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

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

A promising Indian health-tech startup I invested in just shut down. Hard lessons inside… I invested in Onco back in 2020. It was basically an aggregator for cancer hospitals. Patients could visit their website or app, see all the hospitals and treatment options, get online consultations with doctors, and then choose where they wanted to get treated. They raised over $7 million from top investors like Accel, Chiratae, and others. They also built a strong brand. At their peak, they had 25,000+ visitors and over 1000 unique leads (cancer patients) every month - all organic, across their website, app, and social channels. We really thought hospitals would see the value in owning or partnering with a brand like this. But it didn’t work out that way. I’m sharing some lessons I learned watching this journey. Might be useful for founders (and investors) trying to crack India’s healthcare market: 1. Hospitals in India hold all the power. If you’re trying to aggregate them, you’re basically at their mercy. They will delay payments, ignore contracts, and squeeze every bit of margin out of you. They don’t really need you. Your margins get eaten alive by collections and compliance costs. 2. Digital only healthcare sounds great in pitch decks, but it doesn’t work here yet. People don’t pay enough for online-only services. Digital is great for leads, but it can’t be your whole business. Unit economics just don’t work with digital-only solutions because of low ARPU. 3. Offline is necessary. And brutally capital-intensive. Healthcare in India is still very much offline. Patients want to see a real centre and talk to doctors in person. Building those offline centres isn’t cheap. Each one takes at least 12–24 months to break even. You need serious money upfront. If you can’t fund that, you’re stuck. So, if you are building an aggregator only business in Indian healthcare, think twice. If you don’t have strong answers for these challenges, you’re just setting yourself up to be a middleman with no leverage, no margins, and no way out. That’s business suicide. #HarshRealities

#Batteries are starting to dominate the evening peak in California's grid, charging up with daytime solar then discharging as solar ramps down. On 5th April they set another new record for share of supply, peaking at over 34% at 7pm. This represents a rapid progression - two years ago the record was just 13%. And they remained the largest source of supply on the grid from 6:35pm until 9:40pm. As more and more battery storage enters the mix, batteries will continue to play an increasing role in the state's grid, and continue to break more records. They are flexible and extremely quick to respond. By charging in the middle of the day they are soaking up excess solar and are then putting this to good use later, reducing the need for gas and imports in the nighttime hours. From just 0.5 GW in 2018, by late 2024 California already had over 13 GW of battery storage capacity, with more on the way. While that may sound like a lot, there is still some way to go with the California Energy Commission estimating the state will need around 52 GW of battery storage to meet it's 2045 target of getting all its power from carbon-free sources. Batteries will play an important role in the decarbonised grid of the future. As prices continue to fall we will see more and more batteries deployed, and are certainly seeing this happen in Australia - especially Western Australia. We are just on the cusp of much more widespread adoption. Onwards and upwards! #energy #sustainability #renewables #energytransition

What happens when a legacy CPG giant like PepsiCo acquires a fast-growing disruptor like Poppi? It’s a blueprint for the future of FMCG. PepsiCo has spent years evolving its portfolio, shifting toward healthier, functional, and better-for-you options. From acquiring Siete Family Foods to Sabra Dipping Company, and now Poppi, they’re doubling down on what today’s consumers want: ✅ Functional Ingredients: Poppi taps into the gut health boom, projected to reach $72B+ globally by 2032 (Source: Market Research Future® (MRFR)). Consumers aren’t just looking for hydration—they want drinks that boost immunity, digestion, and energy. ✅ Premiumization of Soda: Traditional soda sales have declined by 12% in the last decade, while functional and prebiotic sodas are growing 35% YoY (Source: Beverage Digest). Brands like Poppi prove that consumers will pay a premium for added health benefits. ✅ The Power of Challenger Brands: Nearly 60% of Gen Z & Millennials say they trust emerging brands more than Big CPG (Source: McKinsey & Company). PepsiCo knows the future belongs to brands that feel authentic, mission-driven, and community-led. So, The “Big Food vs. Challenger Brand” battle is over-it’s now about collaboration. Legacy brands need disruptors to stay relevant. Health & wellness aren’t trends-they’re becoming industry standards. If a brand isn’t innovating in functional benefits, it’s already falling behind. The next wave of acquisitions? Expect strategic buys in functional beverages, gut health, and personalized nutrition. This is just the beginning. Are Big CPGs moving fast enough to keep up with evolving consumer demands? #FMCG #PepsiCo #Poppi #GutHealth #ConsumerTrends #MergersAndAcquisitions #FoodAndBeverage

