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Penrose vs EWOG: Consciousness and Quantum Collapse

Consciousness beyond penrose quantum microtubules?utm_source=share&utm_medium=member_android&rcm=ACoAADcXNX8BNm6vE2wHF7V91czmcuYXcuPHhY4.

đŸ§ âš›ïž Beyond Penrose: Can Consciousness Be Derived from Geometry? For more than 30 years, Roger Penrose and Stuart Hameroff proposed that consciousness emerges through Objective Reduction (OR) inside neuronal microtubules. Penrose’s key equation is remarkably simple: τ_OR = ℏ / E_G where: τ_OR = collapse time ℏ = reduced Planck constant E_G = gravitational self-energy of the spacetime superposition The idea is: 🌌 Spacetime superposition ⟶ Gravitational instability ⟶ Wavefunction collapse ⟶ Conscious event But a major question remained: ❓ What is the mathematical mechanism that actually causes collapse? The EWOG framework attempts to provide one.

AI model proves to be a heavyweight in tumor assessment: Mesothelioma patients and physicians benefit

Physicians and researchers at the Netherlands Cancer Institute have developed an AI model that outperforms physicians in evaluating treatment response in pleural mesothelioma. Far more accurate than the current international standard criteria (RECIST), the model provides patients with greater certainty and tailored treatments. It changes how physicians assess tumors and could accelerate the development of new treatments by making clinical trials more reliable and efficient.

Physicians evaluate treatment response by measuring tumor growth. The current diameter-based RECIST criteria are of limited use for pleural mesothelioma because this cancer type grows in a thin, irregular layer along the lung wall. Where, then, do you measure the diameter to determine whether the therapy is working? This leads to uncertainty and frustration among patients and physicians.

AI experts, radiologists and pulmonologists from the Netherlands Cancer Institute (NKI) have now solved this problem. Together, they developed the AI model ARTIMES, which can measure the entire volume of a tumor and compare it with previous scans.

Building Brains: The Molecular Logic of Neural Circuits

Thomas M. Jessel, Howard Hughes Medical Institute Investigator, explores the human brain, the sophisticated product of 500 million years of vertebrate evolution, assembled during just nine months of embryonic development. The functions encoded by its trillion nerve cells direct all human behavior. Yet the brain is a biological organ made from the same building blocks as skin, liver and lung. How does the brain acquire its remarkable computational power? Answers lie in the details of its construction — the cellular and molecular mechanisms that drive the formation of thousands of neural circuits, each wired for a specific behavior.

Developing brain cells routinely repair severe DNA damage during migration

Newborn nerve cells must squeeze through crowded, narrow spaces-through dense tissue, past other cells, between fibers-to reach the areas where they form neural circuits in the brain cortex.

In a new study published in Nature, researchers at Kyoto University’s Institute for Integrated Cell-Material Sciences (WPI-iCeMS) and their collaborators report that this journey causes widespread DNA damage in neurons, resulting in double-strand breaks where both strands of the double helix are completely severed. While this is the most severe type of DNA damage-capable of causing mutations and cell death-the team surprisingly found that it is a normal, routine feature of brain cortex formation, and a healthy brain quickly repairs it before harm occurs.

“The developing brain appears to have evolved to tolerate and repair the neuronal damage efficiently,” says Professor Mineko Kengaku, of WPI-iCeMS, who led the study. “But understanding the limits of that tolerance-and what happens when repair is incomplete-brings us closer to understanding a range of neurological conditions.”

The growing backlash to AI’s “race to replace” humans | The Economist

Opposition to artificial intelligence is uniting America’s left and right. Max Tegmark, physicist and chairman of the Future of Life Institute, argues that sentiment across the political spectrum, from Bernie Sanders to Steve Bannon, is turning against a \.

DP21577 The Generative AI Learning Penalty: Evidence from Chinese Secondary Education

Using 30 months of panel data on 26,811 Chinese students in grades 7−−12, we study how generative AI affects homework productivity and learning. The data combine monthly closed-book exams, high-school and college entrance exams, and homework scores and completion time across nine subjects. We exploit staggered AI adoption in a difference-in-differences design. AI adoption raises homework scores by 18% and reduces completion time by 30%, but lowers monthly exam scores by 20% within six months. High-stakes entrance-exam scores fall by 18 and 24%, with the full penalty emerging only after about two years. The losses are largest in social science subjects, followed by STEM and languages, and are especially large for junior students, high-achieving students, and boys. The learning losses are concentrated among roughly 80% of AI users whose behavior is consistent with homework outsourcing, as indicated by exceptionally short homework completion time coupled with high homework scores. AI users who maintain similar homework completion time as non-AI users experience small learning losses.

AI, Quantum And The New Cybersecurity Framework Imperative

Understanding these technologies through the lens of resilience, rather than just innovation, is critical for cybersecurity leaders planning for the coming decade.

The key cybersecurity issue of the coming decade will not prevent every breach. It will be about maintaining trust and resilience in an age of increasing digital interdependence.

Organizations that embrace adaptive risk management, quantum preparedness, responsible AI governance, and resilience-by-design will be well-positioned to succeed in the Acceleration Era. The future belongs not only to the most inventive but also to the most trustworthy and resilient businesses.

Is Quantum Information More Fundamental Than Reality? | Vlatko Vedral

What if quantum information is more fundamental than space, time, matter, or even quantum mechanics itself?

Vlatko Vedral explores the implications of a Q-number-based reality for quantum gravity, pre-Big-Bang cosmology, the nature of time, and the possibility that quantum information lies beneath our deepest physical theories.

1:25 Quantum Gravity and Q Numbers.
4:30 Before the Big Bang.
7:42 Time, the Block Universe, and Q Numbers.
11:56 Quantum Mechanics at All Scales.
14:01 The Next Revolution in Physics.

Vlatko Vedral is a Serbian-born British physicist. He is best known for his contributions to quantum information theory, quantum mechanics, and quantum entanglement. He earned his Bachelor of Science and Doctor of Philosophy degrees from Imperial College London, where he graduated with a PhD.

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Maths is Cooked: AI’s Latest Breakthrough — And What’s Next

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As AI continues to improve its reasoning abilities, mathematicians are increasingly worried about the computer algorithms replacing them. In late May, those fears got even worse when OpenAI revealed that one of its general-purpose reasoning models had written a proof solving a math problem that’s sat unsolved for more than 80 years. But should they actually be worried? Let’s take a look.

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