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Technology

Long-Term Crypto Success: Beyond Price & Liquidity

by Sophie Lin - Technology Editor
written by Sophie Lin - Technology Editor

The cryptocurrency landscape is often driven by short-term market forces, but lasting success requires a more fundamental approach. According to Yi He, a key differentiator between cryptocurrencies that thrive and those that fade lies in their ability to move beyond initial hype and establish sustainable foundations. While liquidity, public attention, and token structure play a role in initial price surges, long-term viability hinges on revenue generation, genuine user empowerment, and carefully designed economic mechanisms like token issuance and burning.

He argues that the most enduring cryptocurrencies aren’t simply speculative assets; they evolve into ecosystems capable of generating real value. This shift requires a focus on utility and a commitment to building a robust, self-sustaining economic model. The ability to attract and retain users isn’t just about marketing; it’s about providing tangible benefits and fostering a sense of ownership within the network. Understanding these dynamics is crucial for navigating the volatile world of digital assets and identifying projects with long-term potential. The focus on long-term sustainability in current crypto market trends highlights this require for fundamental value.

Beyond the Initial Surge: The Importance of Revenue Generation

Yi He’s assessment emphasizes that initial market enthusiasm, fueled by liquidity and attention, is insufficient for sustained growth. Cryptocurrencies must demonstrate a capacity to generate revenue, whether through transaction fees, decentralized finance (DeFi) applications, or other innovative models. This revenue stream is essential for funding ongoing development, incentivizing network participants, and ensuring the long-term health of the ecosystem. Without a clear path to revenue, a cryptocurrency risks becoming a speculative bubble, vulnerable to market corrections and decline.

Empowerment and Community Ownership

Beyond financial incentives, He highlights the importance of user empowerment. Successful cryptocurrencies aren’t simply platforms controlled by a central entity; they are decentralized networks where users have a genuine stake in the system. This can be achieved through governance tokens, staking mechanisms, or other forms of participation that allow users to influence the direction of the project. A strong sense of community ownership fosters loyalty, encourages active participation, and drives innovation.

The Role of Tokenomics: Issuance and Burning

The economic design of a cryptocurrency, often referred to as its tokenomics, is another critical factor. He points to the importance of mechanisms like token issuance and burning in managing supply and demand. Controlled issuance can aid to incentivize early adoption and reward network participants, while burning – the permanent removal of tokens from circulation – can create scarcity and potentially increase value. These mechanisms, when implemented effectively, can contribute to a more stable and sustainable economic model.

Bitcoin, Ethereum, and Binance Coin: Examples of Endurance

He specifically cites Bitcoin (BTC), Ethereum (ETH), and Binance Coin (BNB) as examples of cryptocurrencies that have demonstrated the ability to transcend the limitations of short-term market forces. These projects have evolved beyond initial hype, building robust ecosystems and attracting a loyal user base. Standard Chartered’s recent warnings about potential market corrections underscore the importance of these established projects.

The recent performance of BNB/ETH, with a 7% increase, as noted in AMBCrypto, suggests a potential shift in market leadership, further emphasizing the need for projects to demonstrate underlying strength.

Looking Ahead

As the cryptocurrency market matures, the focus will inevitably shift from speculation to sustainability. Projects that can demonstrate a clear path to revenue generation, foster genuine user empowerment, and implement sound tokenomics will be best positioned to weather market cycles and achieve long-term success. The current market volatility, as highlighted by recent sell-offs, reinforces the importance of these fundamental principles.

What are your thoughts on the long-term factors driving cryptocurrency success? Share your insights in the comments below.

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Technology

Tracking Water Globally: New Climate Models Use Isotopes to Predict Weather Changes

by Sophie Lin - Technology Editor
written by Sophie Lin - Technology Editor

Scientists are gaining an unprecedented ability to trace the journey of water across the globe, moving beyond traditional hydrological models to leverage the unique “fingerprint” embedded within water molecules themselves. This breakthrough, centered around the analysis of naturally occurring isotopes of hydrogen and oxygen, promises to refine our understanding of weather patterns, climate change, and the availability of this vital resource.

