Innovation

We trained a humanoid with 22-DoF dexterous hands to assemble model cars, operate syringes, sort poker cards, fold/roll shirts, all learned primarily from 20,000+ hours of egocentric human video with no robot in the loop. Humans are the most scalable embodiment on the planet. We discovered a near-perfect log-linear scaling law (R² = 0.998) between human video volume and action prediction loss, and this loss directly predicts real-robot success rate. Humanoid robots will be the end game, because they are the practical form factor with minimal embodiment gap from humans. Call it the Bitter Lesson of robot hardware: the kinematic similarity lets us simply retarget human finger motion onto dexterous robot hand joints. No learned embeddings, no fancy transfer algorithms needed. Relative wrist motion + retargeted 22-DoF finger actions serve as a unified action space that carries through from pre-training to robot execution. Our recipe is called "EgoScale": - Pre-train GR00T N1.5 on 20K hours of human video, mid-train with only 4 hours (!) of robot play data with Sharpa hands. 54% gains over training from scratch across 5 highly dexterous tasks. - Most surprising result: a *single* teleop demo is sufficient to learn a never-before-seen task. Our recipe enables extreme data efficiency. - Although we pre-train in 22-DoF hand joint space, the policy transfers to a Unitree G1 with 7-DoF tri-finger hands. 30%+ gains over training on G1 data alone. The scalable path to robot dexterity was never more robots. It was always us. - Website: https://lnkd.in/gxzgeP-2 - Paper: https://lnkd.in/g7PJdz_8

Grid bottlenecks are a feature — not a bug — of the energy transition. For years, we viewed economics as the main hurdle to scaling clean energy. High costs for wind, solar, heat pumps, and storage dominated the conversation. But the world has changed. Thanks to extraordinary innovation and dramatic cost reductions in renewables and electrification technologies, the bottlenecks we face today are different. They’re no longer about whether clean energy is affordable — it is. Instead, the challenge is whether our energy systems can evolve quickly enough to integrate it. A recent Financial Times piece highlights this clearly: across Europe, the rapid build-out of renewable generation now outpaces the ability of grids to move electricity to where it’s needed. Curtailment, congestion, and long queues for grid connections already cost billions annually — and without decisive action, these costs will grow. This isn’t a sign of failure. It’s a sign of success. It means the transition is happening faster than the infrastructure built for the fossil era can handle. The rise of decentralised, variable renewables and electrified heating and transport requires a fundamentally different approach to planning — one that anticipates growth rather than reacts to it. The EU’s move toward more coordinated, top-down scenario building and cross-border grid planning recognises exactly this. Better alignment between countries and system operators, faster permitting, and prioritisation of critical projects are essential steps to unlock the full value of cheap clean energy. Because every euro lost to bottlenecks is not a cost of climate action — it’s a cost of not modernising our grids fast enough. The more successful we are in deploying renewables and electrification, the more urgently we must upgrade and expand our grids. Grid constraints are not a reason to slow down. They’re a reason to speed up the transformation of an energy system that was never designed for the technologies now powering our transition.

