Lifeboat Foundation: Safeguarding Humanity
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Category: computing

Artificial Intelligence (AI) is, without a doubt, the defining technological breakthrough of our time. It represents not only a quantum leap in our ability to solve complex problems but also a mirror reflecting our ambitions, fears, and ethical dilemmas. As we witness its exponential growth, we cannot ignore the profound impact it is having on society. But are we heading toward a bright future or a dangerous precipice?

This opinion piece aims to foster critical reflection on AI’s role in the modern world and what it means for our collective future.

AI is no longer the stuff of science fiction. It is embedded in nearly every aspect of our lives, from the virtual assistants on our smartphones to the algorithms that recommend what to watch on Netflix or determine our eligibility for a bank loan. In medicine, AI is revolutionizing diagnostics and treatments, enabling the early detection of cancer and the personalization of therapies based on a patient’s genome. In education, adaptive learning platforms are democratizing access to knowledge by tailoring instruction to each student’s pace.

These advancements are undeniably impressive. AI promises a more efficient, safer, and fairer world. But is this promise being fulfilled? Or are we inadvertently creating new forms of inequality, where the benefits of technology are concentrated among a privileged few while others are left behind?

One of AI’s most pressing challenges is its impact on employment. Automation is eliminating jobs across various sectors, including manufacturing, services, and even traditionally “safe” fields such as law and accounting. Meanwhile, workforce reskilling is not keeping pace with technological disruption. The result? A growing divide between those equipped with the skills to thrive in the AI-driven era and those displaced by machines.

Another urgent concern is privacy. AI relies on vast amounts of data, and the massive collection of personal information raises serious questions about who controls these data and how they are used. We live in an era where our habits, preferences, and even emotions are continuously monitored and analyzed. This not only threatens our privacy but also opens the door to subtle forms of manipulation and social control.

Then, there is the issue of algorithmic bias. AI is only as good as the data it is trained on. If these data reflect existing biases, AI can perpetuate and even amplify societal injustices. We have already seen examples of this, such as facial recognition systems that fail to accurately identify individuals from minority groups or hiring algorithms that inadvertently discriminate based on gender. Far from being neutral, AI can become a tool of oppression if not carefully regulated.

Who Decides What Is Right?

AI forces us to confront profound ethical questions. When a self-driving car must choose between hitting a pedestrian or colliding with another vehicle, who decides the “right” choice? When AI is used to determine parole eligibility or distribute social benefits, how do we ensure these decisions are fair and transparent?

The reality is that AI is not just a technical tool—it is also a moral one. The choices we make today about how we develop and deploy AI will shape the future of humanity. But who is making these decisions? Currently, AI’s development is largely in the hands of big tech companies and governments, often without sufficient oversight from civil society. This is concerning because AI has the potential to impact all of us, regardless of our individual consent.

A Utopia or a Dystopia?

The future of AI remains uncertain. On one hand, we have the potential to create a technological utopia, where AI frees us from mundane tasks, enhances productivity, and allows us to focus on what truly matters: creativity, human connection, and collective well-being. On the other hand, there is the risk of a dystopia where AI is used to control, manipulate, and oppress—dividing society between those who control technology and those who are controlled by it.

The key to avoiding this dark scenario lies in regulation and education. We need robust laws that protect privacy, ensure transparency, and prevent AI’s misuse. But we also need to educate the public on the risks and opportunities of AI so they can make informed decisions and demand accountability from those in power.

Artificial Intelligence is, indeed, the Holy Grail of Technology. But unlike the medieval legend, this Grail is not hidden in a distant castle—it is in our hands, here and now. It is up to us to decide how we use it. Will AI be a tool for building a more just and equitable future, or will it become a weapon that exacerbates inequalities and threatens our freedom?

The answer depends on all of us. As citizens, we must demand transparency and accountability from those developing and implementing AI. As a society, we must ensure that the benefits of this technology are shared by all, not just a technocratic elite. And above all, we must remember that technology is not an end in itself but a means to achieve human progress.

The future of AI is the future we choose to build. And at this critical moment in history, we cannot afford to get it wrong. The Holy Grail is within our reach—but its true value will only be realized if we use it for the common good.

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Copyright © 2025, Henrique Jorge

[ This article was originally published in Portuguese in SAPO’s technology section at: https://tek.sapo.pt/opiniao/artigos/o-santo-graal-da-tecnologia ]

University at Albany researchers at the RNA Institute are pioneering new methods for designing and assembling DNA nanostructures, enhancing their potential for real-world applications in medicine, materials science and data storage.

Their latest findings demonstrate a novel ability to assemble these structures without the need for and controlled cooling. They also demonstrate successful assembly of unconventional “buffer” substances including nickel. These developments, published in the journal Science Advances, unlock new possibilities in DNA nanotechnology.

DNA is most commonly recognized for its role in storing genetic information. Composed of base pairs that can easily be manipulated, DNA is also an excellent material for constructing nanoscale objects. By “programming” the base pairs that make up DNA molecules, scientists can create precise structures as small as a few nanometers that can be engineered into shapes with intricate architectures.

