Asit Kumar

✨ Chet Kapoor ✨ is quite the Silicon Valley legend. Three-time founder and currently the CEO of DataStax his wisdom for founders is incredibly spot-on ✅ and timeless ⏰ ! In this most recent and probably best-ever episode of The Enterprise GTM podcast, Chet discusses what it takes to build enduring tech companies. Some 🎤 soundbites 🎤 from our conversation: 👩‍🏫 The quality of people influences the outcome of your startup the most. 🔥 You do not need smart people who sit around and pontificate. ☄ Momentum is everything. Never underestimate it. 🌟 Having complete clarity of thought at any given time is very important--who are you doing this for, and how will it change their lives? 🌈 One of the best ways to create a large company is to create a parade or join one. ☝ Know who you are. There's a high likelihood that the company will become more like who you are rather than who you want to be. 🛑 Don't make the mistake of hiring sales execs too soon. Be extra cautious about partnerships. 📣 Tune in to hear about what he has to say about AI startups getting started today, the future of the data layer, the evolving importance of data roles (data science, data engineering), and so much more! #devtool #founder #startup #data #ai https://lnkd.in/gW-58nvE

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It has been a while since I posted about GLIA Ecosystems I spent 30 years as a lead producer at a bunch of investment banks and boutiques. Successful at times (a couple of exits). Failure at others (a couple of closures). I was a first generation gamer and loved technology. I was an early adopter of Bloomberg back in the days when knowing more fast codes and what the latest product roll outs where made you smarter than the mass. This was back in the days when information was slow, prices were OTC for size, when risk capital was dominated by a handful of banks and when research had price impact. That has all gone away. The game has changed but still retail carries on thinking Trading Views and their ilk (25 mln users looking at charts and back tested technical strategies) can help. Charts, prices, news aggregation and price back testers are nowhere near to a competitive tool kit but it is all most platform users, and market participants, have access to! This at a time when Citadel, Renaissance and their cohort are using weapons of mass destruction to scalp the markets. Guess where all the money is being made? As Robinhood get paid for their “odd lot” order flow and Citadel ride roughshod over it. 90% of trading accounts lose money. 25% of US market flows are retail. 70% of the Western world is financially illiterate. Einstein, or someone close, said “Insanity is repeating the same thing over and over and expecting a different outcome”. That is every data platform user in the markets today, it is the vast bulk of institutional brokers (minus their flow); it is the market at large. We are making leap into the future - a place of differentiation - occupying a space intended to close the gap on the winners; light years (well a good 30 years) ahead of the mass utility offerings. A space where we hope financial success can live. A fund management game with a twist and $1 a day financial intelligence for the mass market. We look forward to sharing much more soon it has been a journey. At long last there is a realisation that mediocre systems breed mediocre outcomes. The future is intelligent; knowledge is curated, content is relevant, and users are at the centre of their digital universe. #learntoearn #joiningthedots #knowingtheknowable #knowledgetoact Peter Bentley Peter O' Toole Adam Toms Matt Barrett Mike Hammond Jon Chase Matthew Fletcher Aba Schubert Ricardo Santos Silva Alf Long Matthew Steiner Mark Gamble Noah Liot Marco Merighi Ameet Patel

