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Groove Quantum Demonstrates 18-Qubit Spin Processor and Secures Funding

PRESS RELEASE — Groove Quantum today announced it has raised €16 million in combined funding and demonstrated an 18-qubit semiconductor spin-qubit processor, the largest of its kind ever built. The result marks a step beyond small-scale laboratory prototypes toward a quantum processor architecture designed for large-scale integration. The combined funding consists of €10 million in equity and €6 million in grants. The equity seed round is co-led by Innovation Industries, a leading European deep tech fund, and 55 North, the world’s largest pure-play quantum fund, with participation from Verve Ventures and the European Innovation Council Fund. Additional funding is provided by grants from the EIC Accelerator programme and JU Chips Act funding programme further underscores institutional confidence in Groove’s approach.

Groove will use the capital to scale qubit count exponentially and to begin manufacturing its processors at established semiconductor foundries.

Quantum computers create a fundamentally new way of computing. This opens the door to solving complex challenges that would take today’s most powerful supercomputers impractically long to address, like the discovery of new medicines, and the design of advanced materials for renewable energy – challenges that are highly important and have a profoundly positive impact on humanity.

Spatial transcriptomics from pancreas and local draining lymph node tissue reveals a lymphotoxin-β signature in human type 1 diabetes

Medina-Serpas et al. provide a public spatial transcriptomic atlas of pancreas and pLN comprising defined stages of human T1D. Cross-platform validation revealed pancreatic inflammation and elevated lymphotoxin-β expression as a signature of T1D, persistent across tissues. These data support therapeutic targeting of the lymphotoxin/TNF pathway in T1D.

ASK A MORTICIAN- Do Hair & Nails Grow After Death?

The age old myth of postmortem production!

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Is Our Model of Dark Energy WRONG? | New 4.2σ Results

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The biggest news in cosmology in recent years is that the mysterious universe-accelerating entity we call dark energy may be fading away. The evidence for this is now strong enough that enormous effort is going into confirming this result. So what’s it going to take, and when are we going to know?

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Are Cosmic Strings Cracks in the Universe?

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Reality has cracks in it. Universe-spanning filaments of ancient Big Bang energy, formed from topological defects in the quantum fields, aka cosmic strings. They have subatomic thickness but prodigious mass and they lash through space at a close to the speed of light. They could be the most bizarre undiscovered entities that actually exist.

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How Close Are We to Human-Level AI? Here’s the Most Plausible Timeframe for Achieving Artificial General Intelligence (AGI)

This is exactly why the benchmarks I propose in the book matter so much. Defining AGI and ASI is not semantics; it determines which architectures we are trying to align, how long top-down control mechanisms remain useful, and when we must shift our focus toward developmental and integrative approaches such as the AGI Naturalization Protocol and merge-based alignment.

In SUPERALIGNMENT, I argue that no single strategy is sufficient. Today’s control-based alignment is indispensable, but only as an early scaffold. Ethical-emotional development is necessary, but only as a middle phase. Merge-based alignment becomes increasingly relevant as humans and artificial minds begin to co-evolve within shared cognitive ecosystems. The triadic structure matters because each phase corresponds to a distinct level of intelligence maturity: constraint, cultivation, and convergence.

In my framework, AGI is not a static point but a continuum of cognitive emergence: from embodied agency to disembodied abstraction, from classical computation to quantum cognition, and from reactive behavior to phenomenological self-awareness. The benchmarks provide the conceptual anchors for intervention. They tell us when control may still be enough, when cultivation becomes necessary, and when convergence between human and synthetic minds becomes the more realistic path to Superalignment.

What If Time Isn’t Linear? Exploring the Universe’s Most Baffling Concept

You are used to thinking of time as a straight line: past behind you, present under your feet, and future stretching endlessly ahead. Clocks tick, calendars flip, and your life seems to march forward in one clean direction. But when you start looking closely at what physics and philosophy actually say about time, that simple picture starts to wobble in surprising and sometimes unsettling ways.

Once you let go of the idea that time must be linear, a whole new universe of possibilities opens up. You begin to wonder whether the past is really gone, whether the future might already exist, and whether your sense of “now” is just a useful illusion. In this article, you’ll explore some of the strangest, most well-supported ideas about time from modern science, and you’ll see how they quietly challenge your everyday experience without requiring you to believe in magic.

If you pause and ask yourself what “now” actually is, you probably feel like the answer is obvious: it’s the present moment you’re living in. But when you compare your “now” with someone else’s “now” far away, the certainty starts to crack. Relativity theory tells you that what counts as “simultaneous” events depends on how you’re moving, so two observers in different states of motion won’t agree on what is happening at the same time.

Artificial neurons successfully communicate with living brain cells

Engineers at Northwestern University have created printed artificial neurons that go beyond imitation and can directly interact with real brain cells. These flexible, low-cost devices produce electrical signals that closely resemble those generated by living neurons, allowing them to activate biological brain tissue.

In experiments using slices of mouse brain, the artificial neurons successfully triggered responses in real neurons. This result shows a new level of compatibility between electronic devices and living neural systems.

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