Innovation

Wind and solar generation is scaling faster than any other electricity sources in history. This chart looks at the time taken for different technologies to grow from 100 TWh to 1,000 TWh of annual electricity generation. Solar took just 8 years Wind took 12 years By comparison, gas took 28 years, coal 32 years and hydro 39 years Nuclear also reached the milestone in 12 years, but then its growth slowed sooner than wind. Importantly, this chart is not measuring market share. It is measuring how quickly different technologies scaled once they reached meaningful levels of deployment. And the story today is also bigger than generation alone. Batteries are increasingly extending solar generation into the evening peak, while electrification is creating new demand for clean electricity in transport, heating and industry. Much of this growth is being driven by improving economics, with wind, solar and batteries becoming increasingly competitive across a growing range of applications. That combination is beginning to reshape energy systems around the world. Renewables now generate more than one third of global electricity, and wind and solar continue to account for the majority of new power capacity added each year. The pace of deployment matters because energy transitions are ultimately about scale. And by that measure, wind and solar are growing faster than anything that came before them.

WIPOs global report on IP filings is out and records are being broken. 2024 saw the highest ever patent filings 3.7 million worldwide. Design filings also peaked at a record 1.6 mln, while trademark filings stabilized after two years of decline. But within this rich trove of data from nearly 150 IP offices, a few deeper insights stand out. First, emerging and developing countries continue to embrace IP-driven growth and transformation, whether driven by the need to diversify engines of growth, support increasing aspirations of local innovators and entrepreneurs, create more attractive investment environments, or simply seek new sources of growth. For the sixth consecutive year, India posts double-digit growth in patent filings, with Trkiye also up some 15%. Among the top 20 countries of origin, 12 saw increases in trademark filings, led by Argentina, Brazil and Indonesia, and with strong growth in upper middle-income economies like Colombia, South Africa, Thailand and Viet Nam. Design filings tell a similar story, with the fastest growth in India, Morocco and Indonesia. What this means is that many emerging economies are following the path of the worlds established innovation powerhouses in using IP as a strategic lever for economic growth, diversification, development and resilience. The next challenge is commercializing more of these filings, so they become real-world products and services. Second, were seeing more domestic, or resident filings. In areas like trademarks and designs, resident filings have traditionally made up the vast majority (+70%) as local businesses often register IP to protect brands and designs serving domestic markets. Now, were seeing the same dynamics in patents. Resident patent filings grew almost 7% last year, the fastest rise since 2016, to 72% of the total. This growth in domestic filings suggests that innovation ecosystems are maturing (even for high-tech discoveries, inventors typically file at home first before expanding abroad). It may also reflect shifts in global trade flows, with some industries becoming more localized. Third, many of the major trends in recent years continue to accelerate. Just as AI and digital innovation dominate the headlines, computer technology remains the top field for patent activity, with its growth outpacing all others. The gender balance in innovation is also improving. The proportion of women inventors in international patent applications has increased from 11.6% in 2010 to 18% last year. Beyond the individual data points, the value of this report lies in what it reveals about the global state of innovation and the direction its heading. This years WIPI shows that people everywhere continue to believe in the power of IP to protect ideas and incentivize innovation, and it gives WIPO the energy to continue strengthening IP ecosystems everywhere to give these innovators and creators the tools to protect and commercialize their ideas. https://ow.ly/gub150XqnE7

AI is rapidly moving from passive text generators to active decision-makers. To understand where things are headed, its important to trace the stages of this evolution. 1. : 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 responsesbut their capabilities end there. They dont retain memory, they dont take actions, and they dont understand goals. They are reactive, not proactive. 2. : - 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 , but still required orchestration. The system didnt plan or actit responded with more relevance. 3. : Agentic AI is a fundamentally different paradigm. Here, systems are built to perceive, reason, and act toward goalsoften without constant human prompting. An Agentic system includes: : to retain and recall information over time. : to decide what actions to take and in what order. : to interact with APIs, databases, code, or software systems. : to loop through perception, decision, and actioniteratively improving performance. Instead of a single model generating content, we now orchestrate , 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. Were no longer designing prompts. Were designing , - capable of interacting with the real world. This evolutionLLM RAG Agentic AImarks the transition from to - .