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💥 𝐃𝐚𝐲 𝟏 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬 𝐟𝐫𝐨𝐦 TechCrunch 𝐃𝐢𝐬𝐫𝐮𝐩𝐭 💥 🌍 Vinod Khosla’𝐬 𝐎𝐩𝐭𝐢𝐦𝐢𝐬𝐭𝐢𝐜 𝐕𝐢𝐬𝐢𝐨𝐧 𝐟𝐨𝐫 𝐀𝐈  ➡️ AI has the potential to create great abundance, drive GDP growth, boost productivity, and even increase income equality. ➡️ The vision is ambitious but clear: AI can lead to an economic surplus that supports those impacted by technological change. 💡 𝐏𝐨𝐥𝐢𝐜𝐲 𝐚𝐧𝐝 𝐆𝐥𝐨𝐛𝐚𝐥 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 ➡️ There is a need for smart policy to manage AI’s impact, different countries will make choices on resource redistribution. ➡️ There is risks in geopolitics, specifically China as a critical player in the AI race. 🚀 𝐓𝐡𝐞 𝐑𝐨𝐥𝐞 𝐨𝐟 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫𝐬 ➡️ “𝘌𝘹𝘱𝘦𝘳𝘵𝘴 𝘦𝘹𝘵𝘳𝘢𝘱𝘰𝘭𝘢𝘵𝘦 𝘵𝘩𝘦 𝘱𝘢𝘴𝘵, 𝘣𝘶𝘵 𝘦𝘯𝘵𝘳𝘦𝘱𝘳𝘦𝘯𝘦𝘶𝘳𝘴 𝘪𝘯𝘷𝘦𝘯𝘵 𝘵𝘩𝘦 𝘧𝘶𝘵𝘶𝘳𝘦.” The best entrepreneurs build from 0 to 1. ➡️ Big innovations rarely come from large enterprises; instead, they’re driven by entrepreneurs with first-principles thinking, persistence, and a big vision. ➡️ The bigger the problem startups solve, the bigger the opportunities and impact they befriend. Those insights remind us that while AI’s path forward involves challenges, it’s also a time of unprecedented opportunity for those willing to build boldly. 💪 📖 𝐒𝐮𝐠𝐠𝐞𝐬𝐭𝐞𝐝 𝐫𝐞𝐚𝐝𝐢𝐧𝐠𝐬 𝐟𝐨𝐫 𝐚 𝐝𝐞𝐞𝐩𝐞𝐫 𝐝𝐢𝐯𝐞: ➡️ '𝘙𝘦𝘪𝘯𝘷𝘦𝘯𝘵𝘪𝘯𝘨 𝘚𝘰𝘤𝘪𝘦𝘵𝘢𝘭 𝘐𝘯𝘧𝘳𝘢𝘴𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦 𝘸𝘪𝘵𝘩 𝘛𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺' (2018) by Vinod Khosla (https://lnkd.in/g8mdExgH) ➡️ '𝘌𝘹𝘱𝘦𝘳𝘵 𝘗𝘰𝘭𝘪𝘵𝘪𝘤𝘢𝘭 𝘑𝘶𝘥𝘨𝘮𝘦𝘯𝘵: 𝘏𝘰𝘸 𝘎𝘰𝘰𝘥 𝘐𝘴 𝘐𝘵? 𝘏𝘰𝘸 𝘊𝘢𝘯 𝘞𝘦 𝘒𝘯𝘰𝘸?' by Philip E. Tetlock Thank you for very inspiring talk, Connie Loizos. #greatabundance #venturecapital #techcrunch #AI

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Nexus Conversations. Yes. This is an invite. Join us. Get to know what we talk about, what we are thinking, what we believe in. Conversations flow, akin to ideas leading to building products for the future. Nexus Conversations is where we at Nexus Venture Partners get together with builders & founders. Today, meet Thomas Li, Co-Founder at Daloopa, an AI platform disrupting the billion $ financial data market talking about critical mission products > hook products! Abhishek Sharma

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Sharing a sanitized version of the mu ventures Q2 q'ly LP update. Included musings: 👉 SEOs shrinking impact, and the rise of LLMO (large language model optimization) 👉 examples of the Commerce AI application layer coming to life 👉 a modern fund strategy that accepts companies require less capital, time, and people to trigger the power law 👉 Mu's guide to investing in AI 👉 all 30 companies in the Mu-niverse (and several others we admire) Founders, VCs, LPs - if you like how we think and suspect we can partner, hit us up! https://lnkd.in/dTJ2zjav

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Thanks to Steve Ispas for hosting me on the #bayareainnovators show for The Epoch Times—excerpts in the link below. This interview is about #innovation, #startups, #founders, #entrepreneurship, #venturecapital, #funding, #exits, #ecosystem, #accelerators, #failures, and #success! We delve into how Silicon Valley continues to be the global hub for technology and startup activity while spreading this phenomenon worldwide. We also explore the role of VCs in startup success, the three horizons and six degrees of innovation, reasons why startups may fail, and much more. Full interview here: https://lnkd.in/gZc2yfbm FYDA Venture Partners FYDA Growth Partners Network VC Techne Infiniti Ventures

