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I wonder how many iterations of “kinematic reproduction” would result in sentience.

Artificial Intelligence has made a landmark achievement by creating robots that can reproduce. US scientists who created the first living robots claim they can now reproduce on their own. Scientists now claim the discovery is a new form of biological reproduction that was not known to science yet. Experts say the parent robot and its babies, called Xenobots, are entirely biological.

#Xenobots. #LivingRobots. #ArtificialIntelligence.

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Clip during an interview made by Nicholas Singh, Senior Product Manager at Novos Labs to Kris Verburgh, CSO and Co-Founder of Novos Lab.

The clip shows the answer made by Kris Verburgh to a question made by José Cordeiro, PhD, MBA, Vice-Chairman of Humanity Plus, about the prediction made by Ray Kurzweil on the availability of full body human biological rejuvenation by 2045.

The episode took place during the webinar “Why Do We Age (And What Can We Do About It)?” organized by Novos Labs that took place on December 9, 2021.

To watch the entire webinar clic here:

According to a news release by The University of Manchester, a groundbreaking study published in the journal Scientific Reports provides new evidence that helps us to understand the asteroid impact that brought an end to 75 percent of life on Earth, including non-avian dinosaurs, at the Cretaceous-Paleogene transition 66 million years ago.

This project has been a huge undertaking but well worth it. For so many years we’ve collected and processed the data, and now we have compelling evidence that changes how we think of the KPg event, but can simultaneously help us better prepare for future ecological and environmental hazards.

Time of year plays an important role in many biological functions— reproduction, available food sources, feeding strategies, host-parasite interactions, seasonal dormancy, breeding patterns, to name a few. It is hence no surprise that the time of year for a global-scale disaster can play a big role in how harshly it impacts life. The seasonal timing of the Chicxulub impact has therefore been a critical question for the story of the end-Cretaceous extinction. Until now the answer to that question has remained unclear.

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.

I probably don’t need to say it, but we should probably all be trying to be less stressed.

Short term, stress can sometimes be helpful – it can help you motivate yourself. But when the stress continues long term, the health effects start to stack up, and studies have shown that this could even age you faster.

Now a new study has looked at people’s biological and psychological ‘resilience’, and found that this resilience is linked to less stress-related negative effects.

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.

Musk has repeatedly instructed the company’s Autopilot team, which works on self-driving car tech, to ditch radar and use only cameras instead, the New York Times reported on Monday.

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.