Lifeboat Foundation: Safeguarding Humanity
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Category: mathematics

When the project started, a “Red Team” of hackers could have taken over the helicopter almost as easily as it could break into your home Wi-Fi. But in the intervening months, engineers from the Defense Advanced Research Projects Agency (DARPA) had implemented a new kind of security mechanism — a software system that couldn’t be commandeered. Key parts of Little Bird’s computer system were unhackable with existing technology, its code as trustworthy as a mathematical proof. Even though the Red Team was given six weeks with the drone and more access to its computing network than genuine bad actors could ever expect to attain, they failed to crack Little Bird’s defenses.

“They were not able to break out and disrupt the operation in any way,” said Kathleen Fisher, a professor of computer science at Tufts University and the founding program manager of the High-Assurance Cyber Military Systems (HACMS) project. “That result made all of DARPA stand up and say, oh my goodness, we can actually use this technology in systems we care about.”

The technology that repelled the hackers was a style of software programming known as formal verification. Unlike most computer code, which is written informally and evaluated based mainly on whether it works, formally verified software reads like a mathematical proof: Each statement follows logically from the next. An entire program can be tested with the same certainty that mathematicians prove theorems.

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If I had to pick my least favorite subject in high school, it would be physics.

The concepts themselves were challenging. The math was even more challenging.

However, my views on physics quickly changed when my teacher mentioned the words “quantum mechanics.”

He refused to discuss it, saying it was beyond the scope of our class. However, my curiosity was piqued.

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Researchers have developed a new technique to measure the density matrix—a more general way of characterizing the state of a quantum system than that provided by the wave function.

The wave function is the physicist’s usual choice to characterize the state of a quantum system. But a different mathematical object, called a density matrix, is required for systems that are in mixed states, which are a mixture of other, pure quantum states. An example of a pure state is a beam of horizontally or vertically polarized photons, whereas a mixed state would be an uncorrelated statistical mixture of both polarizations. A mixed state would also apply to a system quantum mechanically entangled with its environment. The density matrix provides a complete description of a mixed state, but it also applies to pure states. Usually, experimental measurements of density matrices are indirect reconstructions using data acquired from a series of different kinds of measurements.

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(Phys.org)—Are time crystals just a mathematical curiosity, or could they actually physically exist? Physicists have been debating this question since 2012, when Nobel laureate Frank Wilczek first proposed the idea of time crystals. He argued that these hypothetical objects can exhibit periodic motion, such as moving in a circular orbit, in their state of lowest energy, or their “ground state.” Theoretically, objects in their ground states don’t have enough energy to move at all.

In the years since, other physicists have proposed various arguments for why the physical existence of is impossible—and most physicists do seem to think that time crystals are physically impossible because of their odd properties. Even though time crystals couldn’t be used to generate useful energy (since disturbing them makes them stop moving), and don’t violate the second law of thermodynamics, they do violate a fundamental of the laws of physics.

However, now in a new paper published in Physical Review Letters, physicists from the University of California, Santa Barbara (UCSB) and Microsoft Station Q (a Microsoft research lab located on the UCSB campus) have demonstrated that it may be possible for time crystals to physically exist.

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Our friends at the Methuselah Foundation are working on macular degeneration.

Typically, a fellowship and participation in a research study to cure a major disease would occur years after completing undergrad, possibly even after earning a PhD. But Jennifer DeRosa is not a typical student.

As early as high school, DeRosa was already in the lab, conducting research in plant biotechnology at the College of Environmental Science and Forestry (SUNY-ESF) before graduating valedictorian from Skaneateles High School. As a freshman student at Onondaga Community College, she continued to develop skills in molecular biology, analytical chemistry, and cell biology. She logged over 1,600 hours in academic and industry laboratories while maintaining a perfect 4.0 GPA, completing her associate’s degree in Math and Science in only one year.

Although she had planned to continue to a bachelor’s program, DeRosa elected to defer enrollment after being offered a Methuselah Foundation research fellowship. “The fellowship provides distinguished students a year-long stipend to work in any laboratory of their choosing that conducts work on age-associated diseases,” said Methuselah Foundation CEO David Gobel. “We are very pleased that she chose to complete her fellowship at Ichor Therapeutics, where she has been working as a paid intern. Methuselah Foundation has a high degree of confidence in the quality and scope of work being conducted there.”

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New research published in the New Journal of Physics tries to decompose the structural layers of the cortical network to different hierarchies enabling to identify the network’s nucleus, from which our consciousness could emerge.

The is a very complex network, with approximately 100 billion neurons and 100 trillion synapses between the neurons. In order to cope with its enormous complexity and to understand how brain function eventually creates the conscious mind, science uses advanced mathematical tools. Ultimately, scientists want to understand how a global phenomenon such as consciousness can emerge from our neuronal network.