A new 20-year analysis of satellite data shows that the Old Continent’s freshwater reserves are shrinking, silently and steadily. Satellites that weigh the Earth by tracking gravitational changes reveal 👉 Northern Europe is getting wetter. 👉 Southern and central Europe are drying fast. And what’s disappearing fastest is the water we don’t see — groundwater, the strategic reserve that keeps our taps running, our crops alive, and our economies functioning. This is #climatechange in real time. No models, no projections — observations from space. Researchers warn that Europe is barreling toward a 2°C world, and the consequences are already here: • Heavier downpours but longer, harsher dry spells • Winter recharge seasons shrinking • More runoff, less infiltration • Deep aquifers declining across the EU • Increasing pressure on public water supply and agriculture Groundwater is the backbone of Europe’s resilience. In 2022 alone: 🔹 62% of all public water supply came from groundwater 🔹 33% of agricultural demand relied on it 🔹 Groundwater abstractions increased by 6% despite lower overall water use Farmers across southern Europe are watching reservoirs drop while fruit and vegetable yields continue to fall. These are the same dynamics long documented across the Global South, now hitting Europe with unprecedented force. The old assumptions no longer hold. Europe is not water-secure. Infrastructure alone will not save us. New reservoirs arriving in 20 years are not a solution for a crisis happening today. We need: ✅ Radical efficiency — cutting leakage, modernising networks, accelerating water-smart design ✅ Water reuse at scale — separating drinking water systems from non-potable recycled streams ✅ Nature-based solutions — restoring wetlands, aquifers, and natural recharge ✅ Smarter climate-informed water governance — using the best science to guide every decision ✅ A mindset shift — rainwater harvesting, circular water systems, and demand-side management must become standard, not exceptional read the article in The Guardian 👇 https://lnkd.in/eeTsyMve

Invisible UX is coming 🔥 And it’s going to change how we design products, forever. For decades, UX design has been about guiding users through an experience. We’ve done that with visible interfaces: Menus. Buttons. Cards. Sliders. We’ve obsessed over layouts, states, and transitions. But with AI, a new kind of interface is emerging: One that’s invisible. One that’s driven by intent, not interaction. Think about it: You used to: → Open Spotify → Scroll through genres → Click into “Focus” → Pick a playlist Now you just say: “Play deep focus music.” No menus. No tapping. No UI. Just intent → output. You used to: → Search on Airbnb → Pick dates, guests, filters → Scroll through 50+ listings Now we’re entering a world where you guide with words: “Find me a cabin near Oslo with a sauna, available next weekend.” So the best UX becomes barely visible. Why does this matter? Because traditional UX gives users options. AI-native UX gives users outcomes. Old UX: “Here are 12 ways to get what you want.” New UX: “Just tell me what you want & we’ll handle the rest.” And this goes way beyond voice or chat. It’s about reducing friction. Designing systems that understand intent. Respond instantly. And get out of the way. The UI isn’t disappearing. It’s mainly dissolving into the background. So what should designers do? Rethink your role. Going forward you’ll not just lay out screens. You’ll design interactions without interfaces. That means: → Understanding how people express goals → Guiding model behavior through prompt architecture → Creating invisible guardrails for trust, speed, and clarity You are basically designing for understanding. The future of UX won’t be seen. It will be felt. Welcome to the age of invisible UX. Ready for it?

This isn’t a luxury. This is a $200 wheelchair redefining what’s possible. For millions, standing wheelchairs have always been out of reach. Until now. At R2D2, IIT Madras, a team dared to ask: What if mobility wasn’t a privilege, but a right? Their answer is a simple innovation -no Big Tech: A wheelchair that lets you stand—on your terms Ingenious gas-spring technology for seamless movement: -Supports up to 242 pounds -Priced at $200 (when others cost $2,000 or more) But the true breakthrough isn’t just in the engineering. It’s in the lives transformed. → Physical freedom is restored. Stand tall when you choose. Reach the top shelf. Cook your own meals. Keep your body strong and active. → Health is protected. Standing improves circulation. Strengthens bones. Prevents pressure sores. Aids digestion. Reduces heart risks. → Social inclusion becomes reality. Converse at eye level. Join meetings—no barriers. Participate fully in community life. Experience true belonging. Ask yourself: When was the last time you had to look up just to be heard? For millions, that’s every day. This isn’t only about standing. It’s about dignity. It’s about independence. It’s about living fully. And for the first time, it’s within reach for those who need it most. When innovation meets accessibility, lives change. This is technology for humanity. Follow me, Dr. Martha Boeckenfeld for more stories of tech that matters. ♻️ Share with your network to learn more about how simple innovation can change people's live. #TechForGood #Innovation #Healthcare

