Lifeboat Foundation

As the world’s population continues to grow and age, the healthcare system in different geographies is inching closer to the brink of collapse. According to the World Health Organization, the current number of health workers, including physicians, radiologists, and other professionals, is not sufficient to handle the rising caseload. On top of it, the increased stress and burnout stemming from the surge in cases is pushing many to exit the field, further reducing the number of practicing workers. Becker Health estimates show that nearly 72,000 American physicians left the workforce between 2021 and 2022, and some 30,000 who will join the workforce will not be enough to meet the growing demand.

At the core, both these challenges – the rising caseload and dwindling workforce – are leaving one major impact: diminished quality of patient care. This is where the much talked about generative AI can come in, saving healthcare staffers valuable time and resources and enabling them to focus on enhancing clinical outcomes.

First off, it’s important to understand AI is not new in healthcare. Organizations have been experimenting with predictive and computer vision algorithms for a while now, most notably to forecast the success of treatments and diagnose dangerous diseases earlier than humans. However, when it comes to generative AI, things are still pretty fresh, given the technology came to the forefront just a couple of years ago with the launch of ChatGPT. Gen AI models use neural networks to identify patterns and structures in existing data and generate new content such as text and images. They are applicable across sectors, including healthcare – where organizations cumulatively generate about 300 petabytes of data every single day.

StudyFinds’ Dr. Faith Coleman looks at the issue of AI in the field of medicine. Is advanced technology ready to take over healthcare?

Meta and Elon Musk’s artificial intelligence (AI) startup, xAI, are both vying for a strategic partnership with Character.ai, an emerging player in the chatbot industry known for its innovative conversational agents. This competition highlights the escalating race in the AI sector to secure influential collaborations that could redefine user interactions with AI technologies.

Background on Character.ai

Character.ai, co-founded by ex-Google engineers Noam Shazeer and Daniel de Freitas, has gained considerable attention for its advanced conversational AI that allows users to interact with digital versions of various personalities, both real and fictional. The platform aims to deliver engaging and plausible dialogues, setting it apart from traditional AI models focused on factual accuracy.

Advancements in qubit technology at the University of Basel show promise for scalable quantum computing, using electron and hole spins to achieve precise qubit control and interactions.

The pursuit of a practical quantum computer is in full swing, with researchers worldwide exploring a wide array of qubit technologies. Despite extensive efforts, there is still no consensus on which type of qubit best maximizes the potential of quantum information science.

Qubits are the foundation of a quantum computer. They’re responsible for processing, transferring, and storing data. Effective qubits must reliably store and rapidly process information. This demands stable, swift interactions among a large number of qubits that external systems can accurately control.

ABSTRACT. The search for extraterrestrial intelligence is currently being pursued using multiple techniques and in different wavelength bands. Dyson spheres, megastructures that could be constructed by advanced civilizations to harness the radiation energy of their host stars, represent a potential technosignature, that in principle may be hiding in public data already collected as part of large astronomical surveys. In this study, we present a comprehensive search for partial Dyson spheres by analysing optical and infrared observations from Gaia, 2MASS, and WISE. We develop a pipeline that employs multiple filters to identify potential candidates and reject interlopers in a sample of five million objects, which incorporates a convolutional neural network to help identify confusion in WISE data. Finally, the pipeline identifies seven candidates deserving of further analysis. All of these objects are M-dwarfs, for which astrophysical phenomena cannot easily account for the observed infrared excess emission.

Simply put, the Hard Problem asks the following question: how can the machinery of the brain (the neurons and synapses) produce consciousness — the colours that we see, for example, or the sounds that we hear?

From pocket-sized AI models to a warp drive breakthrough, check out this week’s awesome tech stories from around the web.

While tantalizing, Alcubierre’s design has a fatal flaw. To provide the necessary distortions of spacetime, the spacecraft must contain some form of exotic matter, typically regarded as matter with negative mass. Negative mass has some conceptual problems that seem to defy our understanding of physics, like the possibility that if you kick a ball that weighs negative 5 kilograms, it will go flying backwards, violating conservation of momentum. Plus, nobody has ever seen any object with negative mass existing in the real universe, ever.

These problems with negative mass have led physicists to propose various versions of “energy conditions” as supplements to general relativity. These aren’t baked into relativity itself, but add-ons needed because general relativity allows things like negative mass that don’t appear to exist in our universe—these energy conditions keep them out of relativity’s equations. They’re scientists’ response to the unsettling fact that vanilla GR allows for things like superluminal motion, but the rest of the universe doesn’t seem to agree.

The energy conditions aren’t experimentally or observationally proven, but they are statements that concord with all observations of the universe, so most physicists take them rather seriously. And until recently, physicists have viewed those energy conditions as making it absolutely 100 percent clear that you can’t build a warp drive, even if you really wanted to.

Dendritic integration theory of consciousness.

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