AI is becoming a make-or-break factor for banks. But success will not depend on their ability to offer #AI, but on their competence in integrating it. Lets take a look. Banking is forecasted to feel the biggest impact from generative AI among sectors and industries as a percentage of their revenues with the additional value calculated between $200 bn and $340 bn annually (source: McKinsey). But why is the impact so powerful? One of the main reasons is because the abrupt surge of gen AI is exponentially increasing the speed with which #banking is being transformed. That is not to say that the transformation has started with or due to AI. On the contrary: during the past 10 to 15 years banking was already in the middle of transforming from a human-based, relationship-first industry to a more automated and technology-driven business following the #fintech revolution and the ascend of nimbler and more innovative competitors. But AI now does 2 things: It brings the transition to a new level, across 3 dimensions: speed, outcome and impact. It turbo-charges one of the biggest challenges in modern FS: the combination of AI and data that brings under the same roof two inherently opposing forces: mass and customization. In other words, AI seems to find a credible answer to achieving hyper-personalization. In a recent report Deloitte has provided realistic examples on how this is done across both cost efficiency and income growth: Cost efficiency: Workforce acceleration efficiencies across the board: 015% of total staff cost IT development and maintenance acceleration: 1020% of IT staff cost Improved credit-risk assessment leading to 10-15% savings in impairment charges Improved FinCrime/fraud detection reducing litigation/redress charges and fraud losses Income growth: Next generation market analysis / predictive trading algorithms: 57% uplift on trading income Improved customer retention: 12% uplift on fees & commissions Improved customer acquisition through hyper-personalised marketing: 5-10% uplift from interest income and fees & commissions Tailored loan pricing based on credit risk assessment: 23% increase on net interest income Despite all the excitement around these estimated benefits, success will not be a walk in the park. It will depend on the banks ability to integrate AI in a seamless way into their day-to-day operations. Going forward AI will be re-writing much of the scenarios and use cases of the banking value chain. That doesnt necessarily mean that they will all be different, but most will certainly be enhanced with impact spanning both across the back-end and the front-end. Given that resources are limited, one of the main challenges will be how to identify the ones to focus on. Factors such as #strategy, potential impact and a match with the existing skillset should be guiding the selection process. Opinions: my own, Graphic source and use cases: Deloitte

Louder for the people at the back Many organisations today seem to have shifted from being institutions that develop great talent to those that primarily seek ready-made talent. This trend overlooks the immense value of individuals who, despite lacking experience, possess a great attitude, commitment, and a team-oriented mindset. These qualities often outweigh the drawbacks of hiring experienced individuals with a fixed and toxic mindset. The best organisations attract talent with their best years ahead of them, focusing on potential rather than past achievements. Lets be clear this is more about mindset and willingness to learn and unlearn as apposed to age. To realise the incredible potential return, organisations must commit to creating an environment where continuous development is possible. This requires a multi-faceted approach: 1. Robust Training Programmes: Employers should invest in comprehensive training programmes that equip employees with the necessary skills for their roles. This includes on-the-job training, mentorship programmes, online courses, and workshops. 2. Redefining Hiring Criteria: Organisations should revise their hiring criteria to focus more on candidates potential and willingness to learn rather than solely on prior experience or formal qualifications. Behavioural interviews, aptitude tests, and probationary periods can help assess a candidate's ability to learn and adapt. 3. Partnerships with Educational Institutions: Companies can collaborate with educational institutions to design curricula that align with industry needs. Apprenticeship programmes, internships, and cooperative education can bridge the gap between academic learning and practical job skills. 4. Lifelong Learning Culture: Encouraging a culture of lifelong learning within organisations is crucial. Employers should provide ongoing education opportunities and support for professional development. This includes continuous skills assessment and access to resources for upskilling and reskilling. 5. Inclusive Recruitment Practices: Employers should implement inclusive recruitment practices that remove biases and barriers. Blind recruitment, diversity quotas, and targeted outreach programmes can help ensure that diverse candidates are given a fair chance. By implementing these measures, organisations can develop a workforce that is adaptable, innovative, and resilient, ensuring sustainable success and growth.

Should you try Googles famous 20% time experiment to encourage innovation? We tried this at Duolingo years ago. It didnt work. It wasnt 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 weve tried, what weve 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: Its given to individuals, but we want to incentivize team work. Whats more, its 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 its 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 teams work is done. Whats next? Were working on a program that proactively identifies big picture, unassigned problems that we havent 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

Energy is once again dominating headlines all over the world. Gasand oil prices are volatile, key shipping routes face geopolitical pressure, and policymakers are concerned about supply risks. The renewed uncertainty is a reminder of an uncomfortable reality: the next energy crisis isnt an if its a when, and a question of how prepared we are. A defining challenge of this decade, and one that now feels more urgent than ever, is how to build a resilient energy system. Onethat minimises structural dependencies and is designed for rising electricity demand. The imperative of our time: The more we electrify, the less we import fossil fuels.The less we import, the more resilient we become. The course of action is clear: Relentlessly scale renewables: Slowing the buildout will not reduce costs. Quite the opposite delay compounds system costs for the entire economy. Fix the grids: As fast as possible, as efficiently as possible, and at the lowest possible cost. Before they become even more of a bottleneck. Secure 24/7 electricity supply: When the wind isnt blowing and the sun isnt shining, renewables need reliable backup in the form of battery storage and hydrogen-ready gas fired powerplants. But gas should serve only as a backup, with renewables and batteries reducing its utilisation. Reduce gas supply dependence with infrastructure and diversification: Wemust not replace old dependencies with new ones.Diversification of gas supplies is key. And the physicalprerequisite is an import infrastructure with buffers.We needthe plannedLNG terminals,complemented by anationally held gas reserveto help ensure secure supply in winter. Electrify everything that makes sense: The more we can power with mostly homegrown electrons, the less dependent we become on fossil imports. Other energy import-dependent countries like Japan and Chinahave electrification rates that are around 10 percentage points higher than Germanys.This showswhere the path forward lies. Electrification reduces reliance on imported fossil fuels, which in turn strengthens overall resilience. The time to act is now.

