Lifeboat Foundation

Launched in 2010, DARPA’s Living Foundries program aimed to enable adaptable, scalable, and on-demand production of critical, high-value molecules by programming the fundamental metabolic processes of biological systems to generate a vast number of complex molecules. These molecules were often prohibitively expensive, unable to be domestically sourced, and/or impossible to manufacture using traditional synthetic chemistry approaches. As a proof of concept, DARPA intended to produce 1,000 molecules and material precursors spanning a wide range of defense-relevant applications including industrial chemicals, fuels, coatings, and adhesives.

Divided into two parts – Advanced Tools and Capabilities for Generalizable Platforms (ATCG) and 1,000 Molecules – the Living Foundries program succeeded not only in meeting its programmatic goals of producing 1,000 molecules as a proof-of-concept, but pivoted in 2019 to expand program objectives to working with military mission partners to test molecules for military applications. The performer teams collectively have produced over 1,630 molecules and materials to-date, and more importantly, DARPA is transitioning a subset of these technologies to five military research teams from Army, Navy, and Air Force labs who partnered with the agency on testing and evaluation over the course of the program.

“Biologically-produced molecules offer orders-of-magnitude greater diversity in chemical functionality compared to traditional approaches, enabling scientists to produce new bioreachable molecules faster than ever before,” noted Dr. Anne Cheever, Living Foundries program manager. “Through Living Foundries, DARPA has transformed synthetic biomanufacturing into a predictable engineering practice supportive of a broad range of national security objectives.”

The Neuro-Network.

𝐏𝐬𝐲𝐜𝐡𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐑𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐜𝐞 𝐈𝐬 𝐋𝐢𝐧𝐤𝐞𝐝 𝐭𝐨 𝐇𝐨𝐰 𝐌𝐮𝐜𝐡 𝐒𝐭𝐫𝐞𝐬𝐬 𝐌𝐞𝐬𝐬𝐞𝐬 𝐖𝐢𝐭𝐡 𝐘𝐨𝐮𝐫 𝐁𝐨𝐝𝐲

𝙄 𝙥𝙧𝙤𝙗𝙖𝙗𝙡𝙮 𝙙𝙤𝙣’𝙩 𝙣𝙚𝙚𝙙 𝙩𝙤 𝙨𝙖𝙮 𝙞𝙩, 𝙗𝙪𝙩 𝙬𝙚 𝙨𝙝𝙤𝙪𝙡𝙙 𝙥𝙧𝙤𝙗𝙖𝙗𝙡𝙮 𝙖𝙡𝙡 𝙗𝙚 𝙩𝙧𝙮𝙞𝙣𝙜 𝙩𝙤 𝙗𝙚 𝙡𝙚𝙨𝙨 𝙨𝙩𝙧… See more.

Continue reading “Psychological Resilience Is Linked to How Much Stress Messes With Your Body” »

Working with two teams of mathematicians, DeepMind engineered an algorithm that can look across different mathematical fields and spot connections that previously escaped the human mind. The AI doesn’t do all the work—when fed sufficient data, it finds patterns. These patterns are then passed on to human mathematicians to guide their intuition and creativity towards new laws of nature.

“I was not expecting to have some of my preconceptions turned on their head,” said Dr. Marc Lackenby at the University of Oxford, one of the scientists collaborating with DeepMind, to Nature, where the study was published.

The AI comes just a few months after DeepMind’s previous triumph in solving a 50-year-old challenge in biology. This is different. For the first time, machine learning is aiming at the core of mathematics—a science for spotting patterns that eventually leads to formally-proven ideas, or theorems, about how our world works. It also emphasized collaboration between machine and man in bridging observations to working theorems.

I think his purpose in doing this is to prioritize full self driving over partial self driving features.

“Humans drive with eyes and biological neural nets,” Musk said in October. “So [it] makes sense that cameras and silicon neural nets are [the] only way to achieve generalized solution to self-driving.”

Moreover, he’s reportedly implementing that philosophy at Tesla.

