Lifeboat Foundation

The secret to cellular youth may depend on keeping the nucleolus—a condensed structure inside the nucleus of a cell—small, according to Weill Cornell Medicine investigators. The findings were elucidated in yeast, a model organism famous for making bread and beer and yet surprisingly similar to humans on the cellular level.

The study, published Nov. 25 in Nature Aging, may lead to new longevity treatments that could extend human lifespan. It also establishes a mortality timer that reveals how long a cell has left before it dies.

As people get older, they are more likely to develop health conditions, such as cancer, cardiovascular disease and neurodegenerative diseases.

Conventional components perform incredibly inefficiently at these sub-freezing temperatures, the scientists said. They’re also very hard to maintain — as more and more qubits are added to a system, the more heat is emitted, which makes it more difficult and expensive to sustain these ultralow temperatures.

Because the new transistor — dubbed the “cryo-CMOS transistor” — is optimized to operate at temperatures under 1 K and emit near-zero heat, it offers plenty of advantages over traditional electronics, representatives of the Finnish company SemiQon, which developed the transistor, said in a statement.

The genome-editing technology can be supercharged by artificial intelligence—and the results are already being felt.

Summary: Researchers have developed a new method to profile gene activity in the living human brain, offering new insights into neurological conditions like epilepsy. By analyzing RNA and DNA collected from electrodes implanted in patients’ brains, the study linked molecular data with electrical recordings of seizures, creating a detailed snapshot of gene activity.

This approach enhances understanding of seizure networks, potentially improving the precision of epilepsy surgeries for patients who don’t respond to medication. Beyond epilepsy, the method could have applications in studying Alzheimer’s, Parkinson’s, and schizophrenia, advancing knowledge of brain disorders at the molecular level.

The Model Context Protocol connects an AI system to multiple data sources, which Anthropic says can eliminate the need to create custom code for each one.

Ed Boyden is a professor at the MIT Media Lab working on the most advanced brain-computer interfacing technology currently available, optogenetics. At Singularity Summit 2009.

This is the first symposium of Xapiens at MIT — “The Future of Homo Sapiens”

The future of our species will be majorly influenced by the technical advancements and ethical paradigm shifts over the next several decades. Artificial intelligence, neural enhancement, gene editing, solutions for aging and interplanetary travel, and other emerging technologies are bringing sci-fi’s greatest ideas to reality.

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https://scirate.com/arxiv/2411.

Researchers present a #quantummachinelearning advantage of families of constant depth local quantum circuits over reasonably constrained log-log-depth classical circuits.

Quantum…

One of the core challenges of research in quantum computing is concerned with the question whether quantum advantages can be found for near-term quantum circuits that have implications for practical applications. Motivated by this mindset, in this work, we prove an unconditional quantum advantage in the probably approximately correct (PAC) distribution learning framework with shallow quantum circuit hypotheses. We identify a meaningful generative distribution learning problem where constant-depth quantum circuits using one and two qubit gates (QNC^0) are superior compared to constant-depth bounded fan-in classical circuits (NC^0) as a choice for hypothesis classes. We hence prove a PAC distribution learning separation for shallow quantum circuits over shallow classical circuits. We do so by building on recent results by Bene Watts and Parham on unconditional quantum advantages for sampling tasks with shallow circuits, which we technically uplift to a hyperplane learning problem, identifying non-local correlations as the origin of the quantum advantage.

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