The Invisible Scale: Measuring AI’s Return on Energy

The Coin of Energy: Efficiency Paying for Itself
Image Credit: Scientific Frontline

In the public imagination, Artificial Intelligence is often visualized as a chatbot writing a poem or a generator creating a surreal image. This trivializes the technology and magnifies the scrutiny on its energy consumption. When AI is viewed as a toy, its electricity bill seems indefensible.

But when viewed as a scientific instrument—akin to a particle accelerator or an electron microscope—the equation shifts. The question is not "How much power does AI use?" but rather "What is the return on that energy investment?"

When measured across a single human lifetime, the dividends of AI in time, cost, and survival are staggering.

Paleontology: In-Depth Description

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Paleontology is the scientific study of the history of life on Earth as based on fossils. It examines the origins, evolution, distribution, and extinction of ancient organisms, seeking to reconstruct the biological and environmental history of our planet spanning over 3.5 billion years.

Chew on this: Losing teeth weakens key memory hub in mouse brains

Mice that lost their molars showed significant memory decline despite receiving the same diet as controls, hinting at the impact of reduced chewing on brain health.
Illustration Credit: Rie Hatakeyama

Tooth loss doesn’t just make eating harder, it may also make thinking more challenging. A new study from Hiroshima University shows that aging mice missing their molars experience measurable cognitive decline, even when their nutrition remains perfectly intact.

“Tooth loss is common in aging populations, yet its direct neurological impact has remained unclear,” said Rie Hatakeyama, postdoctoral researcher at Hiroshima University’s (HU) Graduate School of Biomedical and Health Sciences and first author of the study. 

What Is: Biological Plasticity

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The Paradigm of the Reactive Genome 

The history of biological thought has long been dominated by a tension between the deterministic rigidity of the genotype and the fluid adaptability of the phenotype. For much of the 20th century, the Modern Synthesis emphasized the primacy of genetic mutation and natural selection, often relegating environmental influence to a mere background filter against which genes were selected. In this view, the organism was a fixed readout of a genetic program, stable and unwavering until a random mutation altered the code. However, a profound paradigm shift has occurred, repositioning the organism not as a static entity but as a dynamic system capable of producing distinct, often dramatically different phenotypes from a single genotype in response to environmental variation. This capacity, known as biological or phenotypic plasticity, is now recognized as a fundamental property of life, permeating every level of biological organization—from the epigenetic modification of chromatin in a stem cell nucleus to the behavioral phase transitions of swarming locusts, and ultimately to the structural rewiring of the mammalian cortex following injury. 

Menopause hormone therapy does not appear to impact dementia risk

Photo Credit: Vitaly Gariev

A major review of prior research has found no evidence that menopause hormone therapy either increases or decreases dementia risk in post-menopausal women, in a new study led by University College London researchers and supported by the University of Exeter. 

The findings, commissioned by the World Health Organization (WHO) and published in The Lancet Healthy Longevity, add much-needed clarity to a hotly debated topic, and reinforce current clinical guidance that menopause hormone therapy, also called hormone replacement therapy or HRT, should be guided by perceived benefits and risks and not for dementia prevention. 

Professor Chris Fox from the University of Exeter Medical School said: “The role of menopause hormone treatment and relationship to dementia is a worry for many women. But our state-of-the-art review indicates there is no evidence that menopause hormone treatment reduces or increases the risk of dementia. When deciding whether to take menopause hormone treatment, reducing one’s risk of dementia should not be part of that decision “ 

Escherichia albertii: The still unfolding journey of a misdiagnosed pathogen

Animal to human bacteria pathways
Escherichia albertii is primarily found in mammals and birds, suggesting it is a novel zoonotic pathogen.
Image Credit: Osaka Metropolitan University

Escherichia albertii, initially identified as Hafnia alvei, by the commercial identification biochemical strip, API 20E, was isolated from an infant with diarrhea in Bangladesh in 1989. However, this bacterium was later renamed as a novel species, E. albertii because of its similarities in biochemical and genetic properties to the genus Escherichia, but different from those of any known species in the genus. E. albertii possesses many pathogenic attributes including a key one, which is the ability to produce attaching and effacing (A/E) lesions in the intestinal mucosa mediated by genes on a 35-kb pathogenicity island called the locus of enterocyte effacement. Therefore, it is a member of the family of A/E pathogens.

Restoring the healthy form of a protein could revive blood vessel growth in premature infants’ lungs

A blood vessel organoid.
Video Credit: Yunpei Zhang and Enbo Zhu, Mingxia Gu Lab

A UCLA-led research team has discovered a molecular switch that determines whether tiny blood vessels in premature infants’ lungs can regenerate after injury. A failure of this repair process is a hallmark of bronchopulmonary dysplasia, or BPD, a serious lung disease that affects babies born very early. It arises from a combination of premature birth, inflammation or infection, and exposure to the high levels of oxygen and breathing support that are necessary to keep these infants alive during a critical period of lung development.

The researchers found that in BPD, the blood vessel cells in the lungs begin producing a shortened, nonfunctional isoform — a version of a protein — called NTRK2, which has been extensively studied in the nervous system but not in the pulmonary vasculature. When this shortened isoform dominates, the lung cannot rebuild the delicate network of tiny blood vessels needed for healthy breathing.

Why can’t powerful AIs learn basic multiplication?

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These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated reasoning. 

But when it comes to four-digit multiplication, a task taught in elementary school, even state-of-the-art systems fail. Why? 

A new paper by University of Chicago computer science Ph.D. student Xiaoyan Bai and faculty co-director of the Data Science Institute's Novel Intelligence Research Initiative Chenhao Tan finds answers by reverse-engineering failure and success.

They worked with collaborators from MIT, Harvard University, University of Waterloo and Google DeepMind to probe AI’s “jagged frontier”—a term for its capacity to excel at complex reasoning yet stumble on seemingly simple tasks.

Oncology: In-Depth Description

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Oncology is the branch of medicine and biology dedicated to the study, diagnosis, treatment, and prevention of cancer. Derived from the Greek word onkos (meaning "mass" or "bulk"), this field focuses on understanding neoplasms (tumors) and the complex biological mechanisms that cause uncontrolled cell division. The primary goal of oncology is to improve patient survival and quality of life through the development of therapeutic interventions and the early detection of malignancies.

The Quest for the Synthetic Synapse

Spike Timing" difference (Biology vs. Silicon)
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The modern AI revolution is built on a paradox: it is incredibly smart, but thermodynamically reckless. A large language model requires megawatts of power to function, whereas the human brain—which allows you to drive a car, debate philosophy, and regulate a heartbeat simultaneously—runs on roughly 20 watts, the equivalent of a dim lightbulb.

To close this gap, science is moving away from the "Von Neumann" architecture (where memory and processing are separate) toward Neuromorphic Computing—chips that mimic the physical structure of the brain. This report analyzes how close we are to building a "synthetic synapse."