A research team from Tohoku University and Kyocera Corp. has developed a new magneto-optical material—a nanocomposite magnetic garnet film—that can be deposited directly onto silicon substrates while delivering a magneto-optical figure of merit four times higher than conventional polycrystalline films.
Using this material, the team demonstrated a monolithically integrated optical isolator on a silicon chip that matches the performance of conventional devices but with a far simpler, seed-layer-free structure. The breakthrough opens a practical path toward large-scale deployment of silicon photonics in AI-era data centers.
The work is published in the journal ACS Applied Optical Materials.
🧠⚛️ 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.
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.
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 \.
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.
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.
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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.
Pengfei Sun et al. develop a spiking neural network with a dual memory pathway, co-designed with a custom neuromorphic chip. The approach delivers over 4× throughput and 5x energy efficiency gains while using 40–60% fewer parameters than state-of-the-art implementations.
Google is using AI to map the human brain, generate synthetic neurons, and speed up one of the most ambitious neuroscience projects ever attempted. But as brain mapping, connectomics, and AI brain decoding move forward, a terrifying question appears: what happens to mental privacy when machines can understand the brain better than we do?
This mini-documentary explores Google’s brain mapping research, synthetic neurons, AI mind decoding, neural privacy, and the future of human thought in the age of artificial intelligence.
CHAPTERS: 00:00 Google’s Brain Mapping Project. 02:00 The Scale of the Human Brain. 04:36 Synthetic Neurons Explained. 06:40 AI Is Already Decoding Thoughts. 10:15 The Rise of Neural Privacy. 14:51 Brain Maps and the Future of AI 17:11 Who Owns Your Mind?
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