Lifeboat Foundation

While our choices and beliefs don’t often make sense or fit a pattern on a macro level, at a “quantum” level, they can be predicted with surprising accuracy.

The irrationality of how we think has long plagued psychology. When someone asks us how we are, we usually respond with “fine” or “good.” But if someone followed up about a specific event — “How did you feel about the big meeting with your boss today?” — suddenly, we refine our “good” or “fine” responses on a spectrum from awful to excellent.

In less than a few sentences, we can contradict ourselves: We’re “good” but feel awful about how the meeting went. How then could we be “good” overall? Bias, experience, knowledge, and context all consciously and unconsciously form a confluence that drives every decision we make and emotion we express. Human behavior is not easy to anticipate, and probability theory often fails in its predictions of it.

Continue reading “Your Brain Isn’t a Computer — It’s a Quantum Field” »

A team of neuroscientists and engineers has developed a tiny, implantable device that has potential to help people with bladder problems bypass the need for medication or electronic stimulators.

The team — from Washington University School of Medicine in St. Louis, the University of Illinois at Urbana-Champaign, and the Feinberg School of Medicine at Northwestern University in Chicago — created a soft, implantable device that can detect overactivity in the bladder and then use light from tiny, biointegrated LEDs to tamp down the urge to urinate.

The device works in laboratory rats and one day may help people who suffer incontinence or frequently feel the need to urinate.

Continue reading “Tiny, implantable device uses light to treat bladder problems” »

An array of cubesats will create brand-sponsored new constellations.

Should brands fill the night sky with corporate logos?

Zero Mass Water produces solar panels that pull water out of the air, filter it, and deliver it to your home faucet.

Rapid comprehension of world events is critical to informing national security efforts. These noteworthy changes in the natural world or human society can create significant impact on their own, or may form part of a causal chain that produces broader impact. Many events are not simple occurrences but complex phenomena composed of a web of numerous subsidiary elements – from actors to timelines. The growing volume of unstructured, multimedia information available, however, hampers uncovering and understanding these events and their underlying elements.

“The process of uncovering relevant connections across mountains of information and the static elements that they underlie requires temporal information and event patterns, which can be difficult to capture at scale with currently available tools and systems,” said Dr. Boyan Onyshkevych, a program manager in DARPA’s Information Innovation Office (I2O).

The use of schemas to help draw correlations across information isn’t a new concept. First defined by cognitive scientist Jean Piaget in 1923, schemas are units of knowledge that humans reference to make sense of events by organizing them into commonly occurring narrative structures. For example, a trip to the grocery store typically involves a purchase transaction schema, which is defined by a set of actions (payment), roles (buyer, seller), and temporal constraints (items are scanned and then payment is exchanged).

The ban could go into effect as soon as 2021.

That most famous characterization of the complexity causality, a butterfly beating its wings and causing a hurricane on the other side of the world, is thought-provoking but ultimately not helpful. What we really need is to look at a hurricane and figure out which butterfly caused it — or perhaps stop it before it takes flight in the first place. DARPA thinks AI should be able to do just that.

A new program at the research agency is aimed at creating a machine learning system that can sift through the innumerable events and pieces of media generated every day and identify any threads of connection or narrative in them. It’s called KAIROS: Knowledge-directed Artificial Intelligence Reasoning Over Schemas.

“Schema” in this case has a very specific meaning. It’s the idea of a basic process humans use to understand the world around them by creating little stories of interlinked events. For instance when you buy something at a store, you know that you generally walk into the store, select an item, bring it to the cashier, who scans it, then you pay in some way, and then leave the store. This “buying something” process is a schema we all recognize, and could of course have schemas within it (selecting a product; payment process) or be part of another schema (gift giving; home cooking).

Continue reading “DARPA wants to build an AI to find the patterns hidden in global chaos” »

FRIB) will be a scientific user facility for the Office of Nuclear Physics in the U.S. Department of Energy Office of Science (DOE-SC). FRIB is funded by the DOE-SC, MSU and the State of Michigan. Supporting the mission of the Office of Nuclear Physics in DOE-SC, FRIB will enable scientists to make discoveries about the properties of rare isotopes (that is, short-lived nuclei not normally found on Earth), nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

This video — The Facility for Rare Isotope Beams at MSU — explains the history of FRIB, its role in research and education, and its future in rare-isotope discoveries. It includes an animated sequence to help viewers understand what FRIB is about.

Employment opportunities: FRIB is looking for engineers, physicists, and other talented professionals to build the world’s leading rare isotope facility.

When radiochemist Jennifer Shusterman and her colleagues got the first results of their experiment, no one expected what they saw: Atoms of a weird version of the element #zirconium had enthusiastically absorbed neutrons.

Zirconium-88 captures neutrons with extreme efficiency, and scientists don’t yet know why.