Lifeboat Foundation

A new study reveals that the iconic extinct Megalodon or megatooth shark grew to larger sizes in cooler environments than in warmer areas.

DePaul University paleobiology professor Kenshu Shimada and coauthors take a renewed look through time and space at the body size patterns of Otodus megalodon, the fossil shark that lived nearly worldwide roughly 15 to 3.6 million years ago. The new study appears in the international journal Historical Biology.

Otodus megalodon is commonly portrayed as a gigantic, monstrous shark in novels and films, such as the 2018 sci-fi thriller “The Meg.” In reality, this species is only known from teeth and vertebrae in the fossil record, although it is generally accepted scientifically that the species was indeed quite gigantic, growing to at least 50 feet (15 meters) and possibly as much as 65 feet (20 meters). The new study re-examined published records of geographic occurrences of Megalodon teeth along with their estimated total body lengths.

It should come as little surprise that pioneering work in biological robotics is as controversial as it is exciting. Take for example the article published in December 2021 in the Proceedings of the National Academy of Sciences by Sam Kreigman and Douglas Blackiston at Tufts University and colleagues. This article, entitled “Kinematic self-replication in reconfigurable organisms,” is the third installment of the authors’ “xenobots” series.

Neural networks have become a hot topic over the last decade, put to work on jobs from recognizing image content to generating text and even playing video games. However, these artificial neural networks are essentially just piles of maths inside a computer, and while they are capable of great things, the technology hasn’t yet shown the capability to produce genuine intelligence.

Cortical Labs, based down in Melbourne, Australia, has a different approach. Rather than rely solely on silicon, their work involves growing real biological neurons on electrode arrays, allowing them to be interfaced with digital systems. Their latest work has shown promise that these real biological neural networks can be made to learn, according to a pre-print paper that is yet to go through peer review.

The broad aim of the work is to harness biological neurons for their computational power, in an attempt to create “synthetic biological intelligence”. The general idea is that biological neurons have far more complexity and capability than any neural networks simulated in software. Thus, if one wishes to create a viable intelligence from scratch, it makes more sense to use biological neurons rather than messing about with human-created simulations of such.

There’s only one Universal Consciousness, we individualize our conscious awareness through the filter of our nervous system, our “local” mind, our very inner subjectivity, but consciousness itself, the Self in a greater sense, our “core” self is universal, and knowing it through experience has been called enlightenment, illumination, awakening, or transcendence, through the ages.

Here’s Consciousness: Evolution of the Mind (2021), Part IV: UNIVERSAL CONSCIOUSNESS

Continue reading “Universal Consciousness | Part IV of Consciousness: Evolution of the Mind (2021) Documentary” »

Nature is a never-ending source of inspiration for scientists, but our artificial devices usually don’t communicate well with the real thing. Now, researchers at Linköping University have created artificial organic neurons and synapses that can integrate with natural biological systems, and demonstrated this by making a Venus flytrap close on demand.

The new artificial neurons build on the team’s earlier versions, which were organic electrochemical circuits printed onto thin plastic film. Since they’re made out of polymers that can conduct either positive or negative ions, these circuits form the basis of transistors. In the new study, the team optimized these transistors and used them to build artificial neurons and synapses, and connect them to biological systems.

When the transistors detect concentrations of ions with certain charges, they switch, producing a signal that can then be picked up by other neurons. Importantly, biological neurons operate on these same ion signals, meaning artificial and natural nerve cells can be connected.

🚨 A major breakthrough.

Scientists have successfully implanted an artificial neuron into a Venus Flytrap, in what could be a major breakthrough in the merging of living things and computers.

The neuron was able to control the plant, making its lobes close, the scientists report.

Continue reading “Scientists successfully connect ‘artificial neuron’ to biological cells in major step” »

No he does not respond to the resveratrol challenges. Important here are the chapters concerning Resetting the Ageing Clock and Repeatable Ageing Reversal.

In the final episode of this season, Dr. David Sinclair and Matthew LaPlante focus on current and near-future technologies relevant to health and aging. In addition to discussing the utility of wearable sensors and biological age measurements, they highlight innovative research aimed at reversing biological age. The societal effects of therapies that successfully extend healthspan and/or lifespan are also considered.

Continue reading “Biotracking, Age Reversal & Other Advanced Health Technologies | Lifespan with Dr. David Sinclair #8” »

With the advent of Big Data, current computational architectures are proving to be insufficient. Difficulties in decreasing transistors’ size, large power consumption and limited operating speeds make neuromorphic computing a promising alternative.

Neuromorphic computing, a new brain-inspired computation paradigm, reproduces the activity of biological synapses by using artificial neural networks. Such devices work as a system of switches, so that the ON position corresponds to the information retention or “learning,” while the OFF position corresponds to the information deletion or “forgetting.”

In a recent publication, scientists from the Universitat Autònoma de Barcelona (UAB), the CNR-SPIN (Italy), the Catalan Institute of Nanoscience and Nanotechnology (ICN2), the Institute of Micro and Nanotechnology (IMN-CNM-CSIC) and the ALBA Synchrotron have explored the emulation of artificial synapses using new advanced material devices. The project was led by Serra Húnter Fellow Enric Menéndez and ICREA researcher Jordi Sort, both at the Department of Physics of the UAB, and is part of Sofia Martins Ph.D. thesis.