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SANATAN LABS - The Architect’s Compass: 10 Directives for the Great Transition (PASSIONIT PRUTL KALKI AIDHARMA framework) To navigate the "Audit of Fire" during this profound transition toward Satya Yuga, Krishna (Strategic Intelligence), Kalki (Systemic Reset), and Shakti (Raw Life Force) offer these ten essential directives for humanity: 1. Master the Asymmetry of Calm In a world of screaming headlines, silence is your greatest weapon. Respond from a place of internal stillness rather than reacting to external noise. When the system is chaotic, your stability becomes the new "Safe Haven." 2. Audit Your Identity (The Laawaris Test) Ask yourself: "If my titles, assets, and digital footprint vanished, who remains?" Detach your worth from possessions. True sovereignty is found when you are no longer "claimed" by the ego-driven systems of the world. 3. Embrace the "Mirror of Kalki" Do not fear the "Bloody Moon" or the exposure of decay. View every systemic collapse—financial, social, or institutional—as a necessary diagnostic. Use this "Mirror" to identify your own attachments and incinerate them before they become liabilities. 4. Move from "Me" to "Mission" Unity is not sameness; it is alignment. Replace "Me vs. You" with "Us vs. The Problem." When diverse strengths are aligned under a shared purpose (Aidharma), the friction of competition dissolves into the flow of progress. 5. Trust the "Internal Gold" While external currencies and metals face regulation or restriction, your integrity remains non-tradeable and unconfiscatable. Invest in your skillsets, your character, and your resilience. These are the only assets that survive the "Audit of Fire." 6. Respect the "Flow of Lakshmi" Prosperity is a river, not a reservoir. Hoarding in fear leads to stagnation and decay. Circulate value through mentorship, ethical trade, and "Groom and Grow" practices. Wealth that serves the collective remains protected by the Sun and Moon. 7. Humanize the Machine (13th Node Reset) Use AI and technology as a "Numeric Auditor" to expose corruption, but never let the cold logic of the machine replace the warmth of human intuition. Ensure technology serves the 14th Node: Absolute Truth. 8. Practice Guerrilla Respect Disarm your "enemies" by preserving their dignity even when you disagree with their actions. Respect targets the ego of the opponent, weakening their appetite for control and opening a path for diplomacy. 9. Build Internal Havens As geography stops being a protection, focus on "Internal Research and Innovation." Cultivate a mind that can remain creative and functional even when trade arteries are choked. 10. Surrender to Karmic Gravity Accept that "God Proposes, Man Disposes." You cannot control the celestial reset, but you can control your alignment with it. Follow the path of Dharma, and the gravity of the new era will pull you toward peace rather than destruction.

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Really useful insights.. Couldnt agree more with what was said. Barring may be 1 point. I am increasingly seeing AI doing the coding and more focus on QA and prompt engineering to ensure the right inputs go in... A lot moving in the back of many of these software organisations and teams. Next 6-12 months could be pretty dramatic in my view....