We may be standing at a moment in time for Quantum Computing that mirrors the 2017 breakthrough on transformers a spark that ignited the generative AI revolution 5 years later. With recent advancements from Google, Microsoft, IBM and Amazon in developing more powerful and stable quantum chips, the trajectory of QC is accelerating faster than many of us expected. Googles Sycamore and next gen Willow chips are demonstrating increasing fidelity. Microsofts pursuit of topological qubits using Majorana particles promises longer coherence times and IBMs roadmap is pushing towards modular error corrected systems. These arent just incremental steps, they are setting the stage for scalable, fault tolerant quantum machines. Quantum systems excel at simulating the behavior of molecules and materials at atomic scale, solving optimization problems with exponentially large solution spaces and modeling complex probabilistic systems tasks that could take classical supercomputers millennia. For example, accurately simulating protein folding or discovering new catalysts for carbon capture are well within quantums potential reach. If scalable QC is just five years away, now is the time to ask : What would you do differently today, if quantum was real tomorrow ?. That question isnt hypothetical its an invitation to start rethinking foundational problems in chemistry, logistics, finance, AI and cryptography. Of course building quantum systems is notoriously hard. Fragile qubits, error correction and decoherence remain formidable challenges. But globally public and private institutions are pouring resources into cracking these problems. I was in LAtoday visiting the famous USC Information Sciences Institute where cutting edge work on QC is underway and the energy is palpable. This feels like a pivotal moment. One where future shaping ideas are being tested in real labs. Just as with AI, the future belongs to those preparing for it now. QC Is an area of emphasis at Visa Research and I hope it is part of how other organizations are thinking about the future too.

The future of tech is not just software. Would you agree? It is structure. And one of the smartest materials in modern engineering is aluminum honeycomb. Used by companies like Boeing and Airbus, this material delivers: Up to 9095% weight reduction vs solid aluminum structures Strength-to-weight ratios comparable to steel Energy absorption up to 40x higher than monolithic materials in crash scenarios And it shows up everywhere: Aircraft structures Every 1 kg saved can reduce lifetime fuel burn by ~3,000 liters across an aircrafts lifecycle EVs Lightweighting can improve driving range by 510% depending on platform Data centers Cooling already accounts for ~3040% of total energy use Space & defense Launch costs still range from $2,000$10,000 per kg to orbit Heres the real insight: We are entering an era where materials = performance multipliers. AI models may get the headlines. But without advances in cooling, weight reduction, and structural efficiency those models dont scale in the real world. The next wave of innovation will come from the intersection of: Advanced materials AI systems Engineering design The companies that understand this will win quietly but decisively. Sometimes, the future isnt built in code. It is engineered in structure. #AI #Innovation via @science.with.ad #Engineering #MaterialsScience #DataCenters #EV #Aerospace #DeepTech

Today, Im thrilled to share what I believe is the biggest breakthrough in microbiome science for a decade. Nature Magazine, the world's most influential scientific journal, has just published a scientific paper by ZOE's scientists, establishing the first reliable, repeatable, global way to measure the health of an individuals gut microbiome. It represents the culmination of eight years of work at ZOE. Scientists have been trying to solve this puzzle for more than 20 years, right back to when they first discovered how important our gut microbes are for our health. Its been achieved only because more than 34,000 ZOE members took part in this research. Weve known for a long time that the microbiome is linked to cholesterol, inflammation, blood sugar control and even how we store fat. But weve never had a clear, evidence-based way to measure how healthy a microbiome actually is. This analysis finally delivers it, revealing a global ranking of microbes that works across populations, diets and environments. The insights are remarkable. Among the top 50 good microbes linked with better health, 22 were completely unknown to science until today, and most of the others have never been successfully grown in a lab. We also discovered clear links between these good microbes and health outcomes: healthy individuals carry around 3.6 more of these beneficial species, and people at a healthy weight carry about 5.2 more than those living with obesity. We also found a strong connection to diet. People eating healthier diets consistently have microbiomes that score better on this ranking. What we eat shapes our gut health, and now we can measure this relationship with unprecedented clarity. ZOE was created to enable microbiome research at a scale that traditional science has been unable to fund, and use this research to create actionable advice that can transform our gut health. This is a major milestone in that journey. Im delighted to say that as a result, this breakthrough science is immediately available for the public to investigate their own microbiome through ZOEs new Gut Health Test in the UK, and this is coming soon in the US. You can now receive not only a reliable measurement of how healthy your microbiome is as you change their diet, but also discover the health of clusters of gut microbes in your gut affecting metabolism, inflammation and more. To all our amazing ZOE members who have participated in our science: you made this possible. You are transforming our understanding of the microbiome. Thank you so much. I hope you feel as proud and excited as I do. I should note that your research is now published in Nature, which is the ultimate scientific accolade, and you can definitely brag about that with your friends! If you think this science could help others understand their health, Id love for you to share it. Youll find links to more details from our findings and access to the paper in the comments.