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Category: quantum physics – Page 7

Keeping up with the Joneses…

The big elephant in the room here is Micro-LED. That’s because, like QDEL, Micro-LED pixels are self-emissive, with each pixel containing a tiny red, blue, and green LED, which combine to produce different colors as needed. It also means that Micro-LED displays have that pixel-level control for true blacks.

But QDEL could win here, too. Quantum dots seem to be able to produce more saturated and more pure colors than LEDs, which is why quantum dots are used on many high-end TVs today. Of course, it’s entirely possible that Micro-LED technology could be combined with a quantum dot layer for purer and more vibrant colors, which would create a stunning image with a high level of brightness.

Likely, however, QDEL could end up doing a similar job as Micro-LED for much cheaper. Micro-LED has proven expensive to produce. While QDEL isn’t being used on consumer screens just yet, it could end up being much cheaper given the fact that quantum dots at this point are relatively easy to manufacture.

Continue reading “Could QDEL replace OLED? Yes, and it might happen sooner than expected” | >

But other calculations say that applies only in limited cases and that if you ramp up the warp engine slowly enough, you’ll be fine.

Yet more calculations sidestep all of this and just look at how much negative energy you actually need to construct your warp drive. And the answer is, for a single macroscopic bubble — say, 30 feet (100 meters) across — you would need 10 times more negative energy than all of the positive energy contained in the entire universe, which isn’t very promising.

However, still other calculations show that this immense amount applies only to the traditional warp bubble as defined by Alcubierre. It might be possible to reshape the bubble so there’s a tiny “neck” in the front that’s doing the work of compressing space and then it balloons out to an envelope to contain the warp bubble. This minimizes any quantum weirdness so that you need only about a star’s worth of negative energy to shape the drive.

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Molecular Dynamics (MD) simulation serves as a crucial technique across various disciplines including biology, chemistry, and material science1,2,3,4. MD simulations are typically based on interatomic potential functions that characterize the potential energy surface of the system, with atomic forces derived as the negative gradients of the potential energies. Subsequently, Newton’s laws of motion are applied to simulate the dynamic trajectories of the atoms. In ab initio MD simulations5, the energies and forces are accurately determined by solving the equations in quantum mechanics. However, the computational demands of ab initio MD limit its practicality in many scenarios. By learning from ab initio calculations, machine learning interatomic potentials (MLIPs) have been developed to achieve much more efficient MD simulations with ab initio-level accuracy6,7,8.

Despite their successes, the crucial challenge of implementing MLIPs is the distribution shift between training and test data. When using MLIPs for MD simulations, the data for inference are atomic structures that are continuously generated during simulations based on the predicted forces, and the training set should encompass a wide range of atomic structures to guarantee the accuracy of predictions. However, in fields such as phaseion9,10, catalysis11,12, and crystal growth13,14, the configurational space that needs to be explored is highly complex. This complexity makes it challenging to sample sufficient data for training and easy to make a potential that is not smooth enough to extrapolate to every relevant point. Consequently, a distribution shift between training and test datasets often occurs, which causes the degradation of test performance and leads to the emergence of unrealistic atomic structures, and finally the MD simulations collapse15.

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The future is coming and much faster than we think. Let’s do an exercise of imagination, imagine, for a moment, being able to send information from one point to another without the need for cables, Wi-Fi or traditional signals, more or less like something telepathic, right? Well, that is precisely what scientists have recently achieved at the University of Oxford: teleporting data between two quantum computers. Although it may seem like science fiction or just news, the world.

Although, let’s lower the hype a little, the transmission distance of this experiment was less than two meters, but that doesn’t matter, what matters is having achieved this milestone of sharing information without the need for connections.

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Imagine being able to see quantum objects with your own eyes — no microscopes needed. That’s exactly what researchers at TU Wien and ISTA have achieved with superconducting circuits, artificial atoms that are massive by quantum standards.

