AI & Robotics: Microsoft, ASLP, Proception, Boston Dynamics, Manus, Anthropic, T-Mobile, Cortical Labs, Sanctuary AI, Alibaba, Convergence AI, Muks Robotics

I get this question all the time; Wait, AI and robotics… aren't they the same thing? Not quite. And understanding the difference is key to understanding the future we're walking into. Here's the simplest way I can break it down; Robotics is about building machines that can sense, move, and act in the real world. Think: Mechanical arms on assembly lines, drones that fly, rovers that explore Mars. Artificial Intelligence (AI) is about building brains that can think, learn, and make decisions. Think: Netflix recommending your next binge, ChatGPT writing responses, algorithms predicting stock prices. One is the body. The other is the mind. Separately, they're powerful. Together? That's when things get interesting. Here's what most people miss, Robots need AI to become smart. Without AI, a robot is just a machine following pre-programmed instructions. It can't adapt. It can't learn. It repeats the same action forever. But AI needs robots to become physical. Without robotics, AI is trapped in the digital world. It can think, sure but it can't touch, build, or move through space. When you combine both, you get something completely different, Machines that perceive their environment. Machines that plan their next move based on what they see. Machines that perform tasks — not blindly, but intelligently. This is what humanoid systems like Figure 01 & 03 represent. Not just robots that move.Not just AI that thinks.But machines that understand what they're doing. And here's why this matters; The robotics founders who win in the next decade won't just be building better machines. They'll be building machines that can learn, adapt, and collaborate with humans in real time. That's not science fiction anymore. That's the present. But if you can't explain that difference clearly to investors, to customers, to the public — your innovation stays invisible. So here's my challenge for you, How would you explain AI vs Robotics to a 10-year-old? Try it below ⤵️ Because if you can make it simple then you can make it powerful 💙 #AIvsRobotics #HumanoidAI #FutureOfTech #RoboticsEducation #FigureAI #STEMSimplified #AIExplained

Mastering the Art of Defuzzification: A Key to Effective Fuzzy Logic Systems In the realm of artificial intelligence and fuzzy logic, defuzzification stands as a critical process that transforms fuzzy sets into precise outputs. As we navigate increasingly complex decision-making environments, understanding and implementing effective defuzzification methods can significantly enhance the performance of AI systems. Defuzzification is essential when dealing with fuzzy inference systems, where inputs are often imprecise or uncertain. The goal is to convert these fuzzy outputs into a single crisp value that can be used for decision-making. There are several popular methods for defuzzification, each with its own strengths and applications: 1. **Centroid Method**: This widely-used technique calculates the center of gravity of the fuzzy set. It provides a balanced output that considers all parts of the fuzzy set, making it ideal for many applications. 2. **Mean of Maximum (MOM)**: This method focuses on the maximum membership values within the fuzzy set. It’s particularly useful when the output needs to reflect the most significant fuzzy values, ensuring that the most relevant information is prioritized. 3. **Bisector Method**: By finding the vertical line that divides the area under the fuzzy set into two equal halves, this method offers a unique perspective on the output, balancing the influence of both extremes. 4. **Smallest of Maximum (SOM)** and **Largest of Maximum (LOM)**: These methods provide outputs based on the smallest or largest maximum membership values, respectively. They are beneficial in scenarios where extreme values play a crucial role in decision-making. 5. **Weighted Average**: This approach combines multiple fuzzy outputs by assigning weights based on their relevance, allowing for a more nuanced decision-making process. As AI continues to evolve, mastering these defuzzification techniques will empower professionals to build more robust and reliable fuzzy logic systems. Whether you're developing smart home technologies, autonomous vehicles, or advanced data analytics tools, understanding how to effectively defuzzify can lead to better outcomes and enhanced user experiences. Let’s embrace the intricacies of fuzzy logic and elevate our AI capabilities! #artificialintelligenceschool #aischool #superintelligenceschool