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We are delighted to present the concluding installment based on our paper, "Vision 2035: The Emergent Singularity" (link in the comments). In this final section, we illuminate the three critical components that will prove instrumental for companies as they navigate the transformative landscape of machine intelligence: 1. The Role of Data: In the age of machine intelligence, data reigns supreme. As we navigate this data-rich landscape, challenges emerge in harnessing its full potential. The concept of "Big Data" evolves rapidly, demanding advancements in edge computing, natural language processing (NLP), and even quantum computing. Despite this growth, there's a growing reluctance to share data, hindering accessibility. Startups can serve as pivotal players, breaking down barriers and showcasing the value of innovative solutions. From technical to regulatory hurdles, the path to data accessibility is fraught with challenges, but also ripe with opportunities for venture-backed initiatives to lead the way. 2. Open-stack technologies: Rooted in openness across software, data, storage, and computation, open-stack technologies are analogous to open-source software in many ways. By embracing open-stack, companies transcend closed system limitations, fostering innovation and enabling agile, cost-effective development through collaborative ecosystems. Leveraging existing communities potentially reduces customer acquisition costs while cultivating dedicated user bases for lasting relationships. 3. Collective intelligence: Ecosystems built on shared, community, and aggregate knowledge offer prime opportunities for open-stack-centric machine intelligence startups. The emergent benefits from group knowledge can speed up product development and broaden customer reach. Collective intelligence approaches like federated learning can also streamline data processes, minimize data sharing while maintaining control and adaptability, enhance model accuracy, and mitigate technical and product risks across an ecosystem. We hope you have found our series of summary analysis on the realm of machine intelligence to be insightful. As highlighted in our longer vision paper, we are convinced that the value creation potential of winners in this space will amount to a remarkable two orders of magnitude (100x) compared to today's companies. Lastly, we may follow up with a little encore in two weeks. Keep your eyes peeled! Patrick & Sri Machine Ventures #singularity #machineintelligence #ai

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Startup decks vs Business plans. It's accepted that a startup needs a deck. Dax Dasilva of Lightspeed Commerce made an important point on 20VC. Writing a business plan - including financial projections - is an important step. It requires discipline. It provides a rigorous framework for thinking deeply about the problem you're trying to solve. Harry Stebbings countered that he doesn't even want to see a deck since it's all dreams. We spent a lot of time and energy on our business plan with the expectation that we would show it to no one ever. The business plan was part of our roadmap for the company. We researched customers - including having 50+ conversations. We wanted to understand them: their background, their interests, their presence on social media. We also wanted to understand how they were evaluated by leadership and how integrated they were with the business of the company they were protecting. We researched pricing both with potential customers and other products in our industry to find out if OpEx or CapEx was a better fit. How did they buy today? How would they like to buy? We did market research to understand the verticals and map the right entry point - we were wrong but that doesn't reduce the value of the research. We looked at competitors in depth to understand what they were seeing that we weren't. Dax is right. This is an invaluable document that should be updated every year - the company is changing, the market is changing, there's more feedback about price and ICP. It's not for sharing with the outside world. It's a map for driving forward. Decks won't get you investment - VCs invest in people. We make decks but we know they don't tell our story. The deck is a calling card. Dax and Harry are both right. https://lnkd.in/e25M82xY

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My latest investment is rooted in a profoundly unique insight in one of the world largest industries, and I could not be more excited about it. Meet Kashmir Intelligence. We’re leading a $5M round alongside our friends at Jigsaw VC, Tiny Supercomputer Investment Company, Material Ventures, firedrop and TrueSight Ventures. The ideal Stride.VC deal requires (a) a unique insight in (b) a fundamentally interesting market with (c) a scalable business model and (d) a team of founders who can reshape their industry and (e) intentionality. This opportunity delivers on of all of these. The downstream oil industry is what our world runs on. Optimising the performance and output of existing infrastructure is one of the most immediately impactful things we can do to address the climate crisis. Additionally, delivering effective infrastructure in the face of the Russia crisis is a geopolitical imperative of profound importance. Oil refineries have a major data problem - they run millions of miles of pipes generating terabytes of sensor data they cannot move to the cloud, and their inability to harness this intelligence is hurting their efficiency. Enter Orbital - an edge infrastructure AI layer that delivers cloud-beating deep learning capabilities into downstream environments at a fraction of the cost, with none of the security risks. Founder Samyakh (Sam) Tukra stumbled upon this issue whilst building digital twins for refineries and immediately realised he'd come across a strategic issue plaguing heavy industrial environments in general and the oil industry in particular. Refineries are completely unique beasts with complex optimisation requirements in data-constrained, high security environments. Hence the solution here would require a complete different approach to deliver the predictive optimisation results that these companies need. Figuring out how to address this multi-faceted issue delivered the unique insight on which this company was born. Sam partnered up with repeat founder Callum Adamson and together they kickstarted Kashmir. Quite the duo. Callum and I share a habit of meditating on our own death and Sam is both charming and so talented I'm not even sure he's really human; the chemistry between all of us was excellent from the word "go". The company is emerging from stealth with real world performance underway at ExxonMobil / Gruppo API and ABB/ICL facilities and are excited to formally launch Orbital at Global Refining & Petrochemicals Congress 2024 in Delhi on the 27th of June as part of their Indian market focus. I'm excited to be part of this important company's journey as we strive to make industry more efficient. Big Data needs a sharp Edge, and we’re looking forward to showing you what Orbital can do. Thank you Pietro Invernizzi for the intro and assist! Onward. https://lnkd.in/eWJmft2w