AI is rapidly moving from passive text generators to active decision-makers. To understand where things are headed, it’s important to trace the stages of this evolution. 1. 𝗟𝗟𝗠𝘀: 𝗧𝗵𝗲 𝗘𝗿𝗮 𝗼𝗳 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗙𝗹𝘂𝗲𝗻𝗰𝘆 Large Language Models (LLMs) like GPT-3 and GPT-4 excel at generating human-like text by predicting the next word in a sequence. They can produce coherent and contextually appropriate responses—but their capabilities end there. They don’t retain memory, they don’t take actions, and they don’t understand goals. They are reactive, not proactive. 2. 𝗥𝗔𝗚: 𝗧𝗵𝗲 𝗔𝗴𝗲 𝗼𝗳 𝗖𝗼𝗻𝘁𝗲𝘅𝘁-𝗔𝘄𝗮𝗿𝗲 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 Retrieval-Augmented Generation (RAG) brought a major upgrade by integrating LLMs with external knowledge sources like vector databases or document stores. Now the model could retrieve relevant context and generate more accurate and personalized responses based on that information. This stage introduced the idea of 𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗮𝗰𝗰𝗲𝘀𝘀, but still required orchestration. The system didn’t plan or act—it responded with more relevance. 3. 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜: 𝗧𝗼𝘄𝗮𝗿𝗱 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 Agentic AI is a fundamentally different paradigm. Here, systems are built to perceive, reason, and act toward goals—often without constant human prompting. An Agentic system includes: • 𝗠𝗲𝗺𝗼𝗿𝘆: to retain and recall information over time. • 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴: to decide what actions to take and in what order. • 𝗧𝗼𝗼𝗹 𝗨𝘀𝗲: to interact with APIs, databases, code, or software systems. • 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝘆: to loop through perception, decision, and action—iteratively improving performance.    Instead of a single model generating content, we now orchestrate 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗮𝗴𝗲𝗻𝘁𝘀, each responsible for specific tasks, coordinated by a central controller or planner. This is the architecture behind emerging use cases like autonomous coding assistants, intelligent workflow bots, and AI co-pilots that can operate entire systems. 𝗧𝗵𝗲 𝗦𝗵𝗶𝗳𝘁 𝗶𝗻 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴 We’re no longer designing prompts. We’re designing 𝗺𝗼𝗱𝘂𝗹𝗮𝗿, 𝗴𝗼𝗮𝗹-𝗱𝗿𝗶𝘃𝗲𝗻 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 capable of interacting with the real world. This evolution—LLM → RAG → Agentic AI—marks the transition from 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 to 𝗴𝗼𝗮𝗹-𝗱𝗿𝗶𝘃𝗲𝗻 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲.

For years, the biggest players in CPG and FMCG—Unilever, Nestlé, Kraft Heinz—built their empires on food. But now? They’re making a massive pivot..if you had told me 5 years ago that these brands would be pulling back from food, I would’ve raised an eyebrow. -Unilever is cutting loose its $8 billion ice cream division, choosing to focus on higher-margin beauty and wellness. -Nestlé is doubling down on health-science-based nutrition as food brands struggle with pricing power. - #CPG giants are seeing stronger growth in self-care, supplements, and skincare than in traditional food categories. The global personal care market is expected to hit $758 billion by 2030, while processed food growth slows. Why This Shift? 1. Margins in food are shrinking. Consumers are trading down, private labels are winning, and inflation-wary shoppers aren’t absorbing cost hikes like they used to. 2. Health & wellness are driving premiumization. Customers will pay more for skincare, supplements, and functional beverages—but not for basic pantry staples. 3. Brand loyalty in food is eroding. Over 50% of consumers are comfortable switching food brands based on price, but loyalty remains strong in beauty, healthcare, and wellness. Winning Brands Are Already Moving: -L'Oréal’s skincare division posted 9.1% revenue growth last year, while traditional CPG food brands saw single-digit declines. -The Coca-Cola Company is investing in functional drinks and non-carbonated wellness categories to stay relevant. -PepsiCo’s biggest success? Gatorade’s expansion into hydration and performance-based drinks, not soda. CPG Leaders: ✅ Stop thinking of food as the core driver of growth. Instead, align with evolving consumer behavior. ✅ Invest in personalization, self-care, and functional health. That’s where demand (and pricing power) is strongest. ✅ Rethink your brand mix. Is your portfolio weighted toward categories that will still be relevant in 5-10 years? So, here’s my question to FMCG execs: Are you future-proofing your brand strategy—or just managing decline? Let’s talk. #FMCG #CPG #ConsumerTrends #GrowthStrategy #Beauty #Wellness #RevenueShift #BrandEvolution "

