Lifeboat Foundation

What we know about Venus so far has been gathered from several past probes.

With a slightly smaller diameter than Earth, Venus orbits closer to the Sun. This means that any water on the surface would have evaporated shortly after its formation, starting its greenhouse effect. Early and sustained volcanic eruptions created lava plains and increased the carbon dioxide in the atmosphere — starting the runaway greenhouse effect, which increased the temperature from just a little higher than Earth’s to its current high value of 475°C.

While Venus’s year is shorter than ours (225 days), its rotation is very slow (243 days) and “retrograde” — the other way round to Earth. The slow rotation is related to a lack of magnetic field, resulting in a continuing loss of atmosphere. Venus’ atmosphere “super-rotates” faster than the planet itself. Images from many missions show V-shaped patterns of clouds composed of sulphuric acid droplets.

Continue reading “The clouds of Venus may be habitable — a crewed flyby could confirm the theory” »

Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic computing designed to rigorously mimic the human brain with semiconductor devices.

Neuromorphic computing aims to realize artificial intelligence (AI) by mimicking the mechanisms of neurons and synapses that make up the human brain. Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses still remains a challenge. To address these issues, a research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices.

Similar to commercial graphics cards, the artificial synaptic devices previously studied often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost efficiency.

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Continue reading “BI 103 Randal Koene and Ken Hayworth: The Road to Mind Uploading” »

The oldest three-dimensional green algae fossil ever found dates back more than half a billion years and may reveal that plants are older than believed.

The future of neural network computing could be a little soggier than we were expecting.

A team of physicists has successfully developed an ionic circuit – a processor based on the movements of charged atoms and molecules in an aqueous solution, rather than electrons in a solid semiconductor.

Since this is closer to the way the brain transports information, they say, their device could be the next step forward in brain-like computing.

Juncal Arbelaiz Mugica is a native of Spain, where octopus is a common menu item. However, Arbelaiz appreciates octopus and similar creatures in a different way, with her research into soft-robotics theory.

More than half of an octopus’ nerves are distributed through its eight arms, each of which has some degree of autonomy. This distributed sensing and information processing system intrigued Arbelaiz, who is researching how to design decentralized intelligence for human-made systems with embedded sensing and computation. At MIT, Arbelaiz is an applied math student who is working on the fundamentals of optimal distributed control and estimation in the final weeks before completing her PhD this fall.

Continue reading “Wiggling toward bio-inspired machine intelligence” »

Crucially, they showed that the synapses were capable of Hebbian learning, the process by which the strength of the connection between two neurons increases or decreases based on activity. This is key to the way information is encoded into the brain, with the strengths of connections between neurons controlling the function of different brain circuits.

In biological neurons this ability to alter the strength of connections—known as plasticity—operates at two distinct timescales. Over shorter timescales, regular firing of the neuron leads to a buildup of ions that temporarily increase the ease with which signals pass across. In the long term though, regular activity can cause new receptors to grow at a synapse, resulting in more durable increases in the strength of the connection.

With the artificial synapses, short-term plasticity operates in much the same way due to a buildup of ions. But boosting the connection strength in the long term relies on using voltage pulses to essentially grow new material out of a soup of chemical precursors at the synapse, which increases its conductivity.

There needs to be a radical change to biological wetware in order to handle viruses. What is needed is either nanoparticles or an immunity to all diseases. Crispr is the main path for the biological singularity but it needs to be perfected first as the human body is still a black box due to restrictions. I do believe that mass spectrometry will essentially be key to see the inner world of human biology. Then crispr can make new parts essentially to evolve past our current limits. But either way the biological singularity is needed for survival of human beings for better health.

The coronavirus revealed flaws in the nation’s pandemic plans. The spread of monkeypox shows that the problems remain deeply entrenched.

Such robotic schools could be tasked with locating and recording data on coral reefs to help researchers to study the reefs’ health over time. Just as living fish in a school might engage in different behaviours simultaneously — some mating, some caring for young, others finding food — but suddenly move as one when a predator approaches, robotic fish would have to perform individual tasks while communicating to each other when it’s time to do something different.

“The majority of what my lab really looks at is the coordination techniques — what kinds of algorithms have evolved in nature to make systems work well together?” she says.

Many roboticists are looking to biology for inspiration in robot design, particularly in the area of locomotion. Although big industrial robots in vehicle factories, for instance, remain anchored in place, other robots will be more useful if they can move through the world, performing different tasks and coordinating their behaviour.