Artificial intelligence (AI) now makes it alarmingly easy to manipulate photos, videos and audio recordings. Whether it is fabricated statements attributed to politicians or misleading images from crisis zones, social media and online platforms are already flooded with so-called deepfakes. The consequences for society and democracy are serious: an increasing number of people are being deceived by such forgeries or are beginning to mistrust even credible sources. Researchers at ETH Zurich have developed a new sensor technology that directly addresses this issue. The concept involves cryptographically signing images, videos or audio signals within a sensor chip at the exact moment they are captured. This signature allows for verification that the data genuinely originate from a camera or recording device, indicates when it was captured, and ensures that it has not been tampered with. “If data is signed the moment it is captured, any later manipulation leaves traces,” explains Fernando Cardes, who co-developed the technology. He is a research associate at Andreas Hierlemann’s Professorship of Biosystems Engineering within the Department of Biosystems Science and Engineering (BSSE) in Basel. “To manipulate the data, the chip would have to be physically attacked, requiring a massive technological effort so that the mass generation of manipulated content for social media platforms would be practically impossible,” he adds. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1776333872274-image.imageformat.1286.329827099.jpg" style="width:100%px" class="fr-fic fr-dib" />How the technology works: a real-world event (1) is recorded by a camera whose sensor chip generates both the image data and a cryptographic signature at the moment of capture (2). Once stored in a public register (3), the signature can later be used to verify that the recording is authentic and has not been altered (4). (Graphic created using AI: Felix Franke / ETH Zurich)<h2>Simple verification thanks to a public register </h2>The signatures generated by the sensor could be stored by camera manufacturers in a publicly accessible, immutable ledger (e.g., a blockchain). This approach would enable anyone to verify the authenticity of the data in question at any time by comparing the chip’s signature stored in the ledger with the original data and confirming its source. “As such, it is barely of any relevance whether a person or the technology involved in data processing and transmission is trustworthy,” explains Felix Franke, who co-developed the chip at ETH Zurich and is now a professor at the University of Basel. “Trust in digital content is eroding. We wanted to create a technology that gives people a way to verify whether something is genuine.” In principle, the technology can be incorporated into any type of sensor or camera. In the future, social media platforms could automatically verify whether the content is genuine as soon as it is uploaded. Where this does not happen, journalists, researchers or public authorities could authenticate content themselves using simple tools. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1776333888604-image.imageformat.1286.1418804681.jpg" style="width:100%px" class="fr-fic fr-dib" />The sensor chip is a prototype that demonstrates technical feasibility.  (Image: Caroline Arndt Foppa / ETH Zurich)<h2>The threat of deepfakes identified at an early stage </h2>The idea behind the sensor chips originated as a side project at the Bio Engineering Laboratory at ETH Zurich. Long before AI systems like ChatGPT became a subject of public debate, the laboratory had been working on highly sensitive sensors to measure electrical signals from living cells. The interdisciplinary team also had the necessary expertise to incorporate additional cryptographic functions directly into the sensor chips. “The danger posed by deepfakes was foreseeable,” recalls Franke. Therefore, as early as 2017, the plan was devised to develop a sensor the data of which could not be manipulated without detection. The chip described in a paper published today is a working prototype and demonstrates technical feasibility. Further steps are still required prior to commercial deployment. Nevertheless, the researchers are confident that, with current technologies and processes, the chip can be developed into a working, market-ready product. They have therefore filed a patent application. “We are currently exploring how to reduce costs for camera and sensor manufacturers should they wish to incorporate the new technology into their chips,” reports Cardes. The work was financially supported by the Swiss National Science Foundation (SNSF) and the State Secretariat for Education, Research, and Innovation (SBFI) through the SwissChips initiative.

Researchers at ETH Zurich have now developed chip technology that enables verification of the authenticity of sensor data, including images or videos.