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Why we invested in Ringg.ai It had been a month since Prashant Kataria finished the sector mapping for voice AI. The study revealed that with the advent of generative models, the voice stack was evolving rapidly. With these new models, we observed that: 1. Intent recognition accuracies were crossing 80% 2. Latencies of responses reached <200ms 3. Time to resolve complex queries was going down 4. Empathy and emotional aspects in conversations were becoming close to real life interactions With these changes we felt that the time was ripe for voice agents to become part of the core infrastructure for the AI. The AI voice tech stack had evolved enough for enterprises to incorporate agentic voice in new and existing workflows. Engineering a stack together was a set of tradeoffs between latency, voice quality, resolution time and specialisation of use case.  Over the month, we had been in the process of reachouts in the space that fitted the considerations we had identified. We were looking for a startup that could deliver scalability across multiple use cases so that by and by its numerous webhooks within an enterprise could create a virtuous loop of customer interaction making it an intelligent repository of “why customers engage and what issues they face and how they respond”.   The voice agent space looked crowded at first pass just like the space Moengage was in when I became their first institutional investor. The crowd was a deterrent, but we found that many companies were still struggling to build the product. Independence Day 2025 was over a long weekend. Everyone was looking forward to a break, but Arkam was abuzz with intense work. We had identified the most promising startup in the voice ai space - Ringg AI.  Ringg stood out from a crowd because it had quietly hit the highest deployed ARR across horizontal use cases. Ringg’s momentum was telling - live customers asking for more deployments  and deployments scaling rapidly. Founded by Siddharth Shankar Tripathi, Utkarsh Shukla and Kali Charan Vemuru, the team emphasized quick learning and turnaround. When we find something, we love, we move very fast. So, the weekend turned into a dedicated Ringg week. We got busy with reference calls and product deep dives.  We liked the team and the team chemistry. Speed of build and responsiveness was allowing the team to go live in 48 hours from POC.  The Customer feedback was about Ringg coming thru fter the customer faced failure with internal projects and competitive products. Most of all we loved the founders’ energy. Hungry, ready to build and ambitious. We got our IC together at short notice and the investment was approved.  We closed Ringg’s Series A round last week. By 2027, Ringg targets its customer conversation to grow 10X to 100 million conversations a month. You can’t slow down teams like Ringg! They will be smashing many barriers and moving forward. We wish them all the best as they define the voice AI space.

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When AWS announced Elastic VMware Service (EVS), the launch narrative was all about cost and control. But the more I dug in — talking to VMware practitioners, IT decision makers, and even a former VMC SRE — the more I realized: This isn’t just a new AWS service. It’s a move in Broadcom’s VCF-everywhere strategy — and a signal that the “vendor-managed comfort zone” for many VMware customers is ending. In my latest post, I cover: - The 3 EVS Personas — who this service is really for - AWS’s checkbox strategy — why they had to offer it - The VxRail parallel — why this feels like déjà vu for Dell customers - The SRE reality check — what happens when AWS hardware fails at scale - The real decision — inherit the lift of running VCF yourself, or choose your hyperscaler If you run mission-critical VMware workloads, this isn’t just news — it’s your next architecture decision. https://lnkd.in/gpsSm-Pg

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History has a pattern most people ignore. When two brothers commit to one mission, outsized things tend to happen. These two just put India on the global AI product map. Mukund Jha and Madhav Jha didn’t start Emergent to “democratize coding.” They started it because app building was fundamentally broken. Especially for people building real businesses, not weekend side projects. Most people think building apps is hard because they’re non-technical. That’s a convenient myth. The real problem is the process. Too many tools. Too many handoffs. Too many systems that work fine until real users show up. And that’s exactly when founders can’t afford failure. So instead of hype decks and loud launches, these two brothers did something rare. They went quiet. No buzz. No flashy demos. No “AI will change everything” noise. Just months of grinding through the system, removing friction where it actually breaks. What came out of that effort became Emergent. Now here’s the part that should make you pause 👇 In just 7 months: 5M+ builders 6M+ real apps powered $50M ARR Users across 190 countries That kind of growth doesn’t come from hype. It comes from reliability. Which is why serious investors noticed. Early backing from Google AI Futures Fund, Gossamer Ventures, and SoftBank, followed by a $70M Series B. Not because it sounded exciting. But because it didn’t break when real users arrived. While most AI app builders stop at prototypes, Emergent goes end-to-end: Backend. Frontend. Database. Cloud. Payments. Deployment. Production-ready from day one. So what does this mean for the Indian Tech & IT landscape? This is the real shift 👇 1️⃣ India moves from services to software leverage When app creation becomes this fast and reliable, Indian founders can own products and IP, not just deliver projects. 2️⃣ Pressure on traditional IT models Billing hours and large dev teams won’t disappear overnight, but their dominance will shrink. Outcome-driven software beats manpower-driven software. 3️⃣ Faster startup cycles Founders no longer wait months to validate ideas. They can go from idea → production → users in days, not quarters. 4️⃣ Talent expectations will change The new edge won’t be “knows React or Java.” It’ll be: can you design systems, workflows, and outcomes? 5️⃣ India becomes a serious global builder, not just an executor Tools like this quietly shift India’s role from “cost-efficient tech” → product-first innovation hub. This isn’t just a startup success story. It’s a signal. Software is shifting from: "writing code to describing outcomes" And the teams that win won’t be the loudest. They’ll be the ones whose products don’t fail at scale. 👇 Let’s open this up Do you think tools like Emergent will disrupt Indian IT services or force them to reinvent themselves faster than ever? #IndianTech #IndiaAI #ArtificialIntelligence #AIProducts #StartupIndia #ProductManagement #ProductManager #ProductStrategy #AIInProduct #TechLeadership