Physical AI is transforming the world around us. When we talk about AI, most people immediately think of chatbots, recommendation engines, or virtual assistants. But AI isn’t just digital, it’s also physical. Physical AI is AI embedded in the real world, making machines smarter, safer, and more capable. Think: 🤖 Robots that collaborate with humans in factories 🚗 Self-driving cars navigating busy streets 🏭 Industrial manipulators handling complex assembly tasks 🏢 Smart cameras and CCTV systems that proactively monitor safety and security Unlike digital AI, which exists in software, Physical AI interacts with the environment, senses changes, and acts on them in real time. The result? Safer workplaces, smarter cities, efficient manufacturing, and even proactive security. It’s where AI meets the tangible world, and the possibilities are endless. Physical AI isn’t the future, it’s here, embodied, and transforming every space it touches. #PhysicalAI #AI #Robotics #SmartCities #Innovation #FutureOfWork #AIInAction #DigitalMeetsPhysical #SmartVueAI

𝗘𝗺𝗯𝗼𝗱𝗶𝗲𝗱 𝗔𝗜: 𝗪𝗵𝗲𝗻 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗦𝘁𝗲𝗽𝘀 𝗢𝘂𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗦𝗰𝗿𝗲𝗲𝗻 We often hear about Artificial Intelligence in the digital world chatbots, Agents, and Virtual assistants. But wait, a silent revolution is unfolding, one that’s bringing AI into the physical world. Welcome to the era of Embodied AI, where intelligence doesn’t just compute, it moves. Take Figure Robotics, for instance. Their latest prototype, Figure 3, is a remarkable leap toward truly humanoid robots. Its predecessor, Figure 2, is already being trained inside BMW factories, performing manual tasks and even household chores! Or look at Unitree Robotics, which is offering highly capable humanoid and quadruped robots at a fraction of the traditional cost and yes, you can already find some of their models on Walmart’s website. Then there’s Clone Robotics, which has built the ProtoClone V1 using 3D-printed polymer bones and over 1,000 myofiber muscles synthetic strands that contract under pressure, mimicking the structure and movement of the human body. The result? Movements that are smooth and organic, no longer the jerky motions we once associated with robots. And of course, the frontier between humans and machines is blurring faster than ever as Neuralink has already demonstrated users controlling robotic arms directly with their brains. What once belonged to sci-fi movies is now being built in real labs by real engineers, in real time. 💡 Many years from now, we might look back at this very decade 2020 to 2029 as the one where AI stepped out of the digital world as a Humanoid and learned to walk among us. The video attached below showcases many of these breakthroughs.... #AI #EmbodiedAI #Robotics #HumanoidRobots #Innovation #FutureOfWork #Neuralink #Technology #DeepTech #Automation

Why Degrees of Autonomy is so important in AI? Degree of autonomy is a term in AI that actually tells how independent something (like a robot, car, or AI system) can be in thinking, deciding, and doing things without needing constant help from a person. Think of it like a kid growing up: - Low autonomy: A toddler who needs hand holding for everything – that's like a basic tool that only works when you tell it exactly what to do. - Medium autonomy: A teenager who can handle tasks on their own but checks in sometimes – like a self-driving car that navigates roads but alerts you for tricky spots. - High autonomy: An adult living independently, making all decisions – like a fully robotic factory that runs itself, adapts to problems, and only needs oversight for big issues. In AI, it's a scale from "just follows orders" to "figures out goals and fixes stuff solo." The higher the degree, the smarter and more self-reliant it is, but it also needs built-in safety rules to avoid mistakes. #FutureOfAI #AITech #AIEthics #MachineLearning #AIInnovation #TechTrends

🔥 AI is no longer confined to screens - it’s stepping into the real world. Imagine a robot that doesn’t just see 👀 or speak 💬, but actually understands, reasons, and acts - in the same fluid way humans do. That’s the promise behind Google’s Gemini Robotics - a new generation of vision-language-action models designed to bring embodied intelligence to life. These models blend perception, cognition, and motion allowing robots to pick up a cup, open a drawer, or rearrange objects - not by memorizing moves, but by reasoning about their surroundings. 🌍 It’s a shift from thinking about the world to thinking within it. And that shift doesn’t stop at robotics. At evvolv.ai, we see the same transformation unfolding inside enterprises -where AI systems are evolving from passive analytics tools to active agents that reason, plan, and execute. 💡 Just like Gemini Robotics acts in the physical world, our AI agents act in the digital world - automating decisions, drafting strategies, managing workflows, and learning from every outcome. The next decade won’t be about using AI. It’ll be about working alongside it. And we are building that bridge #GeminiRobotics #EvvolvAI #AgenticAI #AITransformation #GoogleAI #FutureOfWork #Innovation #EnterpriseAI #ArtificialIntelligence #Automation