Should you try Google’s famous “20% time” experiment to encourage innovation? We tried this at Duolingo years ago. It didn’t work. It wasn’t enough time for people to start meaningful projects, and very few people took advantage of it because the framework was pretty vague. I knew there had to be other ways to drive innovation at the company. So, here are 3 other initiatives we’ve tried, what we’ve learned from each, and what we're going to try next. 💡 Innovation Awards: Annual recognition for those who move the needle with boundary-pushing projects. The upside: These awards make our commitment to innovation clear, and offer a well-deserved incentive to those who have done remarkable work. The downside: It’s given to individuals, but we want to incentivize team work. What’s more, it’s not necessarily a framework for coming up with the next big thing. 💻 Hackathon: This is a good framework, and lots of companies do it. Everyone (not just engineers) can take two days to collaborate on and present anything that excites them, as long as it advances our mission or addresses a key business need. The upside: Some of our biggest features grew out of hackathon projects, from the Duolingo English Test (born at our first hackathon in 2013) to our avatar builder. The downside: Other than the time/resource constraint, projects rarely align with our current priorities. The ones that take off hit the elusive combo of right time + a problem that no other team could tackle. 💥 Special Projects: Knowing that ideal equation, we started a new program for fostering innovation, playfully dubbed DARPA (Duolingo Advanced Research Project Agency). The idea: anyone can pitch an idea at any time. If they get consensus on it and if it’s not in the purview of another team, a cross-functional group is formed to bring the project to fruition. The most creative work tends to happen when a problem is not in the clear purview of a particular team; this program creates a path for bringing these kinds of interdisciplinary ideas to life. Our Duo and Lily mascot suits (featured often on our social accounts) came from this, as did our Duo plushie and the merch store. (And if this photo doesn't show why we needed to innovate for new suits, I don't know what will!) The biggest challenge: figuring out how to transition ownership of a successful project after the strike team’s work is done. 👀 What’s next? We’re working on a program that proactively identifies big picture, unassigned problems that we haven’t figured out yet and then incentivizes people to create proposals for solving them. How that will work is still to be determined, but we know there is a lot of fertile ground for it to take root. How does your company create an environment of creativity that encourages true innovation? I'm interested to hear what's worked for you, so please feel free to share in the comments! #duolingo #innovation #hackathon #creativity #bigideas

AI Product Management AI Product Management is evolving rapidly. The growth of generative AI and AI-based developer tools has created numerous opportunities to build AI applications. This is making it possible to build new kinds of things, which in turn is driving shifts in best practices in product management — the discipline of defining what to build to serve users — because what is possible to build has shifted. In this post, I’ll share some best practices I have noticed. Use concrete examples to specify AI products. Starting with a concrete idea helps teams gain speed. If a product manager (PM) proposes to build “a chatbot to answer banking inquiries that relate to user accounts,” this is a vague specification that leaves much to the imagination. For instance, should the chatbot answer questions only about account balances or also about interest rates, processes for initiating a wire transfer, and so on? But if the PM writes out a number (say, between 10 and 50) of concrete examples of conversations they’d like a chatbot to execute, the scope of their proposal becomes much clearer. Just as a machine learning algorithm needs training examples to learn from, an AI product development team needs concrete examples of what we want an AI system to do. In other words, the data is your PRD (product requirements document)! In a similar vein, if someone requests “a vision system to detect pedestrians outside our store,” it’s hard for a developer to understand the boundary conditions. Is the system expected to work at night? What is the range of permissible camera angles? Is it expected to detect pedestrians who appear in the image even though they’re 100m away? But if the PM collects a handful of pictures and annotates them with the desired output, the meaning of “detect pedestrians” becomes concrete. An engineer can assess if the specification is technically feasible and if so, build toward it. Initially, the data might be obtained via a one-off, scrappy process, such as the PM walking around taking pictures and annotating them. Eventually, the data mix will shift to real-word data collected by a system running in production. Using examples (such as inputs and desired outputs) to specify a product has been helpful for many years, but the explosion of possible AI applications is creating a need for more product managers to learn this practice. Assess technical feasibility of LLM-based applications by prompting. When a PM scopes out a potential AI application, whether the application can actually be built — that is, its technical feasibility — is a key criterion in deciding what to do next. For many ideas for LLM-based applications, it’s increasingly possible for a PM, who might not be a software engineer, to try prompting — or write just small amounts of code — to get an initial sense of feasibility. [Reached length limit. Full text: https://lnkd.in/gYY-hvHh ]

