Comets that have hit Earth have been a mixed bag. Early in Earth’s history, during the solar system’s chaotic beginning, they were likely the source of our planet’s water, ultimately making up about 0.02% of the planet’s mass. (Mars and Venus received a similar fraction.)
Comets brought complex organic molecules and the biosphere, but later posed a threat to the same in cometary collisions. A comet (or asteroid) likely caused the Tunguska Event in 1908 in Russia, and a comet fragment likely triggered the rapid climate shift of the Younger Dryas 12,800 years ago, with its widespread extinctions.
If such collisions happen here, they likely take place in other solar systems as well. Now three scientists in the United Kingdom have modeled the impacts of an icy cometary collision with an Earth-like, tidally locked terrestrial planet. Such objects are prime candidates in the search for habitable exoplanets outside our solar system.
Schavemaker and Lynch derived functions that relate the cell biology of endomembranes to cellular fitness. Applied to the pinocytosis of small-molecule nutrients and the insertion of membrane proteins by a proto-endoplasmic reticulum, the proto-endoplasmic reticulum is revealed to be the more likely path to complex endomembranes in the origin of eukaryotes.
A single-celled microbe that revels in Earth’s most hostile salt lakes has the remarkable ability to transform its mote of a body into multicellular tissue when the pressure’s on.
“The advent of clonal multicellularity is a critical evolutionary milestone,” the international team who made this discovery, led by Brandeis University pathobiologist Theopi Rados, write in their new paper.
Haloferax volcaniiis a member of the often-overlooked archaea domain, which looks quite similar to bacteria and yet have more in common with our own domain, eukaryota. Multicellularity is common in eukaryotes and rare among bacteria, and as far as we know, H. volcanii is only the second archaeon found to take this multicellular leap.
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In this remarkable conversation, Michael Levin (Tufts University) and Blaise Agüera y Arcas (Google) examine what happens when biology and computation collide at their foundations. Their recent papers—arriving simultaneously yet from distinct intellectual traditions—illuminate how simple rules generate complex behaviors that challenge our understanding of life, intelligence, and agency.
A new AI robot called π-0.5 uses 100 decentralized brains, known as π-nodes, to control its body with lightning-fast reflexes and smart, local decision-making. Instead of relying on a central processor or internet connection, each part of the robot—like fingers, joints, and muscles—can sense, think, and act independently in real time. Powered by a powerful vision-language-action model and trained on massive, diverse data, this smart muscle system allows the robot to understand and complete real-world tasks in homes, even ones it has never seen before.
Join our free AI content course here 👉 https://www.skool.com/ai-content-acce… the best AI news without the noise 👉 https://airevolutionx.beehiiv.com/ 🔍 What’s Inside: • A groundbreaking AI robot called π‑0.5 powered by 100 decentralized “π-nodes” embedded across its body • Each node acts as a mini-brain, sensing, deciding, and adjusting without needing Wi-Fi or a central processor • A powerful vision-language-action model lets the robot understand messy homes and complete complex tasks without pre-mapping 🎥 What You’ll See: • How π‑0.5 combines local reflexes with high-level planning to react in real time • The unique training process using over 400 hours of diverse, real-world data from homes, mobile robots, and human coaching • Real-world tests where the robot cleans, organizes, and adapts to brand-new spaces with near-human fluency 📊 Why It Matters: This new system redefines robot intelligence by merging biological-inspired reflexes with advanced AI planning. It’s a major step toward robots that can handle unpredictable environments, learn on the fly, and function naturally in everyday life—without relying on cloud servers or rigid programming. DISCLAIMER: This video explores cutting-edge robotics, decentralized AI design, and real-world generalization, revealing how distributed intelligence could transform how machines move, sense, and think. #robot #robotics #ai.
🔍 What’s Inside: • A groundbreaking AI robot called π‑0.5 powered by 100 decentralized “π-nodes” embedded across its body. • Each node acts as a mini-brain, sensing, deciding, and adjusting without needing Wi-Fi or a central processor. • A powerful vision-language-action model lets the robot understand messy homes and complete complex tasks without pre-mapping.
🎥 What You’ll See: • How π‑0.5 combines local reflexes with high-level planning to react in real time. • The unique training process using over 400 hours of diverse, real-world data from homes, mobile robots, and human coaching. • Real-world tests where the robot cleans, organizes, and adapts to brand-new spaces with near-human fluency.