We reviewed 800+ health startups in India this year. Met 200+ founders in person. These are entrepreneurs building across health tech, fitness, nutrition, software for doctors, diagnostics, healthy food, longevity, sports, elder care, women health, lifestyle management & more. This is a long post on everything we've seen and observed in 2024 at Rainmatter by Zerodha. If you're an entrepreneur, investor of health enthusiast, this is for you. 1) There is a telemedicine fatigue- The post-pandemic boom in telemedicine has plateaued. While accessibility improved, sustainable consumer engagement still remains a challenge due to weak doctor-patient relationship and lack of differentiation. Patients want emotional and personalised engagement. Most companies are overusing AI in the disguise of scale. Opportunity is to solve for depth (chronic disease management) rather than breadth (generic consultation marketplaces). 2) Overload of premium fitness and wellness Apps- Apps targeting high-income urban users are oversaturated. Most startups overestimate the willingness of users to pay for digital fitness content. Opportunity is to focus on communities, hybrid models (offline + online), or affordable mass-market solutions. India is still not ready for Peloton content. We breathe YouTube. 3) Selling SaaS tools to Doctors- Doctors in India are notoriously price-sensitive. Most SaaS products fail due to limited willingness to adopt technology and low ROI visibility. Maybe companies should emphasise on simplicity and immediate value delivery. Job of a Doctor is to deliver treatment to patients and not learn how to use software. Need to humanise software in primary and secondary health care 4) Longevity buzz- Longevity startups sound exciting but cater to a niche. Everyone loves the idea of a pill or device that adds 50 years to life. But longevity is 80% lifestyle and 20% intervention. Startups chasing the 20% often overpromise and underdeliver. Without a strong clinical base or mass appeal, they will remain limited to aspirational urban elites. Opportunity is in integrating into broader wellness solutions rather than standalone ventures 5) Healthy food & nutrition- Overcrowding of “healthy snacks” and “superfoods” where differentiation is low and margins are squeezed by Quick commerce and logistics. Maybe companies should move beyond buzzwords like “organic” or “keto” and solve for authentic, local, and culturally aligned nutrition. India is a country of a million palates 6) Chronic disease management- Diabetes, hypertension, Weight loss and mental health requires long-term engagement and behaviour modification. While the space is competitive, there is room for solutions that prioritise patient journeys and retention over time. Driving outcome has to be the focus. Everything else is a vanity feature that doesn’t earn trust. Paid marketing will get expensive customers who won’t stick around Sharing the remaining notes in the comments section. Read below

