Lifeboat Foundation

Now, scientists in China have developed robots that give human-like realistic expressions.

The humanoid robot with highly expressive facial features is developed by Liu Xiaofeng, a professor at Hohai University in east China’s Jiangsu Province, and his research team.

For the development of this robot, the research team developed a new algorithm for generating facial expressions on humanoid robots.

They also found that, although the power achieved by the conventional PSO algorithm was approximately 0.15% higher than that attained by the QPSO algorithm under the same conditions, the QPSO was able to beat the conventional PSO in more challenging conditions.

“Specifically, the quantum algorithm generates 3.33% more power in higher temperature tests and 0.89% more power in partial shading tests,” they emphasized. “Additionally, the quantum algorithm displays lower duty cycles, with a reduction of 3.9% in normal operating conditions, 0.162% in high-temperature tests, and 0.54% in partial shading tests.”

Singularity net Ben goerzel discusses artificial and general intelligence and cosmist intelligence.

Dr. Ben Goertzel discusses artificial general, non-human and cosmist intelligences with Ed Keller at The Overview Effect Lectures, which is a series positioned as a survey of some of the key operational themes critical to post planetary and universal design.

Continue reading “Dr. Ben Goertzel Discusses Artificial General, Non-Human & Cosmist Intelligences” »

Equitable and accessible education in life sciences, bioengineering, and synthetic biology is crucial for training the next generation of scientists. Here the authors present the CRISPRkit, a cost-effective educational tool that enables high school students to perform CRISPR experiments affordably and safely without prior experience, using smartphone-based quantification and an automated algorithm for data analysis.

It’s about to get easier to catch and analyze a high-quality image of fast-moving molecules. Assistant Professor Ioannis Sgouralis, Department of Mathematics, and colleagues have developed an algorithm that adds a new level to microscopy: super-resolution in motion.

All-optical multiplane quantitative phase imaging design eliminates the need for digital phase recovery algorithms.

UCLA researchers have introduced a breakthrough in 3D quantitative phase imaging that utilizes a wavelength-multiplexed diffractive optical processor to enhance imaging efficiency and speed. This method enables label-free, high-resolution imaging across multiple planes and has significant potential applications in biomedical diagnostics, material characterization, and environmental analysis.

Introduction to Quantitative Phase Imaging.

Dark energy remains among the greatest puzzles in our understanding of the cosmos. In the standard model of cosmology called the Lambda-CDM, it is accounted for by adding a cosmological constant term in Einstein’s field equation first introduced by Einstein himself. This constant is very small and positive and lacks a complete theoretical understanding of why it has such a tiny value. Moreover, dark energy has some peculiar features, such as negative pressure and does not dilute with cosmic expansion, which makes at least some of us uncomfortable.

An AI model developed by scientists at King’s College London, in close collaboration with University College London, has produced three-dimensional, synthetic images of the human brain that are realistic and accurate enough to use in medical research.

The model and images have helped scientists better understand what the human brain looks like, supporting research to predict, diagnose and treat brain diseases such as dementia, stroke, and multiple sclerosis.

The algorithm was created using the NVIDIA Cambridge-1, the UK’s most powerful supercomputer. One of the fastest supercomputers in the world, the Cambridge-1 allowed researchers to train the AI in weeks rather than months and produce images of far higher quality.

An algorithm developed by Washington State University researchers can better find data anomalies than current anomaly-detection software, including in streaming data.

The work, reported in the Journal of Artificial Intelligence Research, makes fundamental contributions to artificial intelligence (AI) methods that could have applications in many domains that need to quickly find anomalies in large amounts of data, such as in cybersecurity, power grid management, misinformation, and medical diagnostics.

Being able to better find the anomalies would mean being able to more easily discover fraud, disease in a medical setting, or important unusual information, such as an asteroid whose signals overlap with the light from other stars.