Continue reading “Elon Musk reportedly demanded cameras over radar in self-driving cars because human eyes don’t rely on radar” »

A scientist who loves to write, can do it well, and can share the excitement of the scientific pursuit is incredibly rare. Kevin Peter Hand 0, Deputy Project Scientist, Europa and Director of the JPL Ocean Worlds Lab is that rare person who can do all these things. In his incredible book Alien Oceans: The Search for Life in the Depths of Space 0, he explains that “We know that the laws of physics, the principles of chemistry, and the principles of geology all work beyond Earth. We’ve explored other worlds and observed that these sciences are universal. When it comes to biology, however, we have yet to make that leap.”

If you want to learn about how the intersection of numerous areas of science are helping inform our understanding of the oceans, space, and ourselves, Alien Oceans is by far one of the most clearly written books on the topic. As Kevin notes, he wrote the book he wishes he could have read in college. Kevin will teach you and inspire you and explain complicated scientific topics in ways nearly anyone can understand. Not only is it a book about his areas of expertise, it is also a wonderful window into the way scientists and engineers think about solving real world problems and applying basic knowledge. For example, Kevin notes in this interview that “Making measurements is where the creativity of science meets the hard reality of engineering.” I read a lot of books on science written for a broad audience, and this book, by far is among the very best I have ever read. More than anything else what came through in Kevin’s writing is excitement about finding out what is true.

What inspired you to write this book?

We can add suggesting and proving mathematical theorems to the long list of what artificial intelligence is capable of: Mathematicians and AI experts have teamed up to demonstrate how machine learning can open up new avenues to explore in the field.

While mathematicians have been using computers to discover patterns for decades, the increasing power of machine learning means that these networks can work through huge swathes of data and identify patterns that haven’t been spotted before.

In a newly published study, a research team used artificial intelligence systems developed by DeepMind, the same company that has been deploying AI to solve tricky biology problems and improve the accuracy of weather forecasts, to unknot some long-standing math problems.

Two Allen Discovery Centers enter their next phase of discovery, poised to address large questions about biology.

Jon Kaas, Gertrude Conaway Vanderbilt Chair in Social and Natural Sciences, Distinguished Centennial Professor of Psychology and associate professor of cell and developmental biology, received the Ralph W. Gerard Prize in Neuroscience, the highest recognition from the Society for Neuroscience, for his pathbreaking work in illuminating the structure and function of the cerebral cortex and plasticity in the developing and adult brain.

Through mapping the cerebral cortex in 30 mammalian species over his career, Kaas has shown the functional and structural organization of the visual and somatosensory—that is, sensations that span the body, such as warmth—systems in detail. Through detailed pictorial construction and electrophysical mapping, Kaas reversed a scientific dogma that brain plasticity only occurs in early life. This has led to new approaches to rehabilitation from brain damage after stroke, from macular degeneration or from motor system disorders and injuries.

“I’m pleased to share this award with Bob Desimone who has done such wonderful research, and who we once tried to convince to move to Vanderbilt,” Kaas said. “From my first days at Vanderbilt, I have worked with outstanding graduate students, undergraduates and postdocs, who made everything possible. The support of members of my Department and other faculty at Vanderbilt has been especially important.”

Light is an electromagnetic wave: It consists of oscillating electric and magnetic fields propagating through space. Every wave is characterized by its frequency, which refers to the number of oscillations per second, measured in Hertz (Hz). Our eyes can detect frequencies between 400 and 750 trillion Hz (or terahertz, THz), which define the visible spectrum. Light sensors in cell phone cameras can detect frequencies down to 300 THz, while detectors used for internet connections through optical fibers are sensitive to around 200 THz.

At lower frequencies, the energy transported by light isn’t enough to trigger photoreceptors in our eyes and in many other sensors, which is a problem given that there is rich information available at frequencies below 100 THz, the mid-and far–infrared spectrum. For example, a body with surface temperature of 20°C emits infrared light up to 10 THz, which can be “seen” with thermal imaging. Also, chemical and biological substances feature distinct absorption bands in the mid-infrared, meaning that we can identify them remotely and non-destructively by infrared spectroscopy, which has myriads of applications.