Smart materials in this futuristic design shift color and texture based on temperature, motion, or light — turning fashion into adaptive tech. Would you wear it? 🧬 This isn’t sci-fi. + Smart textiles are forecast to grow into a $17.6 billion industry by 2030, driven by innovations in nanomaterials, thermal sensors, and electrochromic coatings. + AeroSkin’s concept shows what happens when AI, material science, and design collide — and it raises the question: What happens when your clothes start thinking for you... 🎯 Imagine soldiers with adaptive camouflage. ⚡ Athletes wearing gear that adjusts cooling zones dynamically. 🌆 Or professionals using color-shifting jackets as expressive, data-driven fashion statements. We’ve made phones smart, homes smart, even cars autonomous… yet most of us still wear “dumb fabric.” Maybe the next frontier of computing isn’t a screen — it’s the skin you wear. #WearableTech #SmartMaterials #Innovation #FutureOfFashion #AI #ChameleonJacket #AeroSkin #TechDesign #MaterialScience #AdaptiveClothing

We’ve called efficiency the unsung hero of the energy transition in the past. While the energy transition will happen first through the transition of energy usages, like the shift with transport, from internal combustion engines to electric vehicles, or from fuel or gas boilers to heat pumps, we cannot ignore the utmost priority of the energy transition: efficiency. Efficiency is the greatest path to reduce our energy use, our impact on the world’s climate through CO2 emission reduction, and very importantly, the best way to make solid and practical savings. In its most historical form, energy efficiency is about better insulation, to reduce heating (or cooling) loss in buildings like family homes, warehouses, office high rises, and shopping malls. This is useful, but expensive and tedious to realize on existing installations. Digitizing home, buildings, industries and infrastructure brings similar benefits at a much lower cost and a much higher economic return. The combination of IoT, big data, software and AI can significantly reduce energy use and waste by detecting leaky valves, or automatically adjusting heating, lighting, processes and other systems to the number of people present at any given time, using real-time data analysis. It also allows owners to measure precisely progress, report automatically on their energy and sustainability parameters, and benefit from new services through smart grid interaction. And this is just the energy benefit. Automation and digital tools also optimize the processes, safety, reliability, and uptime leading to greater productivity and performance.

NEW ANALYSIS: The International Energy Agency (IEA) just launched the World Energy Investment 2026 report. Headline figure: Clean energy investment is now more than double that of fossil fuels. $2,155bn for clean energy in 2025, against $1,008bn into oil, gas and coal. The crossover happened around 2016. Since then the gap has only widened. What was a narrow lead a decade ago is now a >2-to-1 split. This is unfolding during the largest energy security crisis the world has ever faced, with the Strait of Hormuz effectively closed. And the response is not a rush back to fossil fuels. The IEA projects oil investment to fall below $500bn in 2026, a third consecutive year of decline. Instead, countries are turning to what they can build at home. Solar alone is set to attract $365bn next year. Grid investment is up nearly 20% year on year. Low-emissions sources now account for more than 70% of all power generation investment globally. There are caveats. Coal spending is creeping up, gas investment is rising on the back of new LNG, and financing costs are climbing in the economies that can least afford them. But the headline number is hard to argue with. When the world faces an energy shock, the money increasingly flows toward electricity and domestically available clean power, not away from it.