“…The authors modified a well-used climate model for exoplanet research and applied it to the planet in Dune. The work was carried out in their spare time and is intended as an appropriate outreach piece to demonstrate how climate scientists use mathematical models to better understand our world and exoplanets…”
Looks like the Kingdom of Jordan to me. 😉
Is Dune scientifically plausible? We ran a climate model to find out.
Collaboration, transparency & urgency for rare disease research — mike graglia, managing director & co-founder, syngap research fund — SRF.
Mike Graglia is the Managing Director & Co-Founder of the SynGAP Research Fund (SRF — https://www.syngapresearchfund.org/), an organization that he set up in 2018 with his wife Ashley, after their son was diagnosed with a rare neurological disease caused by an insufficiency in SynGAP protein, which causes the life-changing diagnoses of Epilepsy, Autism, sleep disorder and intellectual disability.
Oh the things we can see and accomplish when time and death can no longer hinder us.
Immortality is eternal life, being exempt from death, unending existence. Human beings seem to be obsessed with the idea of immortality. But a study published in the journal Proceedings of the National Academy of Sciences has stated, through a mathematical equation, that it is impossible to stop ageing in multicellular organisms, which include humans, bringing the immortality debate to a possible end. So you probably don’t want to die, most people don’t. But death takes us all no matter what we want. However, today in our scenario, humans have found a way to obtain that immortality. Watch the whole timeline video to find out how reaching immortality changes the world and the way we live.
(2021). Nuclear Science and Engineering: Vol. 195 No. 9 pp. 977–989.
Earlier work has demonstrated the theoretical development of covert OT defenses and their application to representative control problems in a nuclear reactor. Given their ability to store information in the system nonobservable space using one-time-pad randomization techniques, the new C2 modeling paradigm6 has emerged allowing the system to build memory or self-awareness about its past and current state. The idea is to store information using randomized mathematical operators about one system subcomponent, e.g., the reactor core inlet and exit temperature, into the nonobservable space of another subcomponent, e.g., the water level in a steam generator, creating an incorruptible record of the system state. If the attackers attempt to falsify the sensor data in an attempt to send the system along an undesirable trajectory, they will have to learn all the inserted signatures across the various system subcomponents and the C2 embedding process.
We posit that this is extremely unlikely given the huge size of the nonobservable space for most complex systems, and the use of randomized techniques for signature insertion, rendering a level of security that matches the Vernam-Cipher gold standard. The Vernam Cipher, commonly known as a one-time pad, is a cipher that encrypts a message using a random key (pad) and can only be decrypted using this key. Its strength is derived from Shannon’s notion of perfect secrecy8 and requires the key to be truly random and nonreusable (one time). To demonstrate this, this paper will validate the implementation of C2 using sophisticated AI tools such as long short-term memory (LSTM) neural networks9 and the generative adversarial learning [generative adversarial networks (GANs)] framework,10 both using a supervised learning setting, i.e., by assuming that the AI training phase can distinguish between original data and the data containing the embedded signatures. While this is an unlikely scenario, it is assumed to demonstrate the resilience of the C2 signatures to discovery by AI techniques.
The AstroAccess initiative is working to advance disability inclusion in space.
Twelve disability ambassadors will fly weightlessly on Sunday (Oct. 17) as part of an initiative to advance disability inclusion in space.
AstroAccess, the latest mission from the SciAccess Initiative, which aims to make STEM (science, technology, engineering and mathematics) more accessible, will fly a crew of 12 disability ambassadors on a weightless parabolic flight. The flight will take off on Sunday from Long Beach, California, aboard Zero Gravity Corporation’s (Zero-G) “G-Force One” plane, which flies in a parabolic arc pattern that creates short periods of weightlessness in its cabin.
International diplomacy has traditionally relied on bargaining power, covert channels of communication, and personal chemistry between leaders. But a new era is upon us in which the dispassionate insights of AI algorithms and mathematical techniques such as game theory will play a growing role in deals struck between nations, according to the co-founder of the world’s first center for science in diplomacy.
