Manik Gupta

We are excited to back Morphing Machines. As Dr. Ranjani, CTO and co-founder says: “For the first time in India and globally, we have a processor that is truly runtime reconfigurable, catering to emerging workloads.” While Nvidia’s growth and high valuation are driven by robust demand for “infra-compute” in high-performance GPUs, spurred by Gen AI, there is a distinct need for innovative solutions tailored to a new wave of reactive applications. Enter Morphing Machines. It addresses this demand with its unique product designed for next-gen telecom, autonomous vehicles, collaborative robots, avionics, and online data analytics. This product is specifically engineered to handle heterogeneous workloads and diverse tasks with varying performance demands simultaneously, ensuring a high level of scalability. As we move from an institutionally-backed research team at IISC to productization, Golden Sparrow is collaborating with Speciale Invest and others to support Deepak Shapeti, who joined as CEO three years ago after earning his Masters at Stanford. He brings not only technical expertise but also the business acumen necessary to guide the product to commercial success. Venkat Raju Afreed Faizan Anand Rao Ritik Singh Michael Marmor

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Someone has to say it - if creating an D2C shopping experience isn’t top of mind, your growth potential is at risk. Ravi Kurani gets it. He learned this concept by launching Sutro, a sleek testing robot that monitors your pool or spa water, giving you instant status right to your smartphone. Right now, they complete 95% of their business DTC through Shopify, but are actively working on equipping retailers with their software in-house. This way, consumers can bring pool samples directly to the experts for further testing and full visibility. The lesson here? Once you’ve found your lane in one channel, don’t stop. Taking this a step further, he also mentioned they are looking to find ways to integrate their data with home automation platforms. Always ahead, he likes to continuously figure out how to work with the interfaces of today AND tomorrow. While not every plan will pan out, that’s not the point. His final words of wisdom were this, “Perfection is the enemy of progress.” Be open to new opportunities, and don’t be afraid to flop at first - it will make you, and your product better. To me, that’s the difference between smart growth and stagnancy.  Tune in: https://lnkd.in/e5Bn35zW

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How does Uber Eats delivery work? Check out my discussion with Kishore Gopalakrishna, Co-Founder and Chinmay Soman, Head of Product from StarTree on The Ravit Show, We delved into the development of Apache Pinot, recent enhancements, and what the future holds for real-time analytics. Also, great announcements made at the RTA Summit. - Commitment to Developers: StarTree's new 'Free Forever' tier - with a 500 GB storage offer through Friday, May 10th, is set to revolutionize how developers engage with real-time analytics, offering unrestricted access to their platform without the stress of time-limited trials — https://lnkd.in/dZdDp73h - Vector Index Support: Enhancing Apache Pinot with new capabilities for AI-related use cases, such as Generative AI (GenAI) Integration, Chatbots, and Recommendation Systems. ​StarTree ThirdEye General Availability: An advanced real-time metrics monitoring, anomaly detection, and root-cause analysis tool designed to increase operational excellence across industries. Tune in to gain valuable insights and participate in the discussion. Full episode in comments! #data #ai #startree #theravitshow

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Sanjay Jha is moderating an intriguing panel discussion at GSA (Global Semiconductor Alliance ) executive forum now Rene Haas : insatiable demand driven by AI speed up our roadmap. Software does not die, AI is an additional demands for hardware. Life science and drug development will be the next big thing. Anirudh Devgan : AI is in the phase 1 of infrastructure and phase 2 of AI in existing application, 3rd phase is AI new application. Cadence is engaging phase 1 by enabling AI Chips, and phase 2 which drive design automation. 3DIC is natural extension of Moore's law. Optimistic about power, as new Innovation along the way will bend the straight line projection usually seen in the early inning of technology like AI. Real value realization will mostly be vertical based, not the horizontal LLM. AI will move from infrastructure AI, physical AI(automotive, robotics) to the horizon 3, that is likely AI biggest apps such as AI for science, particularly life science Sandra Rivera : AI impact is multi facets. First it is a TAM expansion for FPGA, which is needed as co-accelerator. AI is also embedded in placement tool and in even in basic fabrics, which will be making FPGA better. Power is the single Largest limiter for AI deployment. Also, Should AI be better regulated than what happened in social media, leading to the data security and privacy. Tien Wu : AI has driven ASE to increase capex to 4B This year from 2B last year due to systematic complexity, not just technology but the more players in ecosystem, which breaks the traditional pricing. AI has made us seeing the first time that Hardware is the bottleneck in term of improvement and return in profit. US has the data and economic scale to deploy AI across all sectors in term of efficiency improvement, given US also has been a highly "wasteful" nation.

