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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.

Get 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:

Contemporary Amperex Technology Co., Limited (CATL), the largest battery manufacturer in the world with a 38% share of the global market, has just announced some fairly significant breakthroughs in battery tech that aren’t just theoretical; they’re already hitting the market.

Over the past few decades, solar cells have become increasingly widespread, with a growing number of individuals and businesses worldwide now relying on solar energy to power their homes or operations. Energy engineers worldwide have thus been trying to identify materials that are promising for the development of photovoltaics, are eco-friendly and non-toxic, and can also be easily sourced and processed.

These include kesterite-based materials, such as Cu₂ZnSnS₄ (CZTS), a class of semiconducting materials with a that resembles that of the naturally occurring mineral kesterite. Kesterite could have various advantages over the conventional silicon-based photovoltaics that are most used today, including lower manufacturing costs, a less toxic composition and greater flexibility.

Despite their potential, kesterite solar cells developed to date attain significantly lower power conversion efficiencies (PCEs) than their silicon counterparts. This is in great part due to atomic-scale defects in kesterite-based materials that trap charge carriers and prompt non-radiative recombination, a process that causes energy losses and thus reduces the solar cells’ performance.

Cyberattacks can snare workflows, put vulnerable client information at risk, and cost corporations and governments millions of dollars. A botnet—a network infected by malware—can be particularly catastrophic. A new Georgia Tech tool automates the malware removal process, saving engineers hours of work and companies money.

The tool, ECHO, turns malware against itself by exploiting its built-in update mechanisms and preventing botnets from rebuilding. ECHO is 75% effective at removing botnets. Removing malware used to take days or weeks to fix, but can now be resolved in a few minutes. Once a security team realizes their system is compromised, they can now deploy ECHO, which works fast enough to prevent the from taking down an entire network.

“Understanding the behavior of the malware is usually very hard with little reward for the engineer, so we’ve made an automatic solution,” said Runze Zhang, a Ph.D. student in the School of Cybersecurity and Privacy (SCP) and the School of Electrical and Computer Engineering.