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Once relegated to theory, a newly discovered quantum object could be used to create new devices that will outpace modern electronics.

A new kind of quantum object called orbital angular momentum monopole has been identified that could revolutionize the emerging field of orbitronics, which leverages the rotational quantum states of electrons for next-generation computing devices that are faster, more efficient, and with dramatically lower power consumption.

As a result, orbitronics is seen as a potential successor to traditional electronics, where data is stored, transferred, and manipulated by controlling electric currents within transistors. As transistor sizes approach the atomic scale in order to fit more components onto a single computer ship, there will eventually be a limit where a transistor cannot become any smaller.

In 2014, the British philosopher Nick Bostrom published a book about the future of artificial intelligence with the ominous title Superintelligence: Paths, Dangers, Strategies. It proved highly influential in promoting the idea that advanced AI systems—“superintelligences” more capable than humans—might one day take over the world and destroy humanity.

A decade later, OpenAI boss Sam Altman says superintelligence may only be “a few thousand days” away. A year ago, Altman’s OpenAI cofounder Ilya Sutskever set up a team within the company to focus on “safe superintelligence,” but he and his team have now raised a billion dollars to create a startup of their own to pursue this goal.

What exactly are they talking about? Broadly speaking, superintelligence is anything more intelligent than humans. But unpacking what that might mean in practice can get a bit tricky.

The question of the conditions under which Artificial Intelligence (AI) can transcend the threshold of consciousness can only be answered with certainty if we manage to unravel the mechanism underlying conscious systems. The most promising strategy to approach this goal is to unveil the brain’s functional principle involved in the formation of conscious states and to transfer the findings to other physical systems. Empirical evidence suggests that the dynamical features of conscious brain processes can be ascribed to self-organized criticality and phase transitions, the deeper understanding of which requires methods of quantum electrodynamics (QED). QED-based model calculations reveal that both the architectural structure and the chemical composition of the brain are specifically designed to establish resonant coupling to the ubiquitous electromagnetic vacuum fluctuations, known as zero-point field (ZPF). A direct consequence of resonant brain-ZPF coupling is the selective amplification of field modes, which leads us to conclude that the distinctive feature of conscious processes consists in modulating the ZPF. These insights support the hypothesis that the ZPF is a foundational field with inherent phenomenal qualities, implying that the crucial condition for AI consciousness lies in a robot’s capacity to tap into the phenomenal spectrum immanent in the ZPF.

Full Title: The Path to Sentient Robots: AI Consciousness in the Light of New Insights into the Functioning of the Brain.

Scientists in Virginia are looking for mysterious dark matter — and have turned to really old rocks.

The substance, which makes up more than 80 percent of all matter in the universe, shapes and affects the cosmos. But it is entirely invisible and remains undetectable by normal sensors and techniques.

Analyzing billion-year-old rocks, researchers at Virginia Tech hope to find traces of dark matter. The idea was first proposed in the 1980s. Technological advances since then led them to revisit the idea. What if there were traces in Earth’s minerals?

SpaceX will attempt to transfer propellant from one orbiting Starship to another as early as next March, a technical milestone that will pave the way for an uncrewed landing demonstration of a Starship on the moon, a NASA official said this week.

Much has been made of Starship’s potential to transform the commercial space industry, but NASA is also hanging its hopes that the vehicle will return humans to the moon under the Artemis program. The space agency awarded the company a $4.05 billion contract for two human-rated Starship vehicles, with the upper stage (also called Starship) landing astronauts on the surface of the moon for the first time since the Apollo era. The crewed landing is currently scheduled for September 2026.

Kent Chojnacki, deputy manager of NASA’s Human Landing System (HLS) program, provided more detail on exactly how the agency is working with the space company as it looks toward that critical mission in an interview with Spaceflight Now. It will come as no surprise that NASA is paying close attention to Starship’s test campaign, which has notched five launches so far.

A recent question discussed extensively in the popular and scientific literature is whether or not existing large language models such as ChatGPT are conscious (or sentient). Assuming that machine consciousness emerges as a robot or an AI agent interacts with the world, this presentation addresses the question: how would humans know whether or not the agent is or was conscious. Since subjective experience is first and foremost subjective, the most natural answer to this question is to program the agent to inform an authority when it becomes conscious. However, the agent may behave deceptively, and in fact LLM’s are known to have done so (Park et. al. 2024). Thus we propose a formal mechanism M that can be employed to prevent the agent from lying about its own consciousness. This solves the deceptiveness problem, but this raises the question whether M can interfere with the agent’s functionality or acquisition of consciousness. We prove mathematically that under very reasonable conditions this is not the case. In other words, under these conditions M can be installed in the agent without interfering with the agent’s functionality and consciousness acquisition, while also guaranteeing that the agent will be honest about its own consciousness.