Lifeboat Foundation

In a new study in Nature Machine Intelligence, researchers Bojian Yin and Sander Bohté from the HBP partner Dutch National Research Institute for Mathematics and Computer Science (CWI) demonstrate a significant step towards artificial intelligence that can be used in local devices like smartphones and in VR-like applications, while protecting privacy.

They show how brain-like neurons combined with novel learning methods enable training fast and energy-efficient spiking neural networks on a large scale. Potential applications range from wearable AI to speech recognition and Augmented Reality.

While modern artificial neural networks are the backbone of the current AI revolution, they are only loosely inspired by networks of real, biological neurons such as our brain. The brain however is a much larger network, much more energy-efficient, and can respond ultra-fast when triggered by external events. Spiking neural networks are special types of neural networks that more closely mimic the working of biological neurons: the neurons of our nervous system communicate by exchanging electrical pulses, and they do so only sparingly.

Year 2013 😗😁

Shamees Aden, a British designer and scientist, has come up with a concept for a pair of self-repairing shoes of synthetic protocell materials.

Protocells are molecules that on their own are not alive, but when used with other types of protocells can mimic the properties of living organisms. They react to heat, light and pressure like live cells.

Continue reading “New self-repairing bio-shoe concept unveiled” »

Mathematicians have uncovered a universal explanatory framework that provides a “window into evolution.” This framework explains how molecules interact with each other in adapting to changing conditions while still maintaining tight control over essential properties that are crucial for survival.

According to Dr. Araujo from the QUT School of Mathematical Sciences, the research results provide a blueprint for the creation of signaling networks that are capable of adapting across all life forms and for the design of synthetic biological systems.

“Our study considers a process called robust perfect adaptation (RPA) whereby biological systems, from individual cells to entire organisms, maintain important molecules within narrow concentration ranges despite continually being bombarded with disturbances to the system,” Dr. Araujo said.

Researchers have created atomically thin artificial neurons capable of processing both light and electric signals for computing. The material enables the simultaneous existence of separate feedforward and feedback paths within a neural network, boosting the ability to solve complex problems.

For decades, scientists have been investigating how to recreate the versatile computational capabilities of biological neurons to develop faster and more energy-efficient machine learning systems. One promising approach involves the use of memristors: electronic components capable of storing a value by modifying their conductance and then utilizing that value for in-memory processing.

However, a key challenge to replicating the complex processes of biological neurons and brains using memristors has been the difficulty in integrating both feedforward and feedback neuronal signals. These mechanisms underpin our cognitive ability to learn complex tasks, using rewards and errors.

face_with_colon_three 2022 Microbes can now clean up plastics in lakes, streams, and oceans eventually.

Ultra-high resolution mass spectrometry revealed that plastic bags leach labile compounds. Bioassays performed in Scandinavian lakes indicated that these compounds are incorporated into biomass faster and more efficiently than natural organic matter.

Neural networks are distributed computing structures inspired by the structure of a biological brain and aim to achieve cognitive performance comparable to that of humans but in a much shorter time.

These technologies now form the basis of machine learning and artificial intelligence systems that can perceive the environment and adapt their own behavior by analyzing the effects of previous actions and working autonomously. They are used in many areas of application, such as speech and image recognition and synthesis, autonomous driving and augmented reality systems, bioinformatics, genetic and molecular sequencing, and high-performance computing technologies.

Compared to conventional computing approaches, in order to perform complex functions, neural networks need to be initially “trained” with a large amount of known information that the network then uses to adapt by learning from experience. Training is an extremely energy-intensive process and as computing power increases, the neural networks’ consumption grows very rapidly, doubling every six months or so.

An artificial photosynthesis system that combines semiconducting nanoparticles with a non-photosynthetic bacterium could offer a promising new route for producing sustainable solar-driven hydrogen fuel.

Other artificial photosynthesis systems that integrate nanomaterials into living microbes have been developed before, which reduce carbon dioxide or produce hydrogen, for example. However, usually it is the microorganism itself that makes the product via a metabolic pathway, which is aided by a light-activated nanomaterial that supplies necessary electrons.

Now, the labs of Kara Bren and Todd Krauss at the University of Rochester, US, have turned this concept on its head. They have designed a new hybrid bio-nano system that combines a finely-tuned photocatalytic semiconducting nanoparticles to make hydrogen with a bacterium which, while it does not photosynthesise or make hydrogen itself, it provides the necessary electrons to the nanomaterial to synthesise hydrogen.

Universal computation has significant real-world implications in fields such as computer science, physics, biology, and beyond. It is highly relevant to simulation metaphysics and its idea that the physical world could be a type of computer simulation.

Why do some people live lawful lives, while others gravitate toward repeated criminal behavior? Do people choose to be moral or immoral, or is morality simply a genetically inherited function of the brain? Research suggests that psychopathy as a biological condition explained by defective neural circuits that mediate empathy, but what does that mean when neuroscience is used as evidence in criminal court? How can understanding neuroscience give us an insight into the actions and behaviors of our political leaders?

Forensic psychiatrist Dr. Octavio Choi https://med.stanford.edu/profiles/ochoi will explore how emerging neuroscience challenges long-held assumptions underlying the basis—and punishment—of criminal behavior.

Continue reading “The Neuroscience of Real Life Monsters: Psychopaths, CEOs, & Politicians (Science on Tap Livestream)” »