Lifeboat Foundation: Safeguarding Humanity
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Blog – Page 306

In February 2024, Reddit struck a $60 million deal with Google to let the search giant use data on the platform to train its artificial intelligence models. Notably absent from the discussions were Reddit users, whose data were being sold.

The deal reflected the reality of the modern internet: Big tech companies own virtually all our online data and get to decide what to do with that data. Unsurprisingly, many platforms monetize their data, and the fastest-growing way to accomplish that today is to sell it to AI companies, who are themselves massive tech companies using the data to train ever more powerful models.

The decentralized platform Vana, which started as a class project at MIT, is on a mission to give power back to the users. The company has created a fully user-owned network that allows individuals to upload their data and govern how they are used. AI developers can pitch users on ideas for new models, and if the users agree to contribute their data for training, they get proportional ownership in the models.

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A team of materials scientists, chemical engineers, and environmental scientists affiliated with a host of institutions in China has developed a redox flow battery (RFB) with 87.9% energy efficiency, which can also last for 850 cycles. In their project, published in the journal Nature Communications, the group developed a new kind of catalytic electrode to improve the efficiency of the battery.

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Decentralized yet coordinated networks of specialized artificial intelligence agents, multi-agent systems for healthcare (MASH), that excel in performing tasks in an assistive or autonomous manner within specific clinical and operational domains are likely to become the next paradigm in medical artificial intelligence.

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Recent studies have shown that mechanical properties such as extracellular matrix stiffness, fluid flow, weight loading, compression, and stretching can affect cellular functions. Some examples of cell responses to mechanical properties could be the migration of cancer cells from rigid to soft surfaces or the differentiation of fibroblasts into myofibroblasts. Cellular responses to mechanical changes can modify the insertion of proteins in the extracellular matrix (ECM), causing an increase in tissue stiffness with functional consequences. In general, mechanical and physical factors can affect any kind of cell phenotype in culture conditions and in vivo tissues. Cells sense mechanical stimuli by applying force and restructuring their shape and functions in response to the resistance of the stimuli. Furthermore, mechanical triggers can develop a “memory” for altering cellular plasticity and adaptation. This phenomenon is called cellular mechanical memory (CMM), a singular feature of mesenchymal stem cells (MSCs). Controlled targeting of CMM may resolve the scarcity of viable cells needed for cell based therapy (CBT) and implement studies concerning cancer research, fibrosis, and senescence. This review focusses on cells from the mesodermal lineage, such as MSCs, fibroblasts and chondrocytes, and the role of CMM as a potential target for CBT.

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A new model of Alzheimer’s disease has been proposed, which could speed up efforts to understand and cure the complex condition – while bringing all manifestations of the condition under one unifying theory.

Researchers from Arizona State University suggest that stress granules – protein and RNA clumps that form around cells in stressful conditions due to genetic and environmental risk factors – are the primary culprit behind the disease.

In their new study, the team reviewed data from multiple health databases and past papers – particularly a 2022 study on Alzheimer’s progression – to identify widespread changes in gene expression that come with it.

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Fast-charging lithium-ion batteries are ubiquitous, powering everything from cellphones and laptops to electric vehicles. They’re also notorious for overheating or catching fire.

Now, with an innovative computational model, a University of Wisconsin–Madison has gained new understanding of a phenomenon that causes lithium-ion batteries to fail.

Developed by Weiyu Li, an assistant professor of mechanical engineering at UW–Madison, the model explains lithium plating, in which fast charging triggers metallic lithium to build up on the surface of a battery’s anode, causing the battery to degrade faster or catch fire.

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