Chips designed to help identify deepfakes

Semiconductor designs operate under tightly coupled constraints. Device physics, fabrication processes, circuit behavior, layout limitations, and long-term reliability all interact within the same system. A change in one area rarely remains isolated. It quickly influences the rest, like a spiderweb; when you move one node, you always move the entire web somewhat.Engineering progress, therefore, depends less on maximizing a single parameter and more on maintaining balance across the system. This complexity does not stop at the product. It extends into the company that builds it.A deep-tech company that intends to innovate over decades must be structured with similar discipline. Organizational capability, financial sustainability, and engineering expertise evolve together and must remain aligned.At SimpleChips, founder Alain R. Comeau describes this philosophy as Business Tai Chi.The idea reflects a simple principle. Tai Chi teaches that strength emerges from balance rather than force. Business Tai Chi applies the same logic to company building. Success comes from maintaining alignment between the forces that determine long-term resilience.Understanding this philosophy begins with how success itself is defined.<h2>Defining Success as a Balanced System</h2>Business Tai Chi begins with a simple but often overlooked question: What does business success actually mean?In many industries, success is typically expressed through a single dominant metric. Revenue growth, market share, or valuation become the primary reference points for strategic decisions.Deep-tech companies operate within a more complex set of dynamics. Engineering development cycles can span years. Knowledge accumulates gradually through experimentation, design iterations, and real-world deployment. The strength of the organization depends not only on financial performance but also on the expertise of its engineers and the continuity of the systems they develop.SimpleChips approaches success as a dynamically balanced system with three interconnected dimensions: financial sustainability, alignment of personal and organisational values, combined with continuous learning. The continuous flow between these three components and their contribution to the company growth provides a steady business momentum.<h3>1. Financial Sustainability</h3>The first dimension is financial stability. A company must be commercially viable in order to sustain its engineering work. Revenue and profitability provide the foundation that allows technical teams to focus on solving complex problems without constant disruption.Financial sustainability also protects independence. It gives the company the freedom to pursue technically meaningful work rather than reacting to short-term pressures. Being Self-funded and free of external investments, SimpleChips has fewer decision-making strings attached and thus has total freedom to control its destiny. Long-term objectives dominate the decisional landscape; quarter-to-quarter discussions are nonexistent.<h3>2. Personnel Alignment with Company Values</h3>Core Values: Integrity - Innovation - Quality - ServiceThe second dimension concerns values. Engineering organizations depend heavily on judgment and experience. Designers and system architects make decisions that influence reliability, safety, and long-term product performance. These decisions are strongest when backed by science and when the individuals making them believe in the principles guiding the company.At SimpleChips, this value alignment ensures that engineering work reflects a clear sense of purpose. Technical excellence combined with integrity remains central to how projects are approached, managed, and communicated. The company’s core values of Integrity, Innovation, Quality, and Service are very well served by this alignment.<h3>3. Continuous Learning</h3>The third dimension is learning. Every semiconductor project expands understanding of devices, system behavior, and design constraints. These lessons accumulate over time and become a key source of competitive strength.Continuous learning improves future designs, deepens engineering expertise, and strengthens the organization’s ability to tackle increasingly complex challenges. Technical excellence is a demonstration of elevated learning.<h3>A Dynamic Balance</h3>When these three dimensions reinforce each other, the company maintains a stable dynamic center, optimal for moving forward. Financial sustainability supports engineering work (Movement). Value alignment strengthens commitment (Strength). Learning compounds into deeper technical capability (Intelligence). All these contribute to meeting deliverables and consequently to financial stability, closing the loop. This dynamic balance is the foundation of Business Tai Chi, allowing the organization to evolve steadily while remaining grounded in its principles.