The key lies in subtle variations in the atomic structure of water. Although most water molecules are composed of the common isotopes of hydrogen and oxygen, a small percentage contain heavier, naturally occurring forms called isotopes. As water evaporates, forms clouds, and travels through the atmosphere, the ratio of these isotopes shifts in predictable ways, creating a traceable signature. By analyzing these isotopic ratios, researchers can map the origin and movement of water with increasing precision.

A recent study published in the Journal of Geophysical Research: Atmospheres details a novel approach to climate modeling that incorporates this isotopic data. Researchers at the Institute of Industrial Science, The University of Tokyo, utilized an “ensemble” method, combining the results of eight isotope-enabled climate models over a 45-year period, from 1979 to 2023. This technique, driven by consistent wind and sea-surface temperature data, allowed for a more robust evaluation of how each model handles the complex physics of the water cycle.

“Changes in water isotopes reflect shifts in moisture transport, convergence, and large-scale atmospheric circulation,” explained Professor Kei Yoshimura, a senior author of the study and advisor to several of the participating models. “Although we understand, at a simple level, that isotopes are affected by temperature, precipitation and altitude, the variability of current model simulations makes it difficult to interpret the results. We are delighted that our ensemble indicate values capture the isotope patterns observed in global precipitation, vapor, snow, and satellite data much more successfully than any of the individual models.”

Unlocking Climate Insights with Isotope Data

The ability to track water’s movement isn’t merely an academic exercise. It has significant implications for understanding and predicting extreme weather events. By integrating isotope data with hydrological models, scientists can gain a more nuanced understanding of storms, floods, and droughts, and improve projections of how climate change will alter future weather patterns. The U.S. Geological Survey provides detailed information on water isotopes and their role in scientific study.

The research revealed a clear connection between atmospheric water vapor and rising global temperatures over the past 30 years. The ensemble simulations demonstrated strong correlations with major climate patterns like the El Niño-Southern Oscillation, the North Atlantic Oscillation, and the Southern Annular Mode – large-scale systems that profoundly influence global water availability and impact billions of people worldwide.

Dr. Hayoung Bong, an alumnus of the Institute of Industrial Science, The University of Tokyo, now at NASA Goddard Institute for Space Studies, highlighted the benefits of the ensemble approach. “Ensembles offer a nuanced modeling approach that reduces divergence between individual models. This approach allows us to separate the effects of how each model represents water cycle processes from differences arising from individual model structures.”

A First-of-Its-Kind Modeling Framework

This study marks the first time multiple isotope-enabled climate models have been integrated into a single, unified framework. The resulting ensemble’s close alignment with observed data provides a more reliable picture of how water moves through the global climate system. Understanding the different combinations of hydrogen and oxygen isotopes within water molecules – ranging in molecular masses from 18 to 22 – is crucial to this process, as explained by the University of Utah’s Water Isotopes Project.

The implications extend beyond simply refining climate models. The ability to differentiate between local precipitation and imported water sources, as highlighted by HydroFocus, Inc., has practical applications for water resource management and conservation efforts.

“Importantly, the research advances our ability to interpret past climate variability and provides a stronger foundation for understanding and predicting how the global water cycle and the weather it shapes will respond to continued global warming,” Professor Yoshimura concluded.

As climate models continue to evolve and incorporate more sophisticated isotopic analysis, our ability to anticipate and mitigate the impacts of a changing climate will undoubtedly improve. Further research will focus on refining these models and expanding the scope of isotopic data collection to encompass a wider range of geographical regions and climate conditions. The ongoing development of isotope-enabled climate models represents a significant step forward in our quest to understand and protect this essential resource.

What are your thoughts on the potential of isotope analysis to improve climate modeling? Share your comments below and facilitate us continue the conversation.