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Hosted a curated group of NYC AI builders for dinner tonight, incl. founding ICs at Modal, Captions, Replit; founding GTM at Together AI, Databricks Mosaic Research; researchers at Google DeepMind, Harvey, GitHub; product leaders at Anduril Industries, OpenAI, Google DeepMind, Zapier; and founders from South Park Commons We talked about things like the human brain, the foundation model battle, re-imagining AI interfaces, future of consumer AI, super intelligence, AI's role in education, and self-driving cars. As usual, we asked each guest their AI hot take and predictions: 🤠 - OpenAI & other foundation models do not deserve their hefty valuations - a 6-month advantage over open-sourced models like Llama is not a sustainable value driver 🐻 >guest pushback: OpenAI will be a consumer business long term, and the future products layered on top will drive real value 🔮 - Most of the consumer AI as we know today is single-player - there’s tremendous potential in multi-player consumer AI 🤼 - Ads monetization will create perverse incentives for foundation model providers —> user experience with free models will worsen 🙃 - Super intelligence is overhyped, as every physical system has a limit (e.g., speed of light) ☄ >guest pushback: a 10% b2b productivity gain is still a massive value-add 🉐 - There’s nothing magical about the human brain - difficulty comes from learning how to control it with consistency, same logic with AI models for video generation 🧠 - The current AI ecosystem moves too quickly and cares too much about creating fancy product demos - instead, we should re-anchor around solving real user problems 🏃‍♀️ - Building very specific AI models that tackle very specific tasks is the future of AI 👩‍🏫 - The chat interface as UI/UX layer is extremely lazy 🐨 - As we approach AGI, Washington will feel pressured and incentivized to do what they didn’t do with social media to mitigate issues like fraud, lack of safety, etc. 🚨 - We should be losing our minds about self-driving cars instead of gen AI, which isn’t even that cool 🚙 >guest pushback: AI is more like a space race, not a bubble - GPS is now ubiquitous as a result of heavy investments in space; similarly, investing in AI will enable better self-driving cars 🛰 cc: Gopal Raman, John Bryson

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🔍 MVP Research Spotlight: Cutting-Edge Tech Innovators Santosh Rao has just released his latest batch of Quick Take reports, highlighting three groundbreaking companies reshaping their respective industries. Let's dive in: 1. 🧠 Glean (Est. 2019) • Leading enterprise AI search and knowledge management • Transforming legacy enterprise software with AI-powered solutions • Backed by Lightspeed, Citi Ventures, Coatue, Sequoia Capital 2. 🚗 Applied Intuition (Est. 2017) • Advanced simulation for autonomous mobility • Platform-agnostic, commercially proven, government-validated • Investors include Lux Capital, Andreessen Horowitz, Bond, General Catalyst 3. 🔋 Form Energy (Est. 2017) • Pioneering iron-air batteries for grid-scale energy storage • Cost-effective alternative to lithium-ion batteries • Offers significant advantages in storage duration These Quick Take reports provide valuable insights into companies at the forefront of AI, autonomous technology, and sustainable energy. At Manhattan Venture Partners, we're excited by the potential these innovations hold for reshaping industries and driving future growth. Dive deeper into these game-changing companies. 🔗: https://lnkd.in/eJKKeAht #TechInnovation #AITech #AutonomousMobility #CleanEnergy #VentureCapital #MVPAllStarFund #TechInnovation #preipo #siliconvalley #unicorn #MVPALLSTARFUND #mvpvc #mvp #therealmvpvc #venturebytes #allstar #ipo #research #technology #tommorowsipostoday #SecondaryAsAService #saas #SecondariesAsAService

