Why the AI alignment problem is not merely a technical hurdle, but a civilizational rite of passage in the evolution of intelligence
Get the latest international news and world events from around the world.
Cost-Effectiveness of Adjuvant Immunotherapy in Cancer Treatments: A Systematic Review
Adjuvant immunotherapy is increasingly integrated into cancer care to reduce recurrence and improve survival. However, its high cost raises critical concerns regarding affordability and economic value across diverse health system contexts.
This review outlines health gains and economic value, and identifies where future research, pricing reform, or prioritization are needed to support evidence-informed policymaking and sustainable use of immunotherapy in cancer treatment pathways.
Question Is adjuvant immunotherapy cost-effective across cancer types?
Findings This systematic review including 69 economic evaluations (2015−2025) found that adjuvant checkpoint inhibitors, usually single-agent, were associated with higher quality-adjusted life-year/life-year gains and were determined to be cost-effective by 40 studies (58%), with the strongest signals in non−small cell lung cancer and melanoma, particularly in early-stage/high-risk populations, and for some combination regimens. Industry-funded studies more frequently reported cost-effective decisions and findings were sensitive to drug prices, model assumptions, and country-specific willingness-to-pay thresholds.
Meaning These findings suggest that adjuvant immunotherapy can offer good value for money in selected high-risk settings; decisions should be indication-specific, aligned with local health technology assessment thresholds, and supported by price negotiation or managed-entry agreements.
Artificial Intelligence Isn’t the Problem We Should Fear
Artificial intelligence is often discussed as a technological threat, yet the deeper challenge lies not within the machines themselves, but within the values guiding how humanity chooses to use this unprecedented form of power.
Throughout history, every major leap in automation has multiplied productivity while simultaneously concentrating influence in the hands of those who control it. The emergence of artificial intelligence represents the most powerful form of automation ever created, capable of reshaping economies, redefining work, and transforming the nature of human connection itself.
This conversation explores how AI amplifies existing human systems rather than replacing them, why questions of power, wealth, authenticity, and trust are becoming more important than technological capability, and how the future shaped by artificial intelligence will ultimately reflect human intentions rather than machine decisions.
The technology is neutral. The outcome is not.
#AI #ArtificialIntelligence #Future #Technology #MoGawdat
Read more
AI data centers need faster links: A mass-producible optical microchip could help
Researchers at Karlsruhe Institute of Technology (KIT) and École Polytechnique Fédérale de Lausanne (EPFL) present a novel component that enables very fast, economical, and reliable data transmission thanks to an advanced manufacturing technology. Their new electro-optical modulator transmits data efficiently through fiber-optic cables and can be manufactured inexpensively in large quantities on standard semiconductor wafers. This is important, as AI applications and growing data traffic are pushing data centers and fiber-optic networks to their performing limits. The researchers present their findings in Nature Communications.
Similar to modern computer chips, the modulator can be manufactured using established semiconductor processes. The researchers combine lithium tantalate —a material that guides light particularly well and serves as the heart of the modulator—with a proven chip manufacturing technique from microelectronics. To date, these two technologies have never been used together. For the first time now, they enable reliable mass production.
Fiber-optic sensors reveal how farming destroys soil’s natural structure
Soil is often perceived simply as “dirt,” but in reality, it is a dynamic, living system that acts as Earth’s natural sponge. Unfortunately, common agricultural practices—including deep plowing and the use of heavy machinery—can severely disrupt this natural system, according to a new study led by Dr. Shi Qibin from the Institute of Geology and Geophysics of the Chinese Academy of Sciences, in collaboration with international partners.
The study, published in Science, shows that healthy soil contains a natural internal “plumbing” network of microscopic pores and channels that allow water to infiltrate deeply into the ground, where it becomes available to plant roots.
Frequent plowing or heavy tractor traffic not only disrupts soil structure but also reduces its ability to help crops withstand both flooding and drought.
Researchers design a pioneering drug capable of reversing cognitive decline in Alzheimer’s disease in animal models
A team from the Institute of Neurosciences of the University of Barcelona (UBneuro) has designed and validated in animal models an innovative compound with a pioneering mechanism of action for the treatment of Alzheimer’s disease. Unlike current drugs, which mainly remove beta-amyloid plaques that accumulate in the brain, this new experimental drug reprogrammes the neuronal epigenome by correcting alterations in gene expression that contribute to the progression of the disease. The results of this study, published in Molecular Therapy, open the door to an epigenetic-based therapeutic strategy to fight Alzheimer’s disease.
“The compound FLAV-27 represents an innovative and promising approach to Alzheimer’s disease, with the potential to modify the disease process, as it acts not only on its symptoms or a single pathological biomarker, but directly on its underlying molecular mechanisms,” says Aina Bellver, a researcher at the UB Institute of Neurosciences (UBneuro) and first author of the paper.
The study was led by Christian Griñán and Mercè Pallàs, UBneuro researchers and Professors from the Faculty of Pharmacy and Food Sciences. Th work was performed with the participation of researchers from the CIBER Area for Neurodegenerative Diseases (CIBERNED), as well as the UB Institute of Biomedicine (IBUB), the Institute of Nutrition and Food Safety (INSA-UB), the August Pi i Sunyer Biomedical Research Institute (IDIBAPS) and other national and international institutions.
Neuro-symbolic AI could slash energy use while dramatically improving performance
Power usage by AI and data center systems in the U.S. is extraordinary by any measure. The International Energy Agency estimates U.S. AI and data centers used about 415 terawatt hours of power in 2024—more than 10% of that year’s nationwide energy output—and it’s expected to double by 2030.
Seeking to head off this unsustainable path of power consumption, researchers at the School of Engineering have developed a proof-of-concept for efficient AI systems that could use 100 times less energy than current ones, while at the same time providing more accurate results on tasks.
The approach developed in the laboratory of Matthias Scheutz, Karol Family Applied Technology Professor, uses neuro-symbolic AI—a combination of conventional neural network AI with symbolic reasoning similar to the way humans break down tasks and concepts into steps and categories.