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How does Uber Eats delivery work? Check out my discussion with Kishore Gopalakrishna, Co-Founder and Chinmay Soman, Head of Product from StarTree on The Ravit Show. We delved into the development of Apache Pinot, recent enhancements, and what the future holds for real-time analytics. Also, great announcements made at the RTA Summit. - Vector Index Support: Enhancing Apache Pinot with new capabilities for AI-related use cases, such as Generative AI (GenAI) Integration, Chatbots, and Recommendation Systems. ​StarTree ThirdEye General Availability: An advanced real-time metrics monitoring, anomaly detection, and root-cause analysis tool designed to increase operational excellence across industries. Tune in to gain valuable insights and participate in the discussion. Full episode in comments! #data #ai #startree #theravitshow

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The Xoogler.co community is lucky to have incredible leaders like Shiva Rajaraman help community members grow. He's speaking on being a Product Manager to General Manager in 2 hours time. Xooglers/Googlers don't miss out on hearing from him! RSVP: https://lnkd.in/gGEJQUKc Shiva has held leadership roles (Google, YouTube, Spotify, OpenSea, and now Uber) where product has extended beyond designing and prioritizing app experiences and involves content or services to make the experience exceptional. Thus good deals, operational rigor, merchandising, and deep P&L understanding are critical skills and these only get more important in today’s leaner and growth/margin sensitive environment. PMs need to act more like GMs and he’ll walk through what worked in that shift as well as what pitfalls to avoid. #product #gm #xoogler

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For product-minded eng people out there, our call to action is simple. People Ops software shapes the experience of talented people (due to performance management, compensation, mobility, etc) to an extraordinary extent... Not to mention building something amazing for managers and leaders to run their teams better. What if we could build something as delightful as Linear to shape this experience?

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New Thesis - Beyond Language: An Introduction to The Transformational Potential of LxMs A core tenet of the new firm I am building is to generate sectoral theses in areas that I believe can lead to outlier returns. Over the years, I have been fascinated by novel foundational technology catalyzed by open ecosystems - and the impact they can have on areas beyond language. In this post, I introduce the concept of LxMs - a new thesis I am developing - and how they will impact various sectors. Follow along our series for in-depth insights and case studies on how LxMs are transforming various industries. We will explore how these advanced models are revolutionizing fields such as scientific intelligence (biology, chemistry), industrial intelligence (robotics, manufacturing) and gaming (design, engines, modeling, simulation). Read our intro and stay tuned for our subsequent posts. Huge props to Archit Gadhok for co-piloting this with me!

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Will we need websites at all? How can you compare the current AI boom with the age of oil exploration? What does it mean when we say in the world of AI, compute vs. data will have gravity? During the Antler India Residency 4 that concluded recently, we had our good friend Hemant Mohapatra stop by to chat with founders re: his and Lightspeed's take on AI, and especially AI for India, incl. one of their marquee investments Sarvam AI. Sharing our interaction w/ Ishavasyam Dash

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Interesting article on last mile delivery. This is one of those areas where the high level theory is super exciting, but low-level delivery network design and ruthless execution are *everything*. This led to a recent generation of failed attempts to build last mile delivery as startups. I don't hold out much hope that Shein and Temu will change that balance, only delay more failures. Is this an impossible area to build a startup in? No. But it's a problem where domain expertise has to meet capital, and a team has to be brilliant from a network design standpoint, combined with day-to-day operations chops. Those teams are super rare. https://lnkd.in/dgQjYZ_2

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Being a founder means being 100% in it, all the time, especially through the lows. It was fun to run down memory lane with Sequoia and discuss how DoorDash navigated moments of uncertainty to empower local commerce on a global scale. Check out the full episode here: https://lnkd.in/gxmx2nhy