<h2>Values at the Center</h2>In Tai Chi practice, energy is maintained by keeping the movement intentional. Similarly, a business remains steadfast when its core principles are clear and consistent leading to actions alignment with values. At SimpleChips, values sit at the center of the organization, they shape how and why decisions are made, how opportunities are evaluated, and how the company defines its role in the market.Here, three principles stand out:The first is uniqueness. SimpleChips does not approach semiconductor design as a volume-driven exercise. Its work centers on technically demanding challenges where logic, deep understanding of physics, device behavior, and system interactions can create meaningful value. This orientation naturally leads the company toward specialized problems that reward depth rather than scale alone.The second is fearlessness. In this context, fearlessness is not about speed or bravado but rather about technical conviction. When the underlying science suggests a solution, the path deserves to be explored. This kind of thinking is especially important in complex semiconductor environments, where accepted assumptions do not always define the best solution.The third is independence. Ownership and leadership remain closely tied to the engineering vision of the company. This connection keeps decisions grounded in long-term technical reasoning rather than being controlled by short-term external pressures.These principles reflect M. Comeau’s broader approach to engineering and business. From <a href="https://www.wevolver.com/article/the-human-factor-revisited-engineering-from-first-principles" target="_blank">first-principles thinking</a> to a <a href="https://www.wevolver.com/article/simplechips-a-systems-first-approach-to-high-voltage-ic-design" target="_blank">systems-first view</a> of high-voltage IC design, this mindset shapes how SimpleChips itself is built: as a system that must be designed with a stable center, a clear structure, and well-defined relationships between its moving parts.<h2>Independence and Long-Term Engineering</h2>Business Tai Chi also shapes how independence functions within the company. Deep-tech engineering requires sustained focus over long development cycles. Solutions rarely appear immediately. They flow through iteration, accumulated insight, and careful judgment developed over time. Like a slow-moving Tai Chi artist, the products take form through the energy flow of the people creating it. Work of this kind benefits from organizational independence.SimpleChips has built its model around ownership, autonomy, and direct accountability. Leadership remains closely connected to the engineering work itself, and strategic decisions stay grounded in technical understanding rather than being swayed by external pressure.This structure matters in deep tech. When the people responsible for the engineering also shape the direction of the company, technical judgment remains central to decision-making. Difficult problems can be approached with patience, and solutions can be evaluated on their scientific and engineering merit.Organizational independence preserves the integrity and longevity of the engineering process and allows the organization to pursue technically meaningful work over long time horizons.<blockquote>“In deep technology, time reveals everything. The best solutions survive scrutiny. Companies should be built with the same long-term philosophy.” —Alain R. Comeau, Founder &amp; CEO/CTO at SimpleChips </blockquote><h2>Business Tai Chi: The Human Element</h2>One of the most direct principles behind the SimpleChips philosophy is simple: people are not consumable.In technical organizations, knowledge is carried by individuals but strengthened and remembered through collaboration. Teams accumulate shared experience across projects, customer relationships, develop common judgment about design trade-offs, and build the trust required to navigate difficult engineering decisions with all involved entities. That trust is the glue of success.Business Tai Chi recognizes this trust glues the company’s structure, keeping it in balance. Expertise is not treated as a replaceable input but as a capability that deepens over time.Having a cohesive team reinforces this effect. When engineers remain connected across projects, context is preserved and technical insight travels more effectively between problems. Lessons accumulate and strengthen the organization’s ability to approach new challenges with clarity.Over time, this continuity builds trust both internally and externally. It grows from shared experience, track record, and consistent evidence that technical judgment will be exercised with care. In industries where projects are complex and failure can be costly, that trust becomes a genuine business asset in its own right. When trust reaches and encompasses customers, you have established a seed of lasting credibility.<h2>Corporate-Life Tai Chi</h2>SimpleChips has applied first-principles thinking to engineering and business Tai Chi from the beginning. Its work in high-voltage IC design and ASICs has shown what happens when systems are understood deeply and built with discipline and momentum.Building the company as a system and maintaining balance across the forces that matter most is what has brought SimpleChips its success over its 20+ years of existence. Financial sustainability, value alignment, continuous learning, independence, and human expertise all need to work together to reinforce each other.That is the essence of Business Tai Chi. It gives language to something many engineering-led companies overlook or can’t structurally use. At SimpleChips, holding values firm at the center allows the rest of the system to adapt and move with greater clarity, energy, and purpose.This philosophy creates an environment favorable for the staff to be fully engaged in meaningful contributions. High achievers like challenges, and this unconventional company philosophy provides them with such opportunities.

Explore Business Tai Chi, a values-first model for deep-tech companies that balances financial sustainability, engineering learning, and team alignment to build resilient semiconductor innovation.

Business Tai Chi: Values-First Model for Operating a Deep-Tech Company

Article #6 of Confronting AI Series: AI's rapid evolution has outpaced regulation. In this Q&A, Jared Bowns explores how adaptive frameworks, accountability, and ethical oversight can help engineers manage the risks and responsibilities of building trustworthy AI systems.

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