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CXQuest.com examines why the expansion of Palo Alto Networks in Bengaluru is more than office growth. It is a strategic CX and EX play. The global cybersecurity leader has added 500+ seats across two floors. The facility includes advanced training rooms, collaboration zones, and a 450-seat town hall. The move strengthens India’s role in its global cybersecurity and AI roadmap. Anand Oswal, Executive Vice President, Products – NetSec at Palo Alto Networks, officiated the inauguration. The message was clear: innovation capacity must scale with risk. Kunal Ruvala, Senior Vice President and General Manager - India, Palo Alto Networks, stated: “India continues to play a critical role in innovating and delivering on our global product roadmap, and this expansion strengthens our contribution to India’s growing digital economy and the development of world-class technology talent.” Ranjith K P, Senior Director, People Team Business Partner - India, Palo Alto Networks, added: “Our new workspace is designed to support team growth at scale, enhance the employee experience, and enable the next phase of hiring and job creation in India. Purpose-built for learning and collaboration, it features flexible townhall areas, state-of-the-art training rooms, and recreational spaces that foster connection and support a growing workforce.” Three strategic implications. 1. Security Is Customer Experience. Digital trust defines brand perception. Cyber resilience protects journey continuity. 2. Employee Experience Drives Innovation Speed. Training infrastructure accelerates AI capability. Skilled teams reduce customer-impacting incidents. 3. Collaboration Reduces Journey Fragmentation. Purpose-built spaces shrink silos. Faster alignment improves resolution times. This expansion reflects a larger shift. Infrastructure now anchors CX strategy. AI ambition demands talent density. Trust requires ecosystem thinking. For CX and EX leaders: Are your security and CX teams aligned? Does your AI roadmap include workforce acceleration? Can your infrastructure support rapid innovation cycles? Office space alone does not transform experience, intentional design does. If collaboration, training, and hiring align, customer resilience improves. Key Takeaways for Leaders: Treat cybersecurity as a front-stage CX priority. Invest in skill acceleration tied to journey KPIs. Create cross-functional forums for journey accountability. Align regional talent strategy with global AI goals. https://lnkd.in/gVZbjQND #CXLeadership #CustomerExperience #EmployeeExperience #Cybersecurity #DigitalTransformation #AIInnovation #JourneyOrchestration #TrustEconomy #ExperienceStrategy

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At the Bharat Bodhan AI Conclave at IndiaAI Summit 2026, one message stood out: AI in education is now a national responsibility. The shift is real: From experimentation → to execution. From features → to frameworks. From access → to accountability. As AI enters classrooms, we must ask: Will it replace thinking, or strengthen it? At Navneet Education Limited & NAVNEET TOPTECH, our stance is clear. We are building responsible, accessible and scalable AI for both Teachers and Students with #NavneetAI and upcoming initiatives: • AI that empowers teachers; not overwhelms them. • AI for students that preserves cognitive and analytical depth; not shortcuts it. • Capacity building for teachers and AI literacy for students; because awareness must precede automation. The AI decade in Indian education has begun. We intend to shape it.. thoughtfully! #IndiaAI #BharatBodhan #NavneetAI #AIinEducation #EdTech #IndiaAI2026

