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We explore Artificial Intelligence (AI) through Neuromorphic Computing with computer chips that emulate the biological neurons and synapses in the brain. Neuro-biological chip architectures enable machines to solve very different kinds of problems than traditional computers, the kinds of problems we previously thought only humans could tackle.

Our guest today is Kelsey Scharnhorst. Kelsey is an Artificial Neural Network Researcher at UCLA. Her research lab (Gimzewski Lab under James Gimzewski) is focused on creating neuromorphic computer chips and further developing their capabilities.

We’ll talk with Kelsey about how neuromorphic computing is different, how neural-biological computer architecture works, and how it will be used in the future.

Podcast version at: https://is.gd/MM_on_iTunes.

If you own any piece of jewelry with a ruby, you’re probably never going to look at it the same way again.

Forget those perfect gemstones you see glittering in store displays. What scientists are looking for are the flawed ones — the ones that contain inclusions which can whisper the secrets of Earth’s distant past, like that tardigrade trapped in amber. When researcher Chris Yakymchuk and his team unearthed a peculiar ruby in Greenland, the inclusion they found was what remained of life that was over 2.5 billion years old.

What was inside the ruby sounds common enough. Graphite is the same material pencils write with, but it is also a pure form of carbon that Yakymchuk determined to be all that was left of prehistoric microbes, possibly the same cyanobacteria (blue-green algae) that first released oxygen into Earth’s atmosphere through photosynthesis. He led a study recently published in Ore Geology Reviews.

Uncovering the mechanisms of learning via synaptic plasticity is a critical step towards understanding how our brains function and building truly intelligent, adaptive machines. Researchers from the University of Bern propose a new approach in which algorithms mimic biological evolution and learn efficiently through creative evolution.

Our brains are incredibly adaptive. Every day, we form , acquire new knowledge, or refine existing skills. This stands in marked contrast to our current computers, which typically only perform pre-programmed actions. At the core of our adaptability lies . Synapses are the connection points between neurons, which can change in different ways depending on how they are used. This synaptic plasticity is an important research topic in neuroscience, as it is central to learning processes and memory. To better understand these processes and build adaptive machines, researchers in the fields of neuroscience and (AI) are creating models for the mechanisms underlying these processes. Such models for learning and plasticity help to understand biological information processing and should also enable machines to learn faster.

Princeton researchers have invented bubble casting, a new way to make soft robots using “fancy balloons” that change shape in predictable ways when inflated with air.

The new system involves injecting bubbles into a liquid polymer, letting the material solidify and inflating the resulting device to make it bend and move. The researchers used this approach to design and create hands that grip, a fishtail that flaps and slinky-like coils that retrieve a ball. They hope that their simple and versatile method, published Nov. 10 in the journal Nature, will accelerate the development of new types of soft robots.

Traditional rigid robots have multiple uses, such as in manufacturing cars. “But they will not be able to hold your hands and allow you to move somewhere without breaking your wrist,” said Pierre-Thomas Brun, an assistant professor of chemical and and the lead researcher on the study. “They’re not naturally geared to interact with the soft stuff, like humans or tomatoes.”

A new analytical technique is able to provide hitherto unattainable insights into the extremely rapid dynamics of biomolecules. The team of developers, led by Abbas Ourmazd from the University of Wisconsin–Milwaukee and Robin Santra from DESY

Commonly abbreviated as DESY, the Deutsches Elektronen-Synchrotron (English German Electron Synchrotron) is a national research center in Germany that operates particle accelerators used to investigate the structure of matter. It is a member of the Helmholtz Association and operates at sites in Hamburg and Zeuthen.

Consider the room you are sitting in: From the injection-molded plastic of a computer mouse to the synthetic carpet fibers on the floor, you are surrounded by petroleum-derived products in your daily life. But what if there is a better way to produce the products we depend on with cleaner and greener materials? Biomanufacturing offers a way to use materials from nature to create the items we use every day.

Checkerspot, a materials innovation company, is rethinking products from a molecular level. It is optimizing microbes to biomanufacture unique structural oils found in nature. The company has taken the technology it has built and turned it into a platform to bring us closer to a post-petroleum future.

Dr. Yuval Noah Harari, macro-historian, Professor, best-selling author of “Sapiens” and “Homo Deus,” and one of the world’s most innovative and exciting thinkers, has a few hypotheses of his own on the future of humanity.

He examines what might happen to the world when old myths are coupled with new godlike technologies, such as artificial intelligence and genetic engineering.

Harari tackles into today’s most urgent issues as we move into the uncharted territory of the future.

According to Harari, we are probably one of the last generation of homo sapiens. Within a century earth will be dominated from entities that are not even human, intelligent species that are barely biological. Harari suggests the possibility that humans are algorithms, and as such Homo sapiens may not be dominant in a universe where big data becomes a paradigm.