phase: The primary focus is to maximize the yield and minimize the loss (failures) for commercial viability

The Game Changer, EUV Lithography

Lithography is when a light source is used to print tiny patterns of devices, including transistors on silicon. It is a fundamental step in a mass-producing microchip. Lithography machines where the hardware meets software provide a holistic approach to mass-producing patterns on silicon. This machine is one of the most complex machines globally, which has evolved tremendously in the past few decades.

ASML (ASML Holding NV) is the market leader in the DUV (Deep Ultraviolet) lithography machines and the only maker of the next generation EUV (Extreme Ultraviolet) lithography machines in the world.

These machines are so complex (almost the size of a bus), with over 100,000 components and around a mile’s length of cable, all assembled to make a giant lithography machine costing more than $150 million per machine.

The precision of these machines is in the nanometer range. For example, ASML uses DUV machines with a precision of around 200 nanometers wavelength. There are only a few DUV manufacturers (Nikon & Canon) other than ASML.

In addition, ASML has been playing an instrumental role in meeting the challenging demand for the latest technologies and keeping Moore’s law alive. For example, ASML’s EUV lithography machine is the next-generation high-resolution lithography machine that made a revolutionary change in achieving a 10-nanometer (almost X-ray range) precision wavelength, something unprecedented in most cases.

ASML invested more than 17 years and approximately 6 billion euros in research and development in making the EUV lithography machines. These EUV machines manufacture sophisticated microchips. The EUV machine is directly benefitting all human beings.

These microchips are used in all the latest smartphones, gaming consoles, smartwatches, and other high-end embedded devices.



 The Future is here, EXE Lithography Machines

ASML is working on its next generation of EUV lithography (EXE) machine, which will open the door for a smarter digital world in future decades. Intel and ASML are working together to make it a reality as soon as 2025, and they’ve managed to offer EUV production with numbers that were not possible before.

Above all, the EXE EUV machine would reduce the costs and energy needed to manufacture this chip. This machine also offers to scale at an affordable pace, well into the oncoming decade. This machine has a higher resolution that will enable 1.7x smaller chip features and 2.9x increased chip density.

The number of process steps will reduce significantly with this platform, which is a solid motivation to adopt the technology. In addition, it will significantly reduce defects, costs, and cycle time.



Epilogue, Techno-Logical

The entire world of technology is evolving in a feedback loop. For example, the need for faster and more efficient hardware (logic & memory chips) used in the latest technology drives the “Chip” fabrication industry.

And the advancement in semiconductor chip manufacturing further pushes the latest technologies forward. For example, the latest (EXE) lithography machines use the most sophisticated semiconductor “chips,” fabricated using the earlier generation Lithography (DUV/EUV) Machines.

The semiconductor “Chip” (logic & memory) advancements are shaping future technologies. While most of this will depend on how efferently we continue to advance the chip manufacturing industry. These challenges could bring about future technology up to this point unprecedented.

We see a significant evolution happening faster than ever before, creating an “industrial revolution” in Embedded Systems.

Disclaimer: Opinions expressed are the author’s own and not the views of his employer.

Inner Article Image Credit: Provided by the Author; Thank you!

Top Image Credit: Jeremy Waterhouse; Pexels; Thank you!

Kishore Ranjan

Kishore Ranjan is a Senior Design Engineer at ASML (Wilton-CT, USA), having 20+ years of experience working in Embedded Systems in leading technology companies (Aricent, Nokia, NSN, Samsung, Intel & ASML) across the globe (USA, South Korea, China, Finland, Germany & India).


Fintech Kennek raises $12.5M seed round to digitize lending



Google eyed for $2 billion Anthropic deal after major Amazon play

London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs



Deanna Ritchie

As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations



Deanna Ritchie

As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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