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Perplexity is Quietly Winning India, While OpenAI and Gemini Play Catch-Up The numbers don’t lie: While the AI world discusses global domination, something fascinating is happening in India, and it’s reshaping the entire competitive landscape. Perplexity’s India Masterclass: 
✅ 640% year-over-year user growth in Q2 2025, outpacing ChatGPT’s 350% 
✅ India became their largest market by monthly active users, surpassing even the US 
✅ 360 million Airtel users now get free Perplexity Pro (worth ₹17,000/year) 
✅ Real-time Indian stock market data with live earnings transcripts, features a rival's paywall 
✅ 9% market share in India’s AI chatbot space, while Gemini struggles at just 2.3% Where Others Stumble, Perplexity Thrives: - OpenAI’s Response: Just launched ChatGPT Go at ₹399/month, but only after Perplexity gained massive traction - Google’s Challenge: Despite deep Android integration, Gemini holds merely 1.85% mobile market share vs Perplexity’s 2.75% The Secret Sauce: While competitors build for the West and adapt for India, Perplexity built with India from day one. CEO Aravind Srinivas (an IIT Madras alumnus) personally invested $1 million and commits 5 hours weekly to Indian AI development. The company offers: • Free financial data that costs thousands elsewhere • Strategic telecom partnerships over expensive marketing • India-specific pricing strategies planned • Multi-language support tailored for regional needs The Bigger Picture: This isn’t just about market share. Perplexity cracked the code on trust, accessibility, and relevance, the holy trinity for emerging markets. While OpenAI chases enterprise contracts and Google relies on ecosystem lock-in, Perplexity chose collaboration and community-driven growth. The result? India isn’t just adopting Perplexity; it’s becoming the blueprint for how AI tools should integrate into everyday life globally. The next chapter of AI leadership isn’t being written in Silicon Valley boardrooms. It’s being shaped by 1.4 billion Indians who’ve found their AI companion of choice. Question for the community: Are we witnessing the birth of a new AI distribution playbook where emerging markets lead, rather than follow? What do you think about this India-first AI strategy? #AI #India #Perplexity #ChatGPT #TechStrategy #Innovation #ArtificialIntelligence #TechLeadership

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Sam Altman calling “Code Red” didn’t just stir the AI world. It exposed how fragile even the biggest players really are. We have been here before. Google rushed with Bard a few years ago, and the launch revealed major cracks in the deployment. Today, OpenAI is facing a different kind of challenge not technical, but structural. OpenAI has the early-mover advantage. It captured global attention, set the benchmark, dominated mindshare. But with scale comes something most founders underestimate: cost gravity. Training frontier models isn’t just expensive but also unpredictable. From GPUs to R&D cycles, OpenAI is burning capital at a pace that only a handful of companies in the world can sustain. And without a stable revenue model, burn eventually becomes a bottleneck. Google’s position is different. They have: • In-house TPUs (far cheaper than buying GPUs at scale) • Existing cash-generating businesses • An integrated ecosystem for distribution • Billions of users already inside their products This gives Gemini a long-term economic advantage, even if they weren’t first. What founders can actually learn from this: OpenAI still does not have a predictable business model, while Google does. If OpenAI does not build a reliable revenue engine soon, it will run out of cash and struggle to maintain its infrastructure and operations. Google does not face that problem. It can reinvest continuously because its AI layer plugs directly into existing products like Search, Android, Workspace, Cloud and YouTube. For founders watching all this, you cannot ignore this difference. It shows that even the strongest technology needs a sustainable distribution system and a clear path to revenue. Without that, the cost of running AI becomes difficult to survive. Because the future of AI won’t be decided by who launches fastest. It’ll be decided by who can survive long enough. https://lnkd.in/ddCEkShB

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Talking about AI is easy. Doing it difficult. Getting returns from AI is more difficult. It needs the structural changes in education and industry. In addition it needs true adoption of AI, not just using gen AI for interactive search or vanity use cases. Focusing on core technology updates using is the real challenge. My friend Ram has captured our discussions in a nice post. it is just a beginning. Lets really use AI for progress.

