Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: information science – Page 18

The improved accuracy of MNT reaction predictions provided by this model could facilitate the production of isotopes that are difficult to generate using other methods. These isotopes are valuable for scientific research and , such as diagnostics and treatments. According to Prof. Zhang, the goal is to keep the model comprehensive yet practical for experimental use.

This development represents a step forward in , contributing to the understanding of exotic nuclei production through MNT reactions. Further refinement of the model may enhance its utility in guiding future research and improving rare isotope production processes.

This research was conducted in collaboration with Beijing Normal University, Beijing Academy of Science and Technology, and the National Laboratory of Heavy Ion Accelerator of Lanzhou.

Read more | >

Koo and his team tested CREME on another AI-powered DNN genome analysis tool called Enformer. They wanted to know how Enformer’s algorithm makes predictions about the genome. Koo says questions like that are central to his work.

“We have these big, powerful models,” Koo said. “They’re quite compelling at taking DNA sequences and predicting gene expression. But we don’t really have any good ways of trying to understand what these models are learning. Presumably, they’re making accurate predictions because they’ve learned a lot of the rules about gene regulation, but we don’t actually know what their predictions are based off of.”

With CREME, Koo’s team uncovered a series of genetic rules that Enformer learned while analyzing the genome. That insight may one day prove invaluable for drug discovery. The investigators stated, “CREME provides a powerful toolkit for translating the predictions of genomic DNNs into mechanistic insights of gene regulation … Applying CREME to Enformer, a state-of-the-art DNN, we identify cis-regulatory elements that enhance or silence gene expression and characterize their complex interactions.” Koo added, “Understanding the rules of gene regulation gives you more options for tuning gene expression levels in precise and predictable ways.”

Read more | >

What I believe is that symmetry follows everything even mathematics but what explains it is the Fibonacci equation because it seems to show the grand design of everything much like physics has I believe the final parameter of the quantified parameter of infinity.

Recent explorations of unique geometric worlds reveal perplexing patterns, including the Fibonacci sequence and the golden ratio.

Read more | >

Augmented reality (AR) takes digital images and superimposes them onto real-world views. But AR is more than a new way to play video games; it could transform surgery and self-driving cars. To make the technology easier to integrate into common personal devices, researchers report in ACS Photonics how to combine two optical technologies into a single, high-resolution AR display. In an eyeglasses prototype, the researchers enhanced image quality with a computer algorithm that removed distortions.

Read more | >

The large language models that have increasingly taken over the tech world are not “cheap” in many ways. The most prominent LLMs, such as GPT-4, took some $100 million to build in the form of legal costs of accessing training data, computational power costs for what could be billions or trillions of parameters, the energy and water needed to fuel computation, and the many coders developing the training algorithms that must run cycle after cycle so the machine will “learn.”

But, if a researcher needs to do a specialized task that a machine could do more efficiently and they don’t have access to a large institution that offers access to generative AI tools, what other options are available? Say, a parent wants to prep their child for a difficult test and needs to show many examples of how to solve complicated math problems.

Building their own LLM is an onerous prospect for costs mentioned above, and making direct use of the big models like GPT-4 and Llama 3.1 might not immediately be suited for the complex in logic and math their task requires.

Read more | >

New study suggests that black holes may not be the featureless, structureless entities that Einstein’s general theory of relativity predicts them to be.

The frozen star is a recent proposal for a nonsingular solution of Einstein’s equations that describes an ultracompact object which closely resembles a black hole from an external perspective. The frozen star is also meant to be an alternative, classical description of an earlier proposal, the highly quantum polymer model. Here, we show that the thermodynamic properties of frozen stars closely resemble those of black holes: frozen stars radiate thermally, with a temperature and an entropy that are perturbatively close to those of black holes of the same mass. Their entropy is calculated using the Euclidean-action method of Gibbons and Hawking. We then discuss their dynamical formation by estimating the probability for a collapsing shell of “normal’’ matter to transition, quantum mechanically, into a frozen star.

Read more | >

Coronary artery disease (CAD) is the most common cause of illness-based death throughout the world. According to the World Health Organization, CAD causes 17.9 million deaths per year worldwide, nearly one-third of all illness-based deaths annually.

Coronary angiography is currently the best method of confirming a CAD diagnosis, but it is expensive and invasive, poses risks to patients, and is not suitable for early diagnosis and assessing disease risk.

Seeking a safer, lower-cost and more efficient diagnostic method, a research team from Beijing University of Chinese Medicine’s School of Traditional Chinese Medicine, Beijing University of Chinese Medicine’s School of Life Science, and Hunan University of Chinese Medicine’s School of Traditional Chinese Medicine has used artificial intelligence (AI) to develop a diagnostic algorithm based on tongue imaging. Their work is published in Frontiers in Cardiovascular Medicine.

Read more | >

The potential pathways through which AI could help us escape a simulated reality are both fascinating and complex. One approach could involve AI discovering and manipulating the underlying algorithms that govern the simulation. By understanding these algorithms, AI could theoretically alter the simulation’s parameters or even create a bridge to the “real” world outside the simulation.

Another approach involves using AI to enhance our cognitive and perceptual abilities, enabling us to detect inconsistencies or anomalies within the simulation. These anomalies, often referred to as “glitches,” could serve as clues pointing to the artificial nature of our reality. For instance, moments of déjà vu or inexplicable phenomena might be more than just quirks of human perception—they could be signs of the simulation’s imperfections.

While the idea of escaping a simulation is intriguing, it also raises profound ethical and existential questions. For one, if we were to confirm that we are indeed living in a simulation, what would that mean for our understanding of free will, identity, and the meaning of life? Moreover, the act of escaping the simulation could have unforeseen consequences. If the simulation is designed to sustain and nurture human life, breaking free from it might expose us to a harsher and more dangerous reality.

Read more | >