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Marissa was involved in the development of more than 100 products and features for Google. Beyond Google Earth, she played a part in shaping Street View, Google News, and Gmail 👇 I'm starting a new series of posts. Dedicated to first product managers 🥇 Or what I call 'first PMs' 😉 And who better than Marissa Mayer to start this series? Marissa's role evolved from managing specific products. To oversee entire product lines 🔛 She eventually became Vice President of Google’s Search Products. A holy grail in the tech world! Let's dive in! _____ Marissa Mayer was one of Google’s first-ever employees. Employee number 20, to be precise. She joined Google in 1999 as the company’s first female engineer. You might remember when search engines filled their home pages with ads. News, weather reports, and other features. Marissa had other ideas... She decided to keep Google’s homepage as clean as possible 🧼 An approach that prioritized speed and ease of use. Marissa understood that people came to Google primarily to search 🔍 So she insisted that Google pare down the homepage. To make it as easy as possible for users to do just that:  This is how Google stood apart from its competitors 🏆 This minimalism established Google as the go-to search engine for millions. The stripped-back design allowed for faster loading times. While ensuring users could immediately understand exactly what Google was. If you’re looking for an underlying cause of Google’s rapid growth in popularity in the late 90s and early 00s, here it is. By 2005, Google had around 5,000 employees... And Marissa was overseeing the launch of Google Maps 🗺️ At the time, mapping services provided basic map views difficult to read 😣 She & her team decided to push for satellite imagery into Google Maps. Which would turn out to be a game-changer! Marissa understood satellite imagery provides a more detailed view. Yet more intuitive 👍 And that this would be much easier for users to understand. This decision meant investing significant resources. But it all paid off! It resulted in a visually engaging tool for navigation. Which helped set Google Maps apart from its competitors.  Insisting on simplicity in search 🔍 Each of these examples demonstrates Marissa’s commitment. Her commitment to user-centric design. And her willingness to take on immense technical challenges For the sake of improving the user experience. These are all qualities that Marissa had developed at Google. Which she retained even after spending years in the company 🔥 ____ This is the first PM mindset! And it’s a mindset that Google as a whole has embraced. Which has put the company at the forefront of technological innovation. Hope this story sparks a few ideas 😃 Enzo #firstpm #marissamayer

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🌏 𝗠𝗲𝘁𝗮'𝘀 𝗠𝗮𝗿𝗸𝗲𝘁 𝗠𝗼𝘃𝗲𝘀 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗘𝘃𝗼𝗹𝘃𝗶𝗻𝗴 𝗔𝗜 𝗟𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲 🌎 As a staunch supporter and investor in Meta, it’s disheartening to witness a 16% plunge in its stock despite the company surpassing first-quarter expectations. This stark drop, primarily driven by weaker-than-anticipated revenue guidance for the upcoming quarters, underscores the volatility and challenges within the tech sector. What’s particularly interesting—and concerning for some investors—is Meta's substantial investment in hardware through partnerships with companies like NVIDIA, which was pointed out by Chamath Palihapitiya in a recent discussion on the All-In Podcast. Meta may be overspending on NVIDIA's capabilities, which are traditionally strong in training but less so in inference, a critical component of AI efficiency and cost-effectiveness. This misallocation might not be fully appreciated by the market, contributing to the sharp decline in Meta's stock. Aligning with Chamath's critique, Andrew Ng's recent speech at Sequoia Capital emphasizes the growing importance of inference over training in AI development. He argues that the future of AI lies not just in processing vast datasets but in making smarter, iterative improvements through 'agentic workflows.' This approach mimics human-like reasoning and problem-solving, significantly enhancing AI's applicability and effectiveness across various sectors. The juxtaposition of Meta's current strategy with Andrew NG's vision presents a fascinating discourse on the strategic decisions tech giants must make. As investors and industry observers, it's crucial to assess not only the financial metrics but also the technological and strategic underpinnings of these companies. Are they investing in the right technologies for the future, or are they anchored to the past? This scenario serves as a critical lesson for venture capitalists and tech entrepreneurs alike. As we navigate the complexities of AI investments, understanding the distinction between mere computational power (training) and actionable intelligence (inference) will be key to identifying and leveraging the next wave of innovations in technology. Here are all my sources for the ones interested: Meta Earning release reviewed by CNBC: https://lnkd.in/ddGia5kK All-in Podcast clip on Chamath point of view on Meta: https://lnkd.in/dfs7JQG4 Andrew NG at Sequoia: https://lnkd.in/dqnvex2u #AI #VentureCapital #Meta #TechnologyTrends #Innovation #ArtificialIntelligence #NVIDIA #Groq #InvestmentStrategy

