Quantum computing

Quantum computing is an emerging field of computer science and engineering that harnesses the unique properties of quantum mechanics to solve problems beyond the capabilities of even the most powerful classical computers. Quantum computers specifically leverage these phenomena to access mathematical problem-solving methods that are out of reach for classical computing alone, offering the potential to solve in minutes or, at most, hours problems that would otherwise take conventional machines millennia to complete (www.ibm.com, 2026).

Do fax ao telefone celular. Da internet discada até a inteligência artificial. O Fantástico sempre esteve atento aos avanços tecnológicos que transformam o mundo. E 2025 foi declarado pela ONU o “Ano Internacional da Ciência e Tecnologia Quântica”. Quando você vê uma notícia sobre computadores quânticos, consegue ter uma ideia do que eles são ou serão capazes de fazer? O computador quântico é a fronteira da tecnologia atual. Ele promete resolver problemas que achávamos insolucionáveis e desvendar mistérios que ainda nem sabemos formular: da cura do câncer a salvar o mundo das mudanças climáticas. Essa reportagem pretende mostrar que ele não é um monstro misterioso (www.g1.globo.com, 2026) .

Amazon’s “Alexa”along with other artificial intelligences no longer meets our needs; there is criticism that AIs are becoming “dumb” due to the nature of “human brainstorming” versus machine logic. This theory stems from the mathematical architecture of current processors: mathematics is inherently sequential, and true randomness does not exist in computing. What we perceive as random is actually a precise calculation based on the machine’s internal clock specifically its milliseconds. If we consider a one-second interval, we could for instance perform a specific operation 100 times (or more, depending on the programmed functions). In other words, every processor to date processes only one piece of information at a time. To give the end user the impression that multiple tasks are being processed simultaneously, the system employs a virtualization scheme: it takes a tiny slice of each running program and processes that slice individually. This is the technology behind what are marketed today as “multitasking processors” from Intel, AMD, and others. To put it simply, these are single-core processors that use runtime virtualization to break tasks into smaller segments. By executing thousands of these segments per second, they create the illusion of simultaneous processing; in reality, however, while one mathematical calculation is being performed, there is no room for another on the processor.

Processors have evolved from systems that performed only one task at a time to chips capable of managing dozens of functions simultaneously. The key difference lies in how they handle time and processing cores. Single-tasking Processors (The Past): Older processors had only one core and executed instructions in a strictly sequential manner. Single focus: Ran only one program at a time. Rigid queue: The second program would only start after the first had finished. Bottleneck: If a command stalled, the entire system would freeze. User experience: To switch tasks, the user had to close one program and open another. Multitasking Processors (The Present): Modern processors use multiple cores and advanced time-slicing techniques to run several programs concurrently. Time-slicing: Switches between tasks in milliseconds (managed by Operating Systems). Multiple cores: Each physical core can process an independent task. Virtual threads: Doubles the capacity of each core (Hyper-Threading). Fluidity: Allows for listening to music, browsing the web, and rendering a video all at the same time (IA Gemini Goolge, 2026).

Much like the “regular dodecahedron” objects seen in science fiction films, each face would feature a laser targeting system aimed at another face, maximizing inter-element connectivity. This results in a processor that operates in a completely random and thus non-sequential and non-mathematical manner; discovery points emerge through calculations rather than relying on the “indestructible bridges” found in sequential systems. It stores data in variables and utilizes available connection elements, which can be arranged to optimize mutual visibility whether as 2D vectors or 3D matrices. The elements mentioned here are nano-resistors, making them suitable for a wide range of applications, including processors, RAM, ROM, single-purpose chips, and more. This architecture offers vastly superior speeds ranging from ten times faster to virtually infinite GHz, PB, TB, or MB limited only by the physical space available to house the machine or the desired investment cost. When combined with 3D printing technology, these units could be manufactured in real-time; furthermore, with shielded computational expansion modules, the factory and server farm could even be located underwater such as in the ocean—where there is abundant space for construction.

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