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Technology

Gérard Mourou: The Story Behind the Nobel Prize Winner’s “Extreme Light”

by Sophie Lin - Technology Editor
written by Sophie Lin - Technology Editor

The world of physics lost a bit of its mystery in the 1980s, thanks to the groundbreaking work of Gérard Mourou and his doctoral student, Donna Strickland. Their development of a technique for creating ultrashort, high-power laser pulses revolutionized fields ranging from medicine to manufacturing, ultimately earning them the 2018 Nobel Prize in Physics, shared with Arthur Ashkin. Now, at 81 years classic, Mourou continues his research at Peking University, having joined the institution in 2024, and is sharing insights into his journey in a recently published autobiography.

Mourou’s story, as he recounts it, wasn’t driven by a grand vision of laser applications, but rather by a persistent curiosity and a willingness to challenge conventional wisdom. The core of their innovation – chirped pulse amplification – addressed a fundamental limitation of lasers at the time: the tendency for high-intensity pulses to distort and lose energy as they traveled through the laser medium. This breakthrough allowed scientists to focus incredibly powerful laser beams, opening up possibilities previously confined to theoretical speculation. The impact of this work on optical physics is undeniable.

The Genesis of “Extreme Light”

The title of Mourou’s autobiography, “Lumière extrême” (Extreme Light), hints at the intensity and precision at the heart of his research. “Extreme light” refers to the creation of laser pulses with durations measured in femtoseconds – quadrillionths of a second – and peak powers reaching levels previously unattainable. This level of control over light allows scientists to study matter at its most fundamental level, probing the interactions between light and atoms with unprecedented detail. The technique developed by Mourou and Strickland is now used in a wide range of applications, including laser eye surgery, precision micromachining, and the creation of new materials.

From Early Doubts to Nobel Recognition

Mourou’s recollections reveal a surprising lack of initial enthusiasm for lasers within the scientific community. As he notes, in the 1960s, the potential applications of lasers were largely unknown. “Dans les années 1960, personne ne voyait à quoi le laser pourrait servir,” he reportedly stated, highlighting the transformative nature of their work. The Nobel Prize in 2018, awarded jointly to Mourou, Strickland, and Ashkin, served as a powerful validation of their contributions and a testament to the enduring impact of their research. Donna Strickland, a professor at the University of Waterloo, played a crucial role in the development and implementation of chirped pulse amplification.

A Legacy of Innovation Continues

Despite his age, Mourou remains actively engaged in research at Peking University, continuing to push the boundaries of laser technology. His work exemplifies a dedication to scientific inquiry and a willingness to embrace unconventional approaches. The Natural Sciences and Engineering Research Council of Canada has even established a prize in Strickland’s name, further cementing the legacy of their collaborative achievements.

The story of Gérard Mourou and Donna Strickland is a compelling reminder that scientific breakthroughs often arise from unexpected places and require a combination of intellectual curiosity, technical skill, and a willingness to challenge established norms. Their work has not only transformed the field of physics but has likewise paved the way for countless technological advancements that continue to shape our world.

As Mourou continues his research in China, the future of extreme light promises even more exciting discoveries and applications. The ongoing exploration of ultrashort, high-power laser pulses will undoubtedly lead to new insights into the fundamental nature of matter and energy, and further innovations in fields ranging from medicine to materials science. Share your thoughts on the impact of laser technology in the comments below.

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Technology

AI & Critical Infrastructure: Gartner Warns of Shutdown Risks by 2028

by Sophie Lin - Technology Editor
written by Sophie Lin - Technology Editor

The increasing reliance on artificial intelligence to manage critical infrastructure presents a growing risk, with a new report from Gartner predicting that misconfigured AI could shut down national critical infrastructure in a G20 country by 2028. This isn’t a scenario involving malicious actors, but rather a failure stemming from the complexities of AI systems operating within cyber-physical systems (CPS).