Michael Ambühl, a professor of negotiation and conflict management and former chief Swiss-EU negotiator, said recent advances in AI and machine learning mean that these technologies now have a meaningful part to play in international diplomacy, including at the Cop26 summit starting later this month and in post-Brexit deals on trade and immigration.
The math is pretty basic. How many satellites are going to go up over the next decade? How many solar panels will they need? And how many are being manufactured that fit the bill? Turns out the answers are: a lot, a hell of a lot, and not nearly enough. That’s where Regher Solar aims to make its mark, by bringing the cost of space-quality solar panels down by 90% while making an order of magnitude more of them. It’s not exactly a modest goal, but fortunately the science and market seem to be in favor, giving the company something of a tailwind. The question is finding the right balance between cost and performance while remaining relatively easy to manufacture. Of course, if there was an easy answer there, someone would already be doing that.
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Microsoft’s blog post on Megatron-Turing says the algorithm is skilled at tasks like completion prediction, reading comprehension, commonsense reasoning, natural language inferences, and word sense disambiguation. But stay tuned—there will likely be more skills added to that list once the model starts being widely utilized.
GPT-3 turned out to have capabilities beyond what its creators anticipated, like writing code, doing math, translating between languages, and autocompleting images (oh, and writing a short film with a twist ending). This led some to speculate that GPT-3 might be the gateway to artificial general intelligence. But the algorithm’s variety of talents, while unexpected, still fell within the language domain (including programming languages), so that’s a bit of a stretch.
Despite the continued progress that the state of the art in machine learning and artificial intelligence (AI) has been able to achieve, one thing that still sets the human brain apart — and those of some other animals — is its ability to connect the dots and infer information that supports problem-solving in situations that are inherently uncertain. It does this remarkably well despite sparse, incomplete, and almost always less than perfect data. In contrast, machines have a very difficult time inferring new insights and generalizing beyond what they have been explicitly trained on or exposed to.
How the brain evolved to achieve these abilities and what are the underlying ‘algorithms’ that enable them to remain poorly understood. The development and investigation of mathematical models will lead to a deep understanding of what the brain is doing and how are not mature and remain a very active area of research.
Coastal artisanal fisheries, particularly those in developing countries, are facing a global crisis of overexploitation1. Artificial reefs (ARs), or human–made reefs2, have been widely advocated by governmental and non-governmental conservation and management organizations for addressing these issues. Industries, particularly oil and gas, seeking to avoid the costs of removal or conventional disposal of used materials are often major advocates for deploying ARs. Yet, major questions remain regarding the success of such efforts in the context of weak governance and poorly sustained international investment in AR development projects. There is frequently confusion over whether or not ARs should be fishing sites and the precise goals of constructing such ARs are often unclear, making difficult to evaluate their successfulness3. Over the last 40 years, both failures and success AR implementation programs have been reported4,5. The main point of the present work is to underline the importance of the governance issue and address social and management factors on AR “success”.
To improve fishery yields, it has been recommended that ARs must be no-take areas (e.g.,2). Yet, most ARs were historically delineated as sites for fishing4, and were rarely implemented at large scales in/for no-take zones, even in countries with centuries of experience in constructing ARs, such as Japan. In Japan, fishery authorities and local fishers use ARs to promote sustainable catches and to establish nursery grounds of target species6. However, fishery authorities and local fishery cooperatives in Japan have extensive management authority over ARs. For example, fishing around ARs is usually limited to hook and line techniques, with net fishing rarely being permitted in areas where risk of entanglement in ARs is high. Furthermore, during spawning, fishing gear and fishing season are often restricted around ARs in Japan. These practices are recognized for their effectiveness in maintaining good fishing performance and marine conservation in Japan and elsewhere where they have been implemented7.