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Traditional product development frameworks are proving insufficient to keep up with AI-native products and users who expect constant evolution, says TechArena Voice of Innovation Banani Mohapatra in her latest article. She digs into what she is calling the new product DNA – where AI, causality, and experimentation are wired into the product from the inside out. Instead of treating experiments as occasional side projects, leading teams are turning the entire lifecycle into a learning engine. --Ideation is powered by LLMs and copilots that spin up hypotheses, flows, and copy variants on demand. --Design taps AI tools that simulate user reactions and predict engagement before a pixel hits production. --Build bakes in feature flags, observability, and experiment scaffolding so every release is testable by design. --Launch isn’t about “Did metrics move?” but “Did this feature actually cause the change we see?” --Learning is automated by agentic AI that summarizes results, spots patterns across experiments, and proposes what to test next. Banani grounds this in a real-world example from digital health, showing how an AI-powered experimentation loop can steadily improve daily engagement and treatment adherence for chronic conditions. Check it out: https://lnkd.in/gBv6U-az

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The most interesting thing about DLF's ₹5,590 crore sellout wasn't the speed. It was who bought. 47% were under 35. Tech founders, not legacy families. And they weren't buying homes, they were buying clusters. Three, four units at once. One for living, others for their core team. The old Gurugram buyer wanted to tell people they lived near the Oberoi. These new buyers? They just want to walk to work and reach their jets fast. So DLF Limited's entire strategy is shifting. Their next launch won't have advertisements or a sales office. It's invitation-only, near Aerocity. Because when your buyers value time over heritage, you stop selling prestige and start selling proximity. I'm seeing this pattern everywhere. That Brisbane mansion with the Ferrari mural that went viral? Bought by a 32-year-old crypto founder who never even visited. In watches, buyers under 40 are driving 69% of growth above $30k. They don't care about waiting lists or heritage stories. The entire luxury playbook is being rewritten by buyers who made their money in months, not generations. And most sellers haven't noticed yet. Gurugram went from ₹1,800 to ₹180,000 per sq ft in 25 years. The next multiplication will take 5. Because speed is the new luxury. Everything else is just nostalgia.

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Musings# From Radio Licenses to Responsible AI: Why Soft Laws Make Loud Noise and Little Progress I studied in Sainik School Kazhakootam a residential school from 6th to 12th grade, designed to feed the officer cadre pipeline for the Indian Defense Forces. (No, I never made the cut.) Every night at 9:00 PM, we tuned in to Doordarshan’s English news read by legends like Rini Simon-Khanna, Salma Sultan, or Gitanjali Iyer ; wrote it down, and validated it with the next morning’s newspaper. One student, “the chosen one,” then read it aloud to the entire school. Yes. I grew up on a steady diet of news and newspapers. Then came the 2010s. I quit newspapers and moved to Twitter (now X). But lately, the noise there has become deafening. So, I shifted to LinkedIn only to find a different kind of noise. Every post here seems to be about AI, and frankly, it’s driving me insane. There are two kinds of “AI experts” on LinkedIn today: (a) Those who’ve once touched code now talk in fluent AI jargon, like LLM, RAG, tokenization, and fine-tuning. (b) Those who haven’t, brushed their profiles with soft laws frameworks, principles, and lofty words like fairness, bias, hallucinations, responsibility, and trustworthiness. The second category fascinates me more. My fundamental objection? The terms they use are vague by design, crafted for PR value rather than legal accountability. They let organizations 'sound' responsible while interpreting “compliance” on their own terms. Soft law mechanisms let firms signal virtue without structural change. But swinging to the other extreme of “heavy, rigid regulation” isn’t the answer either. Unplanned hard regulation can produce strange consequences. Take the US. highways: unlike Europe, they’re flooded with SUVs, thanks to a well-intentioned Obama-era IRS tax tweak that made large vehicles financially attractive. The lesson is simple: soft laws make noise; hard laws can suffocate. What we need is clarity and balance. SHAJI P JACOB IRS, ANINDYA SIRCAR - Our next book focuses on what truly matters in AI Governance: I. Ownership and Intellectual Property Rights II. Privacy and Data Residency III. Accountability and Liability IV. AI Sovereignty and Fair Taxation PS: Example of how “irrelevant hard laws” can hurt development! From the 1920s through the 1980s, owning a radio in India required an annual Broadcast Receiver's License (BRL). The administrative burden and fear of penalties limited access and slowed radio’s growth for decades. (Below is my Dad’s original BRL for his first radio in 1971. His proud badge of compliance in a world of unnecessary paperwork!)