Unlike natural atoms, these structures can be engineered to have customizable properties, allowing scientists to control energy levels and interactions in ways never before possible. By coupling them, they’ve developed a method to store and retrieve light, laying the groundwork for revolutionary quantum technologies. These engineered systems also enable precise quantum pulses and act as a kind of quantum memory, offering an unprecedented level of control over light at the quantum level.

Gigantic Quantum Objects – Visible to the Naked Eye.

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At the threshold of a century poised for unprecedented transformations, we find ourselves at a crossroads unlike any before. The convergence of humanity and technology is no longer a distant possibility; it has become a tangible reality that challenges our most fundamental conceptions of what it means to be human.

This article seeks to explore the implications of this new era, in which Artificial Intelligence (AI) emerges as a central player. Are we truly on the verge of a symbiotic fusion, or is the conflict between the natural and the artificial inevitable?

The prevailing discourse on AI oscillates between two extremes: on one hand, some view this technology as a powerful extension of human capabilities, capable of amplifying our creativity and efficiency. On the other, a more alarmist narrative predicts the decline of human significance in the face of relentless machine advancement. Yet, both perspectives seem overly simplistic when confronted with the intrinsic complexity of this phenomenon. Beyond the dichotomy of utopian optimism and apocalyptic pessimism, it is imperative to critically reflect on AI’s cultural, ethical, and philosophical impact on the social fabric, as well as the redefinition of human identity that this technological revolution demands.

Since the dawn of civilization, humans have sought to transcend their natural limitations through the creation of tools and technologies. From the wheel to the modern computer, every innovation has been seen as a means to overcome the physical and cognitive constraints imposed by biology. However, AI represents something profoundly different: for the first time, we are developing systems that not only execute predefined tasks but also learn, adapt, and, to some extent, think.

This transition should not be underestimated. While previous technologies were primarily instrumental—serving as controlled extensions of human will—AI introduces an element of autonomy that challenges the traditional relationship between subject and object. Machines are no longer merely passive tools; they are becoming active partners in the processes of creation and decision-making. This qualitative leap radically alters the balance of power between humans and machines, raising crucial questions about our position as the dominant species.

But what does it truly mean to “be human” in a world where the boundaries between mind and machine are blurring? Traditionally, humanity has been defined by attributes such as consciousness, emotion, creativity, and moral decision-making. Yet, as AI advances, these uniquely human traits are beginning to be replicated—albeit imperfectly—within algorithms. If a machine can imitate creativity or exhibit convincing emotional behavior, where does our uniqueness lie?

This challenge is not merely technical; it strikes at the core of our collective identity. Throughout history, humanity has constructed cultural and religious narratives that placed us at the center of the cosmos, distinguishing us from animals and the forces of nature. Today, that narrative is being contested by a new technological order that threatens to displace us from our self-imposed pedestal. It is not so much the fear of physical obsolescence that haunts our reflections but rather the anxiety of losing the sense of purpose and meaning derived from our uniqueness.

Despite these concerns, many AI advocates argue that the real opportunity lies in forging a symbiotic partnership between humans and machines. In this vision, technology is not a threat to humanity but an ally that enhances our capabilities. The underlying idea is that AI can take on repetitive or highly complex tasks, freeing humans to engage in activities that truly require creativity, intuition, and—most importantly—emotion.

Concrete examples of this approach can already be seen across various sectors. In medicine, AI-powered diagnostic systems can process vast amounts of clinical data in record time, allowing doctors to focus on more nuanced aspects of patient care. In the creative industry, AI-driven text and image generation software are being used as sources of inspiration, helping artists and writers explore new ideas and perspectives. In both cases, AI acts as a catalyst, amplifying human abilities rather than replacing them.

Furthermore, this collaboration could pave the way for innovative solutions in critical areas such as environmental sustainability, education, and social inclusion. For example, powerful neural networks can analyze global climate patterns, assisting scientists in predicting and mitigating natural disasters. Personalized algorithms can tailor educational content to the specific needs of each student, fostering more effective and inclusive learning. These applications suggest that AI, far from being a destructive force, can serve as a powerful instrument to address some of the greatest challenges of our time.