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With today’s data rates of only a few hundred megabytes per second, access to digital information remains relatively slow. Initial experiments have already shown a promising new strategy: Magnetic states can be read out by short current pulses, whereby recently discovered spintronic effects in purpose-built material systems could remove previous speed restrictions.

Researchers at HZDR and TU Dortmund University are now providing proof of the feasibility of such ultrafast data sources. Instead of , they use ultrashort , thereby enabling the read-out of magnetic structures within picoseconds, as they report in the journal Nature Communications.

“We now can determine the magnetic orientation of a material much quicker with light-induced current pulses,” explains Dr. Jan-Christoph Deinert of HZDR’s Institute of Radiation Physics. For their experiments, the physicist and his team employed light that is invisible to the human eye—so-called terahertz radiation.

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A small team of computational and evolutionary biologists from the University of Chinese Academy of Sciences, Zhongshan Hospital and the Max Planck Institute for Evolutionary Anthropology, reports that unique lactase genes carried by about 25% of East Asian people may have been inherited from Neanderthals.

In their study published in Proceedings of the National Academy of Sciences, the group compared the of thousands of people of African, East Asian and European descent against one another and then against Neanderthal genes.

Prior research has shown that many people of European descent carry genes that allow them to easily digest the sugars (lactose) present in milk, in sharp contrast to people of East Asian descent, who tend to have a high percentage of . However, in this new effort, the research team found unique versions of the lactase gene in some East Asian people along with evidence that they may have come from interbreeding between humans and Neanderthals thousands of years ago.

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Like engineers who design high-performance Formula One race cars, scientists want to create high-performance plasmas in twisty fusion systems known as stellarators. Achieving this performance means that the plasma must retain much of its heat and stay within its confining magnetic fields.

To ease the creation of these plasmas, physicists have created a new computer code that could speed up the design of the complicated magnets that shape the plasma, making stellarators simpler and more affordable to build.

Known as QUADCOIL, the code helps scientists rule out plasma shapes that are stable but require magnets with overly complicated shapes. With this information, scientists can instead devote their efforts to designing stellarators that can be built affordably.

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Quantum Internet Alliance (QIA) researchers at TU Delft, QuTech, University of Innsbruck, INRIA and CNRS recently announced the creation of the first operating system designed for quantum networks: QNodeOS. The research, published in Nature, marks a major step forward in transforming quantum networking from a theoretical concept to a practical technology that could revolutionize the future of the internet.

“The goal of our research is to bring quantum network technology to all. With QNodeOS we’re taking a big step forward. We’re making it possible—for the first time—to program and execute applications on a quantum network easily,” says Prof. Dr. Stephanie Wehner, Professor of Quantum Computer Science at TU Delft’s quantum technology research institute QuTech, who led the study. “Our work also creates a framework opening entirely new areas of quantum computer science research.”

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Simulations of quantum many-body systems are an important goal for nuclear and high-energy physics. Many-body problems involve systems that consist of many microscopic particles interacting at the level of quantum mechanics. They are much more difficult to describe than simple systems with just two particles. This means that even the most powerful conventional computers cannot simulate these problems.

Quantum computing has the potential to address this challenge using an approach called quantum simulation. To succeed, these simulations need theoretical approximations of how quantum computers represent many-body systems. In research on this topic, at the University of Washington developed a new framework to systematically analyze the interplay of these approximations. They showed that the impact of such approximations can be minimized by tuning simulation parameters.

The study is published in the journal Physical Review A.

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Quantum systems don’t just transition between phases—they do so in ways that defy classical intuition.

A new experiment has directly observed these “dissipative phase transitions” (DPTs), revealing how quantum states shift under carefully controlled conditions. This breakthrough could unlock powerful new techniques for stabilizing quantum computers and sensors, making them more resilient and precise than ever before.

Quantum phase transitions: a new frontier.

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Glen Anderson’s created an analog computer that uses water to demonstrate digital logic

A computer that uses water instead of electricity? That’s what Glen Anderson and his daughter, Dale, are demonstrating at Maker Faire Bay Area this weekend. He invites kids to fill buckets and dump them into one of four water tanks. On Friday, I asked him how it was going. “I am adding 1 and 1 but getting 1,” he said. Something was wrong and he was working to fix it.

Glen said his goal for the project was to demystify how computers “think”

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Quantum entanglement is a fundamental phenomenon in nature and one of the most intriguing aspects of quantum mechanics. It describes a correlation between two particles, such that measuring the properties of one instantly reveals those of the other, no matter how far apart they are. This unique property has been harnessed in applications such as quantum computing and quantum communication.

A common method for generating entanglement is through a , which produces with entangled polarizations via spontaneous parametric down-conversion (SPDC): if one photon is measured to be horizontally polarized, the other will always be vertically polarized, and vice versa.

Meanwhile, metasurfaces—ultrathin optical devices—are known for their ability to encode vast amounts of information, allowing the creation of high-resolution holograms. By combining metasurfaces with nonlinear crystals, researchers can explore a promising approach to enhancing the generation and control of entangled photon states.

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