Keeping track of AI governance, policy and regulations is a never-ending task Here are the key tracker resources you need to follow to stay ahead 𝐀𝐈 𝐈𝐍𝐂𝐈𝐃𝐄𝐍𝐓𝐒 & 𝐑𝐈𝐒𝐊𝐒 ➡️ AI Risk Repository [MIT FutureTech] A comprehensive database of 700 risks from AI systems 🔗 https://airisk.mit.edu/ ➡️ AI Incident Database [Partnership on AI] Dedicated to indexing the collective history real-world of harms caused by the deployment of AI 🔗 https://lnkd.in/ewBaYitm ➡️ AI Incidents Monitor [OECD - OCDE] AI incidents and hazards reported in international media globally are identified and classified using machine learning models 🔗 https://lnkd.in/e4pJ7jcA 𝐀𝐈 𝐑𝐄𝐆𝐔𝐋𝐀𝐓𝐈𝐎𝐍𝐒 & 𝐏𝐎𝐋𝐈𝐂𝐈𝐄𝐒 ➡️ Global AI Law and Policy Tracker [IAPP - International Association of Privacy Professionals] Resource providing information about AI law and policy developments in key jurisdictions worldwide 🔗 https://lnkd.in/eiGMk9Rm ➡️ National AI Policies and Strategies [OECD.AI] Live repository of 1000+ AI policy initiatives from 69 countries, territories and the EU 🔗 https://lnkd.in/ebVTQzdb ➡️ Global AI Regulation Tracker [Raymond Sun] An interactive world map that tracks AI law, regulatory and policy developments around the world 🔗 https://lnkd.in/ekaKzmzD ➡️ U.S. State AI Governance Legislation Tracker [IAPP - International Association of Privacy Professionals] Tracker which focuses on cross-sectoral AI governance bills that apply to the private sector 🔗 https://lnkd.in/ee4N-ckB. 𝐀𝐈 𝐆𝐎𝐕𝐄𝐑𝐍𝐀𝐍𝐂𝐄 𝐓𝐎𝐎𝐋𝐊𝐈𝐓𝐒 & 𝐑𝐄𝐒𝐎𝐔𝐑𝐂𝐄𝐒 ➡️ AI Standards Hub [The Alan Turing Institute] Online repository of 300+ AI standards 🔗 https://lnkd.in/erVdP4g7 ➡️ AI Risk Management Framework Playbook [National Institute of Standards and Technology (NIST)] Playbook of recommended actions, resources and materials to support implementation of the NIST AI RMF. 🔗 https://lnkd.in/eTzpfbCi ➡️ Catalogue of Tools & Metrics for Trustworthy AI [OECD.AI] Tools and metrics which help AI actors to build and deploy trustworthy AI systems 🔗 https://lnkd.in/e_mnAbpZ ➡️ Portfolio of AI Assurance Techniques [Department for Science, Innovation and Technology] The Portfolio showcases examples of AI assurance techniques being used in the real-world to support the development of trustworthy AI 🔗 https://lnkd.in/eJ5V3uzb Happy tracking!

Many groundbreaking innovations stem from solving specific, sometimes minor, issues but yield profound impacts. What do you think about this one? These "incremental innovations" drive efficiency, safety, cost savings, and user experiences forward. Take a look at some examples: - Post-it Notes: Born from a failed attempt at a strong adhesive, these sticky notes revolutionized quick note-taking and reminders. - Airbags in Cars: Rather than redesigning vehicles entirely, adding airbags significantly boosted passenger safety and reduced accident fatalities. - Gore-Tex Fabric: By solving the simple problem of staying dry and comfortable, this breathable, waterproof fabric transformed outdoor clothing. - QR Codes: Improving on barcodes, QR codes store more data and offer easier scanning, revolutionizing information sharing and transactions. - Zippers: Replacing buttons and hooks, zippers streamlined fastening clothes and bags with speed and security. - Wheels on Luggage: The addition of wheels to suitcases set a new standard, making travel significantly more convenient. - Penicillin: Beyond its initial discovery, incremental enhancements in production and distribution have saved countless lives through antibiotics. - LED Lighting: The shift from incandescent bulbs to LEDs delivers substantial energy savings and longer lifespans, addressing efficiency and environmental concerns. - USB Ports: Standardizing a universal port for data transfer and charging simplified connectivity across a diverse range of devices. These examples showcase how small improvements can lead to significant advancements in various aspects of our lives. #Innovation #Progress #Efficiency #Safety via @shajapur_mandi_bhav #Technology