The AI landscape is transforming rapidly! We're seeing groundbreaking advancements including MIT's TX-GAIN, now the most powerful university AI supercomputer in the US, and IBM's hyper-efficient Granite 4.0 models. Meanwhile, China is pushing the boundaries of humanoid robotics with realistic AI robots for seamless human interaction, and Google’s Jules Tools is streamlining developer workflows. As the discussion around human-AI convergence by 2050 picks up, it's more crucial than ever to implement robust governance for responsible AI use. Stay informed on the latest in AI innovation and its ethical implications. #AI #Innovation #TechNews #Robotics https://lnkd.in/gzRaeFm4

The Future of AI Isn't a Robot. It's Your Toaster. The fascination with humanoid robots as the embodiment of AI often overlooks a significant barrier: human language. How can AI truly grasp our world if it only comprehends our words, lacking the context behind them? The true breakthrough in AI will not stem from a robot that mimics human behavior. Instead, it will arise from integrating AI into our everyday lives. Consider an AI that doesn't merely read about the world—it experiences it. It learns from the environment we inhabit. This is why I encourage every brand and manufacturer to prioritize AI as a core function in their next-generation products. Envision more than just a talking assistant: - An electric vehicle that adapts to your driving habits and real-time road conditions. - A refrigerator that understands nutrition, manages waste, and knows your pantry better than you do. - An air conditioner that learns the micro-climate of your home for optimal efficiency. - A toaster that perfects your toast based on the moisture content of the bread. These are not just "smart" appliances; they represent the senses of AI. By providing AI with diverse forms in our homes, cars, and cities, we enable it to learn from a more natural, physical, and intuitive dataset. Let’s shift our focus from creating a single robot to building a smarter world. #EmbodiedAI #AIoT #FutureIsNow #SmartHome

Crossing the Embodiment Threshold: When AI Learns to Move For decades, AI existed in screens, clouds, and servers—intelligence without form. But in the past year, something extraordinary happened: AI gained a body. We’ve officially crossed the Embodiment Threshold—the moment when artificial intelligence transitions from digital cognition to physical capability. Humanoid robots are no longer science fiction. They’re operating forklifts, assembling parts, walking factory lines, and responding to human instructions in natural language. This isn’t a prototype phase. It’s deployment. 🔹 The Rise of Physical AI AI is no longer a passive observer of data; it’s an actor in reality. Tesla’s Optimus executes dynamic manipulation tasks with learned dexterity. Figure 03 has completed multi-week warehouse shifts with zero remote intervention. XPeng’s DR02 merges motion control with perception models adapted from self-driving AI. This convergence of reasoning and motion marks a paradigm shift: intelligence embodied. 🔹 Why Humanoid Form Wins Humanoids aren’t shaped like us by coincidence—they’re optimized for a human-built world. Every switch, shelf, and tool we’ve made assumes a body like ours. The humanoid is not a novelty—it’s compatibility embodied. With global logistics and retail already built around human ergonomics, the bipedal form isn’t aesthetic—it’s economic. 🔹 The New Corporate Race From DeepMind’s embodied learning systems to NVIDIA’s Project GR00T and Alibaba’s humanoid SDK, every major tech power is converging on a single goal: to unify simulation, reasoning, and physical control into one deployable intelligence. We’re watching a new $5 trillion industry take shape at the intersection of robotics, AI, and infrastructure. 🔹 Crossing the Threshold What defines this new era isn’t just movement—it’s meaning. Embodied AI doesn’t follow scripts. It perceives, plans, and adapts. It’s the first generation of machines that can live and learn in the same environments we do. The question is no longer when robots will work beside us—it’s what happens when they start working without us. 👉 Read the full breakdown: https://lnkd.in/gUmYrc4E 👉 Watch the full episode: https://lnkd.in/gar4X9ER The digital mind has crossed into the physical world—and it’s not looking back.