Gartner defines CPS as “engineered systems that orchestrate sensing, computation, control, networking and analytics to interact with the physical world (including humans).” This broad category encompasses operational technology (OT), industrial control systems (ICS), industrial automation and control systems (IACS), the Industrial Internet of Things (IIoT), robots, drones, and Industry 4.0 technologies. The core concern isn’t AI “hallucinations” or deliberate attacks, but the potential for these systems to miss subtle changes that experienced human operators would readily identify, leading to cascading failures.

The rapid adoption of AI in these systems is accelerating the risk. Operators are increasingly granting machine learning systems the authority to make real-time decisions. While this offers efficiency gains, it also introduces vulnerabilities. A seemingly minor alteration in settings, a flawed software update, or even inaccurate data input can trigger unpredictable responses with potentially devastating consequences, Gartner warns. Unlike traditional software bugs that might crash a server, errors in AI-driven control systems can directly impact the physical world, causing equipment failures, forcing shutdowns, or destabilizing entire supply chains.

The Challenge of Subtle Changes

The Gartner report highlights a critical difference between AI and human oversight. Experienced operational managers develop an intuitive understanding of system behavior and can detect anomalies that might escape the notice of an AI. “The next great infrastructure failure may not be caused by hackers or natural disasters but rather by a well-intentioned engineer, a flawed update script, or a misplaced decimal,” cautioned Wam Voster, VP Analyst at Gartner, in the report. This underscores the importance of robust testing and validation procedures as AI takes on more responsibility for critical infrastructure management.

The issue extends beyond simply preventing errors. it’s about ensuring AI systems can adapt to changing conditions and unexpected events. Critical infrastructure is rarely static. Maintenance, upgrades, and even seasonal variations can introduce subtle shifts in system behavior. An AI trained on a specific dataset might struggle to interpret these changes correctly, leading to incorrect decisions. This is particularly concerning in complex systems where the interplay between different components is not fully understood.

Nozomi Networks Leads in AI-Powered OT Security

As AI integration into CPS expands, the need for robust cybersecurity measures is paramount. Nozomi Networks has emerged as a leader in AI-native operational technology (OT) security, according to a December 2025 Gartner report on AI Vendor Races. Gartner noted that Nozomi’s early investment in embedding machine learning capabilities into its CPS security product, starting in 2013, has given it a significant operational advantage in enabling AI to support CPS discovery, analysis, and alerting capabilities (Nozomi Networks). The company’s AI engine utilizes various techniques to enrich asset profiles, establish baseline behavior, and provide actionable insights for complex cyber-physical systems across sectors like energy, manufacturing, and transportation.

Implications for CIOs and Infrastructure Operators

The Gartner report serves as a wake-up call for CIOs and infrastructure operators. A proactive approach to AI risk management is essential. This includes implementing rigorous testing and validation procedures, developing robust monitoring systems, and ensuring that human operators retain the ability to override AI decisions when necessary. Organizations need to invest in training programs to equip their workforce with the skills needed to understand and manage AI-driven systems. The focus must shift from simply deploying AI to ensuring its safe and reliable operation within complex critical infrastructure environments.

The potential for widespread disruption is significant. Gartner predicts that by 2028, misconfigured AI in cyber physical systems will shut down national critical infrastructure in a G20 country (Gartner). This isn’t a distant threat; it’s a rapidly approaching reality that demands immediate attention. As AI continues to permeate critical infrastructure, the focus must be on building resilience and mitigating the risks associated with these powerful, yet potentially fragile, systems.

Looking ahead, the development of industry standards and regulatory frameworks for AI in CPS will be crucial. Establishing clear guidelines for testing, validation, and monitoring will help to ensure the safe and reliable deployment of AI in critical infrastructure. Continued research into explainable AI (XAI) – AI systems that can provide clear explanations for their decisions – will also be essential for building trust and accountability. The conversation around AI safety needs to move beyond hypothetical risks and focus on the practical challenges of deploying these technologies in the real world.

What are your thoughts on the increasing role of AI in critical infrastructure? Share your insights and concerns in the comments below.

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