Innovation

The latest reporting from the Financial Times highlights a point that energy analysts have been making for years: geopolitical shocks consistently strengthen the case for renewables, electrification and storage. Microsoft’s global vice-president for energy notes that oil and gas price spikes linked to the Middle East conflict reinforce the value of wind, solar and batteries in providing price stability. Once installed, renewables offer predictable cost profiles and reduce exposure to volatile global fuel markets. We saw this dynamic after Russia’s invasion of Ukraine. Europe accelerated solar deployment, heat pump uptake increased in several countries, and governments revisited questions of energy security through the lens of diversification and electrification. The underlying issue remains unchanged. Fossil fuels must continuously flow through complex global supply chains. When those flows are disrupted, prices spike and economies are exposed. Renewables, by contrast, are capital intensive upfront but deliver long term domestic supply and insulation from commodity shocks. There are short term risks. Inflation, higher interest rates and supply chain constraints can slow clean energy investment. Some governments may also respond by doubling down on gas infrastructure. The policy challenge is to avoid locking in further structural vulnerability. Energy security and climate policy are not competing objectives. In a world of recurrent geopolitical instability, they are increasingly aligned.

WIPO’s 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 Türkiye 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 world’s 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, we’re 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, we’re 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 it’s heading. This year’s 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

🚨 Introducing the AI Apps 50: Startup Edition Ever wondered how startups are spending their money when it comes to AI? Our team at Andreessen Horowitz worked with Mercury to crunch the numbers and rank the top applications by spend. The list + what we learned from it ⬇️ - Horizontal apps have a slight lead over vertical (60% of the list). This includes general assistants (ex. Perplexity) and SIX different meeting support tools (ex. Fyxer AI). But, it also encompasses creative tools and vibe coding tools that are used in roles across orgs. - Vertical apps can augment human labor...or replace it. We're mostly seeing the former - but five companies on the list allow customers to "hire AI" (ex. Crosby Legal, Cognition, 11x). Labor augmenters mostly assist with customer service, sales, and recruiting. - Vibe coding has landed in enterprises. It's not just a prosumer trend! Number three on the list, below OpenAI and Anthropic? Replit. Other listmakers in the category include Lovable and Emergent, while Cursor made the ranks for more technical users. - Products are making the consumer -> enterprise jump. 12 cos also appeared in our most recent Consumer AI Top 100 - almost all of which started out B2C and have migrated B2B over time. In fact, 70% of listmakers are available for individual use (no enterprise license needed)! Check out the full report: https://lnkd.in/gmMvfvSv

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

My team and I get pitched 5–10 new businesses every week. Mostly from entrepreneurs trying to raise money. If you want your message or pitch to stand out to investors, do this: 1. Start with the problem, not the product. If I don’t feel the pain, I won’t value the solution. 2. Be brutally clear. My team should understand your business in 10 seconds or less. 3. Show traction, not just vision. Even if it's small, show me that the market wants it and you know how to deliver. 4. Tell me why you’re the one. I’m investing in you as much as the idea. Show conviction, not just ambition. 5. Make it a conversation, not a monologue. Curiosity builds trust. Ask good questions and make it collaborative. Keep it simple.

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.

AbbVie and Johnson & Johnson contribute data to fuel new molecular prediction drug discovery model, OpenFold3 💊AlphaFold 3 is a leading AI tool for predicting protein structures, but it lacks enough data on how proteins interact with drug molecules, limiting its utility in drug discovery 💊In response, AbbVie and Johnson & Johnson have recently teamed up to use their own data enhance a new AI model, OpenFold3, within the AI Structural Biology Consortium (AISB) 💊The consortium also includes Sanofi, Boehringer Ingelheim, and Takeda pooling collective pharma expertise and proprietary data to push AI-driven drug discovery forward 💊AbbVie alone is contributing over 9,000 proprietary protein-ligand structures, with other companies likely contributing similar volumes locked in private repositories 💊The data will remain confidential, protected by Apheris’ federated learning platform, which enables joint AI training without exposing or transferring sensitive data 💊The model will be developed collaboratively in a way that safeguards intellectual property and will remain accessible only to consortium members, not the public or external researchers 👇Link to articles in comments #pharma #digitalhealth #ai

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

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. Let’s 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: 0–15% of total staff cost —  IT development and maintenance acceleration: 10–20% 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: 5–7% uplift on trading income —  Improved customer retention: 1–2% 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: 2–3% 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 doesn’t 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