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I participated in a “SMART MANUFACTURING” panel with Gayathri Radhakrishnan, Rohini Chakravarthy and Abhijit Supekar (moderator) last week at TIECon 2024. The coolest part of the panel was 3 Women VCs talking about a topic that has not traditionally been discussed by women. I never imagined I’d see this in my lifetime. Things have indeed changed! We had a very lively discussion of whether we can expect lights out factory in 5-10 years. Automation is happening in all stages but full automation manufacturing is tough because it requires human like adaptability. It is not converting text into instruction or code - it is about precision. Robotics + AI is making this happen and we will get there. AI is going to bring the cost down for complete solution for example: there are robotic arms that can do more tasks and learn like a human and not just some specific tasks. Also check out our portfolio companies Micropsi Industries and RGo Robotics that are making it happen in this space. Thanks to Anshu Bahadur Hrishikesh Sathawane Nilesh Dixit for organizing the panel and Anita Manwani and Surbhi Kaul for making this happen! #TiECon2024 #AIUbiquity

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We are launching FreightIntel AI today. It's a tool that digests large sets of transportation data and creates actionable intelligence from that, allowing for chat-like interaction with the insights. It's a standalone product but it's also already natively integrated with our ShipperGuide TMS. You can see the 3-minute demo here. This tool is right for you if: - You are a large shipper with extensive logistics data that finds it difficult to find opportunities for optimization without month-long projects or extensive analyst resources - You run optimization or cost-saving projects only once a year and would like to be nimbler and find savings on an ongoing basis during the calendar year - You use a legacy TMS system with data reporting that contains too much noise and has an unfriendly UI, making it difficult to derive intelligence from raw data - You rely on a managed transportation or 3PL/4PL provider to handle your logistics and want to hold them accountable and ensure they are exploring all optimization opportunities - You have an M&A strategy that relies on identifying cost-savings opportunities of target companies and would like an easy and fast tool to execute this analysis - You are a CFO who is looking to understand potential optimization opportunities in your transportation budget to drive shareholder value Super proud of the Loadies who made this happen - huge effort!

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Great session James Newell and thanks for hosting Jon Prentice and SVB! In terms of the answers and perspective shared from Voyager Capital and James…. The Good (for Seattle investing and VCs) —— * the opportunity in Seattle (and the wider PNW / Cascadia region) that Voyager is still capitalizing on, is that there is a ton of potential in Seed to Series A investing that isn’t as accessible elsewhere. * SF and other markets are saturated and less engaged as investors at this stage. * talent pool here is massive, especially on the engineering and product side. What would be a “Game Changer” for Seattle —— * there is a talent shortage especially in terms of sales and marketers locally. * Few sales and marketers want to do $0 - $1M journey again if prior successful. * Angels are more private here, and may not feel the need to give back to the start up community if that isn’t how they made their wealth Outside of Seattle specific feedback: —— * Founders need to be doers, not “leaders of leaders” (an issue with those coming from big tech); talent need to meet the stage and act accordingly. * AI as a tool and business foundation is only important in terms of delivering business value. * AI powered firms need to show they have an ability to access proprietary data or be linked intimately to workflows or both to be a sound investment [this is established consensus among investors] * Investing, especially very early stage, should be run as a process. Be your own best BDR for fundraising. And finally …. The top 2 pieces of advice most often given to founders…. 1) Try to avoid VC capital to the degree you can [which means you have a capital efficient business]. 2) find a co-founder to complement your skills vs doing it all on your own.

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Join us for a conversation with Peggy Rayzis on building a "Developer Intent led" GTM motion! We explore the key drivers that led to the wild success of Apollo Graph QL... followed by an AMA Link to register in comments. Feel free to share any questions

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