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Introducing the Complete AI Transformation Framework for Schools After 9 months of intensive research with school owners, principals, teachers, students, and parents across India, we've identified the critical gaps in AI adoption at educational institutions—and built solutions to bridge them. Proud to present AI Ready School's three core offerings to making schools truly AI-ready: NEO - AI Innovation Lab Going beyond consumption to creation. NEO empowers students to learn, experiment, build, and contribute to open-source AI projects. We're not just preparing students for an AI future—we're enabling them to shape it. This is where India's next generation of AI innovators will emerge. Morpheus - AI-Powered Teaching Agent Liberation for educators. Morpheus transforms teaching through semi-automated content creation, intelligent personalization, seamless delivery, adaptive assessments, and actionable analytics. Teachers can finally focus on what they do best—inspiring and mentoring students. Matrix - AI Infrastructure for Schools The foundation that makes it all possible. Matrix provides secure, local AI infrastructure, private cloud solutions, and an AI orchestration layer that integrates with existing CRM, ERP, and CCTV systems. Complete data privacy. Complete control. Why this matters: India has the potential to become the global powerhouse of AI talent. But this transformation starts in our classrooms—with the right tools, infrastructure, and vision. Yes, we're huge fans of The Matrix film! Like the film showed us a world of infinite possibilities, we're helping schools unlock the infinite potential of AI in education. Ready to transform your school into an AI innovation hub? 📞 9100013885 📧 sales@aireadyschool.com Let's build the future of education, together. #AIinEducation #EdTech #AIReadySchool #FutureOfLearning #IndianEducation #AIInnovation #DigitalTransformation #EducationTechnology #SchoolInnovation #TheMatrix

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6 Languages. 1 Ad. Limitless Possibilities. We just reimagined a classic Coke Ad — But this time, powered entirely by AI. AI Voice Cloning Multilingual Translation Smart Lip Syncing Real-Time Localization From English to Tamil, Hindi, Telugu, Kannada, and Malayalam — Every word, every emotion, every frame — feels native. Why? Because your brand doesn't just need to speak. It needs to connect. 🧩 What this unlocks: ✅ Hyper-personalized video marketing ✅ Regional campaigns without regional teams ✅ Cost-efficiency with zero compromise on quality ✅ 6X market expansion without 6X effort No more: ⛔ Voiceovers ⛔ Manual translations ⛔ Long timelines Just AI + creativity — working in harmony. 📌 If you're building a 2025-ready brand — this is your edge. Your audience is multilingual. Your content should be too. 💬 Ready to unlock your brand in every language? Comment UNLOCK or DM me for a live demo. #AIxBranding #VoiceAI #CokeAd #LuxuryMarketing #CreativeTech #AIDriven #MultilingualMarketing #ContentLocalization #FutureOfAds #AIIndia #BrandInnovation #NextGenMarketing

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#AI #governance #framework is crucial for guiding #responsible AI #development and use, mitigating risks like #bias, #privacy #breaches, and #security #threats, #ensuring #ethical #alignment (#fairness, #transparency, #accountability), building public #trust, and ensuring #regulatory #compliance, all while balancing #innovation with societal #safety and #human #rights. It provides structure to manage AI's inherent complexities and potential harms, fostering #trustworthy AI systems that benefit #society. #better #future #safe #india

