Lifeboat Foundation

The sophistication of autonomous systems currently being developed across various domains and industries has markedly increased in recent years, due in large part to advances in computing, modeling, sensing, and other technologies. While much of the technology that has enabled this technical revolution has moved forward expeditiously, formal safety assurances for these systems still lag behind. This is largely due to their reliance on data-driven machine learning (ML) technologies, which are inherently unpredictable and lack the necessary mathematical framework to provide guarantees on correctness. Without assurances, trust in any learning enabled cyber physical system’s (LE-CPS’s) safety and correct operation is limited, impeding their broad deployment and adoption for critical defense situations or capabilities.

To address this challenge, DARPA’s Assured Autonomy program is working to provide continual assurance of an LE-CPS’s safety and functional correctness, both at the time of its design and while operational. The program is developing mathematically verifiable approaches and tools that can be applied to different types and applications of data-driven ML algorithms in these systems to enhance their autonomy and assure they are achieving an acceptable level of safety. To help ground the research objectives, the program is prioritizing challenge problems in the defense-relevant autonomous vehicle space, specifically related to air, land, and underwater platforms.

The first phase of the Assured Autonomy program recently concluded. To assess the technologies in development, research teams integrated them into a small number of autonomous demonstration systems and evaluated each against various defense-relevant challenges. After 18 months of research and development on the assurance methods, tools, and learning enabled capabilities (LECs), the program is exhibiting early signs of progress.

BF16, the new number format optimized for deep learning, promises power and compute savings with a minimal reduction in prediction accuracy.

BF16, sometimes called BFloat16 or Brain Float 16, is a new number format optimised for AI/deep learning applications. Invented at Google Brain, it has gained wide adoption in AI accelerators from Google, Intel, Arm and many others.

The idea behind BF16 is to reduce the compute power and energy consumption needed to multiply tensors together by reducing the precision of the numbers. A tensor is a three-dimensional matrix of numbers; multiplication of tensors is the key mathematical operation required for AI calculations.

O.o.

New research has exploded the space of problems that quantum computers can efficiently verify, simultaneously knocking down milestone problems in quantum physics and math.

Circa 2017

The Middle Ages certainly were far from being science-friendly: Whoever looked for new findings off the beaten track faced the threat of being burned at the stake. Hence, the contribution of this era to technical progress is deemed to be rather small. Scientists of Karlsruhe Institute of Technology (KIT), however, were inspired by medieval mail armor when producing a new metamaterial with novel properties. They succeeded in reversing the Hall coefficient of a material.

The Hall effect is the occurrence of a transverse electric voltage across an electric conductor passed by current flow, if this conductor is located in a magnetic field. This effect is a basic phenomenon of physics and allows to measure the strength of magnetic fields. It is the basis of magnetic speed sensors in cars or compasses in smartphones. Apart from measuring magnetic fields, the Hall effect can also be used to characterize metals and semiconductors and in particular to determine charge carrier density of the material. The sign of the measured Hall voltage allows conclusions to be drawn as to whether charge carriers in the semiconductor element carry positive or negative charge.

Continue reading “Metamaterial: Mail armor inspires physicists” »

O.o!

A mind-expanding and funny trip to the edge of mathematics

How big is the universe? How many numbers are there? And is infinity + 1 is the same as 1 + infinity? Such questions occur to young children and our greatest minds. And they are all the same question: What is infinity? In Beyond Infinity, Eugenia Cheng takes us on a staggering journey from elemental math to its loftiest abstractions. Along the way, she considers how to use a chessboard to plan a worldwide dinner party, how to make a chicken-sandwich sandwich, and how to create infinite cookies from a finite ball of dough. Beyond Infinity shows how one little symbol holds the biggest idea of all.

Continue reading “Beyond Infinity: An Expedition to the Outer Limits of Mathematics” »

#survival #coronavirus
In light of recent events its a good opportunity to go over the basics of pandemic preparedness.

*Correction* I need to make a correction to information provided within this video. The case-fatality rate of the Spanish influenza is often quoted by virologists as 2.5 % when in reality the math on this doesn’t add up as the population of the planet at the time doesn’t align with this statistic. This stat is misinterpreted to mean the overall case-fatality rate was (greater than) 2.5%. It is presumed a safer mortality estimate was between 7.5%-15% at the pandemics peak wave. The correct statistic is the 2.5%-5% of the WORLDS population perished as a result of this. It should be noted that there were several waves to this pandemic hence the 2.5 (greater than) statistic. The first wave was relatively tame, the second wave was devastating, the third wave was less severe. https://www.cdc.gov/flu/pandemic-resources/1918-commemoration/three-waves.htm

Continue reading “10 Steps to Survive a Global Pandemic: Coronavirus” »

The YangDAO was created specifically to allow the Yang Gang community to coordinate and fund projects that we decide are in our shared interest, whether that’s a Federal Meme Reserve 🏛, Freedom Dividend pilots 💰, or that new MATH blockbuster movie 🎬.

Complex cognitive dissonance disorder guaranteed. 😬.

Garrett Lisi, the so called “Surf Bum with a Theory of Everything (or T.O.E.)”, is a PhD theoretical physicist who has refused to be captured by the theoretical physics community. By making shrewd investments, he has avoided holding meaningful employment for his entire adult life. Instead, he lives in Maui and travels the world chasing the perfect wave.

Continue reading “Garrett Lisi on ‘The Portal’, Ep. #015 — My Arch-nemesis, Myself. (with host Eric Weinstein)” »

A team of researchers, two with the French Atomic Energy Commission (AEC) and a third with the Soleil synchrotron, have found evidence of a phase change for hydrogen at a pressure of 425 gigapascals. In their paper published in the journal Nature, Paul Loubeyre, Florent Occelli and Paul Dumas describe testing hydrogen at such a high pressure and what they learned from it.

Researchers long ago theorized that if hydrogen gas were exposed to enough pressure, it would transition into a metal. But the theories were not able to derive how much pressure is required. Doubts about the theories began to arise when scientists developed tools capable of exerting the high pressures that were believed necessary to squeeze hydrogen into a metal. Theorists simply moved the number higher.

In the past several years, however, theorists have come to a consensus—their math showed that hydrogen should transition at approximately 425 gigapascals—but a way to generate that much pressure did not exist. Then, last year, a team at the AEC improved on the diamond anvil cell, which for years has been used to create intense pressure in experiments. In a diamond anvil cell, two opposing diamonds are used to compress a sample between highly polished tips—the pressure generated is typically measured using a reference material. With the new design, called a toroidal diamond anvil cell, the tip was made into a donut shape with a grooved dome. When in use, the dome deforms but does not break at high pressures. With the new design, the researchers were able to exert pressures up to 600 GPa. That still left the problem of how to test a sample of hydrogen as it was being squeezed.