Lifeboat Foundation

I found this on NewsBreak: #Design

Leveraging advanced computational techniques in physical sciences has become vital for accelerating scientific discovery. This involves integrating large language models (LLMs) and simulations to enhance hypothesis generation, experimental design, and data analysis. Automating these processes aims to streamline and democratize access to cutting-edge research tools, pushing the boundaries of scientific knowledge and improving efficiency across various scientific domains.

Researchers face a significant challenge in effectively simulating observational feedback and integrating it with theoretical models in physical sciences. Traditional methods often need a universal approach that can be applied across various scientific fields, leading to inefficiencies and limiting the potential for innovative discoveries. The need for a more comprehensive and adaptable framework is evident to address this issue and advance scientific inquiry.

Continue reading “This AI Paper Introduces the Scientific Generative Agent: A Unified Machine Learning Framework for Cross-Disciplinary Scientific Discovery” »

The codes to replicate the simulations of the paper: Available at: https://arxiv.org/abs/2405.12832 and also: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4835325

For now, we just added the codes to…

In this paper, we introduce Wav-KAN, an innovative neural network architecture that leverages the Wavelet Kolmogorov-Arnold Networks (Wav-KAN) framework to enhance interpretability and performance. Traditional multilayer perceptrons (MLPs) and even recent advancements like Spl-KAN \cite{kan} face challenges related to interpretability, training speed, robustness, computational efficiency, and performance. Wav-KAN addresses these limitations by incorporating wavelet functions into the Kolmogorov-Arnold network structure, enabling the network to capture both high-frequency and low-frequency components of the input data efficiently. Wavelet-based approximations employ orthogonal or semi-orthogonal basis and also maintains a balance between accurately representing the underlying data structure and avoiding overfitting to the noise. Analogous to how water conforms to the shape of its container, Wav-KAN adapts to the data structure, resulting in enhanced accuracy, faster training speeds, and increased robustness compared to Spl-KAN and MLPs. Our results highlight the potential of Wav-KAN as a powerful tool for developing interpretable and high-performance neural networks, with applications spanning various fields. This work sets the stage for further exploration and implementation of Wav-KAN in frameworks such as PyTorch, TensorFlow, and also it makes wavelet in KAN in wide-spread usage like nowadays activation functions like ReLU, sigmoid in universal approximation theory (UAT).

In this pivotal Spring 2024 edition of “The Xsolla Report: The State of Play,” Xsolla delves into the evolving dynamics and innovations shaping our industry, emphasizing the burgeoning realm of mobile gaming.

To kickstart innovation follow the insider startup knowledge about charisma, “well-rounded square pegs” and rock-solid teams.

Sharp-7 employs an 8MP automotive-grade sensor, ensuring consistent, high-quality imaging across various temperatures in automotive environments.

Aiding in advancing future automotive safety systems, Sheba Microsystems has launched a novel autofocus camera.

Sharp-7 pioneers autofocus in automotive cameras, ensuring high-quality imaging despite temperature fluctuations, crucial for ADAS.

Continue reading “Driving innovation: Sheba unveils world’s first autofocus car camera” »

Engineers from University of Glasgow and colleagues from the U.K. and Australia are behind a research breakthrough in a developing form of wireless communications could help precisely pinpoint the locations of people and objects indoors.

*BREAKTHROUGH!!*

Scientists may one day be able to freeze brains and bring them back to life following a major breakthrough in cryogenics.

Researchers in China have successfully frozen and thawed human brain tissue, after which it regained normal function.

Continue reading “Frozen brain tissue brought back to life in major breakthrough” »

Researchers at Pohang University of Science and Technology (POSTECH) have achieved a breakthrough in surpassing the limitations of traditional acoustic metalenses. They have successfully developed the first wide field-of-hearing metalens. Their research has been published in Nature Communications.

In a scientific breakthrough, Mount Sinai researchers have revealed the biological mechanisms by which a family of proteins known as histone deacetylases (HDACs) activate immune system cells linked to inflammatory bowel disease (IBD) and other inflammatory diseases.

This discovery, reported in Proceedings of the National Academy of Sciences (PNAS), could potentially lead to the development of selective HDAC inhibitors designed to treat types of IBD such as ulcerative colitis and Crohn’s disease.

“Our understanding of the specific function of class II HDACs in different cell types has been limited, impeding development of therapies targeting this promising drug target family,” says senior author Ming-Ming Zhou, PhD, Dr. Harold and Golden Lamport Professor in Physiology and Biophysics and Chair of the Department of Pharmacological Sciences at the Icahn School of Medicine at Mount Sinai. “Through our proof-of-concept study, we’re unraveling the mechanisms of class II HDACs, providing essential knowledge to explore their therapeutic potential for safer and more effective disease treatments.”