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India’s startup journey is entering its most important phase execution with intent. Time is ticking. As India builds digital public infrastructure at scale, we must also return to something fundamental: we-commerce systems designed around real people, real institutions, and real work, not just invisible automation and outcome dashboards. Startup India gave us momentum. DPIIT gave us structure. NEP gave us vision. Now the challenge is alignment at the ground level. Too often, we digitized processes without strengthening ownership. We measured outcomes without investing in how learning, work, and value creation actually happen. In education, NEP reminds us that learning is experiential, multidisciplinary, and skill-driven not transactional. In startups, DPIIT’s vision demands innovation that creates employment, capability, and resilience not just valuation. In policy, Startup India’s success depends on founders staying close to process, not abstracting it away. This is not about slowing down technology. It’s about designing it responsibly for India. The next generation of Indian startups must: Build human-in-the-loop systems aligned with NEP’s learning-by-doing philosophy. Create tools that empower teachers, shop owners, operators, and MSMEs Scale trust, skills, and participation, not just automation. Policy works best when it strengthens the builder not when it replaces them. India doesn’t need copied playbooks. India needs process-aware innovation, rooted in local context and national priorities. If we get this right, India won’t just produce startups. it will produce institutions that last. #StartupIndia #DPIIT #NEP2020 #IndiaStartups #EducationReformIndia #HumanCenteredTech #AtmanirbharBharat #FounderPerspective #PolicyAndInnovation #BuildForIndia #FutureOfWorkIndia

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What if AI could unveil the secrets to crafting a blockbuster movie? Creating successful films is not just about luck. Experts have analyzed 1,327 stories and identified six key emotional paths that lead to hits. Notable Indian films like Dangal (2,200 crore), Baahubali 2 (1,810 crore), and Pushpa 2 (1,800 crore) exemplify these paths. The hero's journey remains a timeless narrative that resonates deeply with audiences. Successful films typically feature a relatable hero, a significant goal, unexpected twists, and challenging decisions. Here are the secrets in detail: - Strong hero's journey: The hero starts in a normal setting, receives a call to adventure, faces tests, undergoes internal transformation, and ultimately achieves a significant victory. - Emotional pressure: The hero is consistently in peril, with stakes involving family or personal well-being. - Many surprises: Incorporate 7 to 10 major twists that alter the course of the story. - Real feelings in a big world: Present a relatable character amidst thrilling action. - Big scale: The personal conflict escalates to a level that impacts many. - Cultural touch: Integrate themes like justice or family that resonate with audiences. - Smart star: Feature a charismatic actor, akin to Aamir or Prabhas. - No boring middle: Ensure every scene heightens the tension and stakes. Combining these elements can create the magic that captivates audiences and leads to box office success. #movie #ai #secrets #jobs #hiring #fun #analysis #youtube Movie Facts, Inc. Movie Maniacs

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The Persuasive Power of Nondidactic Moral Art in India: How Refusal to Instruct Becomes Ethical Argument This book argues that one of the most persuasive forms of moral art in India is art that refuses to instruct—that refuses moralizing, sermonizing, or direct ethical prescriptions— and instead enacts moral persuasion through ambiguity, dissonance, affective experience, and ethical complexity. Grounded in interdisciplinary theory spanning aesthetics, moral philosophy, postcolonial studies, and cultural sociology, close readings of cinema, literature, theatre, visual art, and new media across modern and contemporary India demonstrate how non-didactic strategies produce deeper ethical engagement and public moral imagination than overtly instructive works. Through microhistories, audience reception studies, archival research, and textual and visual analysis, the book maps mechanisms including perspectival multiplicity, narrative indeterminacy, affective contradiction, and formal rupture, situating them within historical contexts: colonial schooling of moral didacticism, anticolonial moral pedagogy, Nehruvian nation-building narratives, and contemporary globalized publics. The book advances a theoretical framework—the "refusal model" of moral persuasion— and offers methodological tools for measuring persuasiveness beyond explicit ministrations: longitudinal reception analysis, policy traces, intertextual contagion, and civic repertoires. Case studies encompass selected films across Indian and regional cinemas, canonical and marginal literary texts including novels, short fiction, and poetry, performance pieces from street theatre to contemporary stage, visual art installations, and viral digital interventions. The research interrogates normative claims about what moral art should do, proposing instead what art does: creates ethical attention, cultivates shared ambiguities, and enables ethical negotiation.  https://lnkd.in/dYvwWCzD

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