Lifeboat Foundation

The show provides a glimpse into humanity’s astonishing diversity. Social scientists have a similar goal—understanding the behavior of different people, groups, and cultures—but use a variety of methods in controlled situations. For both, the stars of these pursuits are the subjects: humans.

But what if you replaced humans with AI chatbots?

The idea sounds preposterous. Yet thanks to the advent of ChatGPT and other large language models (LLMs), social scientists are flirting with the idea of using these tools to rapidly construct diverse groups of “simulated humans” and run experiments to probe their behavior and values as a proxy to their biological counterparts.

Dr. Michael Roberts, Ph.D. is Chief Science Officer of the International Space Station National Laboratory (https://www.issnationallab.org/), and Vice President at the Center for the Advancement of Science in Space (CASIS — https://www.issnationallab.org/about/center-for-the-advancem…dership/), which as manager of the ISS National Laboratory in partnership with NASA, is responsible to the nation for enabling access to the International Space Station for research, technology development, STEM education, and commercial innovation in space as a public service to foster a scalable and sustainable low Earth orbit economy.

Before joining CASIS in 2013, Dr. Roberts worked as a microbial ecologist, principal investigator, and research group lead in the NASA Advanced Life Support program at the Kennedy Space Center.

Continue reading “Dr. Michael Roberts, Ph.D. — Chief Science Officer, International Space Station National Laboratory” »

“The new research program, led by Associate Professor Adeel Razi, from the Turner Institute for Brain and Mental Health, in collaboration with Melbourne start-up Cortical Labs, involves growing around 800,000 brain cells living in a dish, which are then “taught” to perform goal-directed tasks. Last year the brain cells’ ability to perform a simple tennis-like computer game, Pong, received global attention for the team’s research.”

Monash University-led research into growing human brain cells onto silicon chips, with new continual learning capabilities to transform machine learning, has been awarded almost $600,000 AUD in the prestigious National Intelligence and Security Discovery Research Grants Program.

According to Associate Professor Razi, the research program’s work using lab-grown brain cells embedded onto silicon chips, “merges the fields of artificial intelligence and synthetic biology to create programmable biological computing platforms,” he said.

Continue reading “Research to merge human brain cells with AI secures national defence funding” »

A team of researchers just got a $600,000 grant from Australia’s Office of National Intelligence to study ways of merging human brain cells with artificial intelligence.

In collaboration with Melbourne-based startup Cortical Labs, the team has already successfully demonstrated how a cluster of roughly 800,000 brain cells in a Petri dish is capable of playing a game of “Pong.”

The basic idea is to merge biology with AI, something that could forge new frontiers for machine learning tech for self-driving cars, autonomous drones, or delivery robots — or at least that’s what the government is hoping to accomplish with its investment.

Scientists specializing in chemical and environmental engineering at the University of California, Riverside have discovered two types of bacteria in the soil capable of breaking down a class of stubborn “forever chemicals,” giving hope for low-cost biological cleanup of industrial pollutants.

Assistant Professor Yujie Men and her team at the Bourns College of Engineering have found that these bacteria are able to eradicate a specific subgroup of per-and poly-fluoroalkyl substances, known as PFAS, particularly those that contain one or more chlorine atoms within their chemical structure. Their findings were published in the scientific journal, Nature Water.

Unhealthful forever chemicals persist in the environment for decades or much longer because of their unusually strong carbon-to-fluorine bonds. Remarkably, the UCR team found that the bacteria cleave the pollutant’s chlorine-carbon bonds, which starts a chain of reactions that destroy the forever chemical structures, rendering them harmless.

I gotta admit although effective and innovative, it’s also kinda creepy.

Last year, Monash University scientists created the “DishBrain” – a semi-biological computer chip with some 800,000 human and mouse brain cells lab-grown into its electrodes. Demonstrating something like sentience, it learned to play Pong within five minutes.

The micro-electrode array at the heart of the DishBrain was capable both of reading activity in the brain cells, and stimulating them with electrical signals, so the research team set up a version of Pong where the brain cells were fed a moving electrical stimulus to represent which side of the “screen” the ball was on, and how far away from the paddle it was. They allowed the brain cells to act on the paddle, moving it left and right.

Continue reading “Computer chip with built-in human brain tissue gets military funding” »

Over the past decade, teams of engineers, chemists and biologists have analyzed the physical and chemical properties of cicada wings, hoping to unlock the secret of their ability to kill microbes on contact. If this function of nature can be replicated by science, it may lead to development of new products with inherently antibacterial surfaces that are more effective than current chemical treatments.

When researchers at Stony Brook University’s Department of Materials Science and Chemical Engineering developed a simple technique to duplicate the cicada wing’s nanostructure, they were still missing a key piece of information: How do the nanopillars on its surface actually eliminate bacteria? Thankfully, they knew exactly who could help them find the answer: Jan-Michael Carrillo, a researcher with the Center for Nanophase Materials Sciences at the Department of Energy’s Oak Ridge National Laboratory.

For nanoscience researchers who seek computational comparisons and insights for their experiments, Carrillo provides a singular service: large-scale, high-resolution molecular dynamics (MD) simulations on the Summit supercomputer at the Oak Ridge Leadership Computing Facility at ORNL.

In it, he explores how we can make better, scientifically informed predictions about the world around us, using maths. “Mathematics can provide us with the objective tools to bypass the foibles of our own biology – the limitations imposed by our own thought processes, the compulsions that ultimately make us human, but let us down when it comes to making inferences about the world around us,” he writes. “They are humanity’s shortcuts: the preconceptions and cognitive biases, refined over millennia of evolution, that all too often lead us astray when we try to apply our brain’s old rules to our society’s new environments.”

No matter how tempting it is to think, “Ooh, that’s a bit spooky” when faced with a completely random coincidence or chance occurrence, we should all be expecting unusual things to happen all the time, he says.

Yates describes a person who, when browsing in a secondhand bookshop far from where they grew up, opens a copy of their favourite children’s book, only to find their own name inscribed inside. Yet, he says, “the law of truly large numbers” dictates that, just as someone wins the lottery almost every week, with enough opportunities, such extraordinary coincidences are far more likely to happen than you might think. “There are so many different types of coincidences that make us say: ‘Well, that’s extraordinary.’ But it’s not unlikely that some of them happen to us every so often.”

An international group of experts argue that tackling the long-standing challenge of decoding the communication systems of whales, crows, bats, and other animals is coming within reach, following breath-taking advances in artificial intelligence (AI) research.

In an article published in Science, led by Professor Christian Rutz from the School of Biology at the University of St Andrews, the authors explain how cutting-edge machine-learning tools could provide transformative insights into the hidden lives of animals, with important implications for their conservation.

The prospect of understanding what animals say to each other, or of even initiating a conversation with another species, has fired humans’ imagination for millennia. But since there is no Rosetta Stone for translating animals’ communication signals, their meaning must be deciphered through careful observation and experimentation. Despite good research progress over the past few decades, collecting and analyzing data is a challenging task. For example, annotating recordings of bird calls, whale songs or primate gestures is time-consuming, and even experienced biologists often struggle to differentiate seemingly similar signal types.