However, for this vision to become reality, a strategic approach is required—one that goes beyond mere technological implementation. It is crucial to ensure that AI is developed and deployed ethically, respecting fundamental human rights and promoting collective well-being. This involves regulating harmful practices, such as the misuse of personal data or the indiscriminate automation of jobs, as well as investing in training programs that prepare people for the new demands of the labor market.

While the prospect of symbiotic fusion is hopeful, we cannot ignore the inherent risks of AI’s rapid evolution. As these technologies become more sophisticated, so too does the potential for misuse and unforeseen consequences. One of the greatest dangers lies in the concentration of power in the hands of a few entities, whether they be governments, multinational corporations, or criminal organizations.

Recent history has already provided concerning examples of this phenomenon. The manipulation of public opinion through algorithm-driven social media, mass surveillance enabled by facial recognition systems, and the use of AI-controlled military drones illustrate how this technology can be wielded in ways that undermine societal interests.

Another critical risk in AI development is the so-called “alignment problem.” Even if a machine is programmed with good intentions, there is always the possibility that it misinterprets its instructions or prioritizes objectives that conflict with human values. This issue becomes particularly relevant in the context of autonomous systems that make decisions without direct human intervention. Imagine, for instance, a self-driving car forced to choose between saving its passenger or a pedestrian in an unavoidable collision. How should such decisions be made, and who bears responsibility for the outcome?

These uncertainties raise legitimate concerns about humanity’s ability to maintain control over increasingly advanced technologies. The very notion of scientific progress is called into question when we realize that accumulated knowledge can be used both for humanity’s benefit and its detriment. The nuclear arms race during the Cold War serves as a sobering reminder of what can happen when science escapes moral oversight.

Whether the future holds symbiotic fusion or inevitable conflict, one thing is clear: our understanding of human identity must adapt to the new realities imposed by AI. This adjustment will not be easy, as it requires confronting profound questions about free will, the nature of consciousness, and the essence of individuality.

One of the most pressing challenges is reconciling our increasing technological dependence with the preservation of human dignity. While AI can significantly enhance quality of life, there is a risk of reducing humans to mere consumers of automated services. Without a conscious effort to safeguard the emotional and spiritual dimensions of human experience, we may end up creating a society where efficiency outweighs empathy, and interpersonal interactions are replaced by cold, impersonal digital interfaces.

On the other hand, this very transformation offers a unique opportunity to rediscover and redefine what it means to be human. By delegating mechanical and routine tasks to machines, we can focus on activities that truly enrich our existence—art, philosophy, emotional relationships, and civic engagement. AI can serve as a mirror, compelling us to reflect on our values and aspirations, encouraging us to cultivate what is genuinely unique about the human condition.

Ultimately, the fate of our relationship with AI will depend on the choices we make today. We can choose to view it as an existential threat, resisting the inevitable changes it brings, or we can embrace the challenge of reinventing our collective identity in a post-humanist era. The latter, though more daring, offers the possibility of building a future where technology and humanity coexist in harmony, complementing each other.

To achieve this, we must adopt a holistic approach that integrates scientific, ethical, philosophical, and sociological perspectives. It also requires an open, inclusive dialogue involving all sectors of society—from researchers and entrepreneurs to policymakers and ordinary citizens. After all, AI is not merely a technical tool; it is an expression of our collective imagination, a reflection of our ambitions and fears.

As we gaze toward the horizon, we see a world full of uncertainties but also immense possibilities. The future is not predetermined; it will be shaped by the decisions we make today. What kind of social contract do we wish to establish with AI? Will it be one of domination or cooperation? The answer to this question will determine not only the trajectory of technology but the very essence of our existence as a species.

Now is the time to embrace our historical responsibility and embark on this journey with courage, wisdom, and an unwavering commitment to the values that make human life worth living.

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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/a-sinfonia-do-amanha-tit…exao-seria ]