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For those of you still doubting Artificial Intelligence....wake the f$%& up!!! Go walk around downtown San Francisco and maybe all of Google's Waymo driverless cars on the streets may be a wake up call for you. If you need more proof take a look at Y Combinator's current cohort of companies as well as all the AI and AI-Enabled companies in the MedTech Innovator current cohort of companies or the ones pitching at LSI and LSI Europe!

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AI is reshaping how enterprise software delivers—and prices—value. Companies like Zendesk, Intercom, and Forethought are shifting to outcome-based pricing, charging only when AI autonomously resolves issues. I've been investing in AI for over a decade. The shift to outcome-based pricing in enterprise software is a seismic change. As I told Jon Victor at The Information, software companies now face a critical decision: Does a company decide to change business models at the expense of losing revenue? It's a necessary risk. With cheap access to LLMs, businesses can build their own enterprise apps. Adapt or die. Why this pricing shift matters: → Vendor success ties directly to customer outcomes → Short-term revenue risks enable long-term market expansion → Industry faces widespread pressure to demonstrate measurable value Pitching AI-powered automation software as a clear cost-reduction tool could ultimately lead to greater revenue for vendors. This is because customers may view AI solutions as fundamentally different from traditional enterprise apps, whose business value is often harder to quantify directly. It's a huge market expansion opportunity. Vendors that nail outcome-based pricing could see massive growth as AI transforms enterprise operations. Those that don't? 😬🫣 How do you see this impacting sectors beyond customer support? Leave a comment. And if you're building in this space, send me a message.

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Are you starting or just starting an AI-first startup? If so, please consider attending this session this Saturday (May 25th, at 11 a.m.). What we would be discussing: 1. Understand what makes a great founder for an AI startup. 2. Why start now? Why is this a massive opportunity? 3. What type of use cases in what markets make sense? Please see below the details for registration.

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Great Insights from Vinod Khosla's Talk on Investor Value: 🔸 90% of Investors add No value, and 70% actually add negative value. Real value comes from experience, not credentials. 1. Simply having an MBA or working at a venture firm doesn’t qualify someone to guide entrepreneurs. 2. Those who haven't built a large company or gone through the uncertainties and traumas of entrepreneurship are often unqualified to advise. 3. If you’ve never been in the trenches making tough trade-offs, you can’t effectively help an entrepreneur. 🔸 Pick investors who can help – not those just with experience in stability. 4. Investors who are comfortable with uncertainty and first-principles thinking. 5. Look for investors who prioritize learning and adaptability over rigid experience. 6. Do not choose an investor who only understands incremental change, not disruptive innovation. Khosla’s Final Advice to Entrepreneurs: 7. Don’t Overvalue Experience: Just because someone has worked in a big company or has a prestigious title doesn’t mean they’re equipped to handle the fast-moving, unpredictable nature of startups. 8. Look for Problem Solvers: Investors who can deconstruct challenges to their fundamental components and find creative solutions are more valuable than those offering "tried and tested" advice that doesn’t fit your unique situation. 9. Adaptability Over Stability: The best investors will challenge your thinking, help you discover new approaches, and aren’t afraid of making bold decisions—just like you need to be as an entrepreneur. Apply first principles when choosing. Choose wisely!! https://lnkd.in/gV6rG6NJ #FirstPrinciplesThinking #Entrepreneurship#StartupAdvice #InvestorInsights #LearningOverExperience #BoldDecisions

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Product-market-fit (PMF) is achieved when a product addresses an existing need or generates new demand, thereby establishing its position in the market. “Rather than diagnosing whether you have product-market fit, this framework outlines three distinct archetypes of PMF which help you understand your product’s place in the market and determine how your company operates.” This framework created by Sequoia Capital is an absolute must-read for founders to self-identify the path that their company is on.

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