A team of physicists from Bar Ilan University in Israel led by Professor Shlomo Havlin and Professor Reuven Cohen used network theory in order to deal with this complexity and to determine how the structure of the human cortical network can support complex data integration and . The gray area of the human cortex, the neuron cell bodies, were scanned with MRI imaging and used to form 1000 in the cortical network. The white matter of the human cortex, the neuron bundles, were scanned with DTI imaging, forming 15,000 links or edges that connected the network’s nodes. In the end of this process, their network was an approximation of the structure of the human cortex.

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More insights on human conscientious in relation to its state after we die.

Personally, (this is only my own opinion) I believe much of the human conscientious will remain a mystery even in the living as it relates to the re-creation of the human brain and its thinking and decision making patterns on current technology. Namely because any doctor will tell you that a person’s own decisions (namely emotional decision making/ thinking) can be impacted by a whole multitude of factors beyond logical information such as the brain’s chemical balance, physical illness or even injury, etc. which inherently feeds into conscientious state. In order to try to replicate this model means predominantly development of a machine that is predominantly built with synthetic biology; and even then we will need to evolve this model to finally understand human conscientious more than we do today.

Sir Roger Penrose, a mathematical physicist at Oxford University, has asked “what right do we have to claim, as some might, that human beings are the only inhabitants of our planet blessed with an actual ability to be “aware”? It is hard to see how one could begin to develop a quantum-theoretical description of brain action when one might well have to regard the brain as “observing itself” all the time! Beneath all this technicality is the feeling that it is indeed “obvious” that the conscious mind cannot work like a computer, even though much of what is involved in mental activity might do so.

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My new Vice Motherboard story on the Fermi Paradox, Jethro’s Window, and why we’ll never discover intelligent aliens:

Here’s the sad solution to Fermi’s Paradox: We’ve never discovered other life forms because language and communication methods in the Singularity evolve so rapidly that even in one minute, an entire civilization can become transformed and totally unintelligible. In an expanding universe that is at least 13.6 billion years old, this transformation might never end. What this means is we will never have more than a few seconds to understand or even notice our millions of neighbors. The nature of the universe—the nature of communication in a universe where intelligence exponentially grows—is to keep us forever unaware and alone.

The only time we may discover other intelligent life forms is that 100 or so years during Jethro’s Window, and then it requires the miracle of another species in a similar evolutionary time table, right then, looking for us too. Given the universe is so gargantuan and many billions of years old, even with millions of alien species out there, we’ll never find them. We’ll never know them. It’s an unfortunate mathematical certainty.

Zoltan Istvan is a futurist, author of The Transhumanist Wager, and a 2016 US Presidential candidateof the Transhumanist Party. He writes an occasional columnfor Motherboard in which he ruminates on the future beyond human ability.

Topics: opinion, columns, fermi paradox, aliens, Extraterrestrial Life, Futures.

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I’m guessing you’d be like: :o.

So, here’s the deal. My biohacker friends led by Peter Fedichev and Sergey Filonov in collaboration with my old friend and the longevity record holder Robert Shmookler Reis published a very cool paper. They proposed a way to quantitatively describe the two types of aging – negligible senescence and normal aging. We all know that some animals just don’t care about time passing by. Their mortality doesn’t increase with age. Such negligibly senescent species include the notorious naked mole rat and a bunch of other critters like certain turtles and clams to name a few. So the paper explains what it is exactly that makes these animals age so slowly – it’s the stability of their gene networks.

What does network stability mean then? Well, it’s actually pretty straightforward – if the DNA repair mechanisms are very efficient and the connectivity of the network is low enough, then this network is stable. So, normally aging species, such as ourselves, have unstable networks. This is a major bummer by all means. But! There is a way to overcome this problem, according to the proposed math model.

The model very generally describes what happens with a gene network over time – the majority of the genes are actually working perfectly, but a small number doesn’t. There are repair mechanisms that take care of that. Also, there are mechanisms that take care of defected proteins like heat shock proteins, etc. Put together all of this in an equasion and solve it, and bam! here’s an equasion that gives you the Gompertz law for all species that have normal aging, and a time independent constant for the negligibly senescent ones.

What’s the difference between those two aging regimes? The model suggests it’s the right combination of DNA repair efficiency and the combined efficiency of proteolysis and heat shock response systems, mediating degradation and refolding of misfolded proteins. So, it’s not the accumulation of damages that is responsible for aging, but rather the properties of the gene network itself. The good news is that even we are playing with a terrible hand at first, there is a chance we can still win by changing the features of our network and making it stable. For example, by optimizing misfolded protein response or DNA repair.

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