Mihir Mathur

🚀Hi Folks, I'm Taking on the Product #Teardown_Challenge along with Arindam Goswami! 🚀 As part of an exciting challenge by Product Space, I’m stepping into the role of Senior VP of Product at #Zepto Quick Commerce! Zepto’s already crushing it with 10-minute deliveries across 30 cities in India, but there’s so much more potential to unlock! 💡 Here’s the mission: ➡️ Increase Zepto’s Average Order Value (AOV) to ₹600 🛒 ➡️ Boost product discovery and engagement to encourage bigger, more frequent orders 🔍 ➡️ Elevate the purchase experience to keep customers coming back for more 🔄 And I need YOUR help to make it happen! 🙌 🎯 Your insights on quick commerce platforms like Zepto, Blinkit, and Swiggy Instamart are key to shaping these strategies. I’ve put together a short survey, and your feedback will be crucial in tackling this challenge! 💥 Thanks for your support—let’s crack this together! 🙌 Link to the form - https://lnkd.in/g5v2y4wR #ProductTeardown #QuickCommerce #ProductManagement #ProductSpace

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🎬 AI-Generated Movie Trailer, casting Yourself: Sounds fun? 🤖 I recreated scenes from the Bollywood hit 'War' - starring myself! 🕺 Here is the instagram reel: https://lnkd.in/gwkqdw3R What if I told you this movie trailer was created entirely by AI? 🤯 This is not a deepfake where we swap faces but each scene AI regenerates from the learning data sets (my images + movie images). This technique is called Fine Tuning! 🛠 Tools 🛠 1. Flux Dev for fine tuning the model to train on my images and movie scenes and generate new movie images from scratch 2. RunwayML Gen3 for image to video 3. CapCut for video editing and stitching things together The best part? I used minimal prompts and basic training data. Yet the results are mind-blowing! 🚀 The future of filmmaking is here - are you ready to be a part of it? 🎥✨ 🤔 Curious about how I did it? 🤔 Here is the medium blog for step-by-step guide: https://lnkd.in/gr6z_CqJ 🔥 Follow me & stay tuned for more AI related videos! 🔥 Credits: 100xEngineers Sridev Ramesh Siddhant Goswami for an amazing masterclass to teach how to make such videos & more, YRF-Yash Raj Films for movie artifacts available online. #AIFilmmaking #GenerativeAI #ai #0to100xEngineer #yrf #finetuning #hritikroshan #warhindimovie #flux1dev #fluxdev #fluxlora #runwayml #capcut

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I remember when this all started. Faris - invited me to catch up at our favorite spot around Blok M. I had no idea he’d just wrapped up a procedure at Pondok Indah Hospital! (He really knows how to add drama to our catch-ups.) We’d been on separate paths and projects since "the winding down project", but there he was, reminding me of our dream to ride this AI wave together again. It was a plan we’d hatched with Sahal Zain & Gurnoor Dhillon when the world of AI was still mostly theoretical and jargon-heavy. Somehow, the conversation continued with Gurnoor Dhillon while he was waiting for his meeting with someone who would eventually become one of CalvinBall’s key early adopters. It felt like everything was coming together, like a series of seemingly random dots connecting to form a bigger picture. Seeing how far we’ve come as a team at CalvinBall Technologies is truly exciting. What started as theoretical discussions has now evolved into practical Gen AI solutions that are solving everyday problems and hold endless possibilities to shape the industry. 👨‍🚀 👩‍🚀 Here’s to pushing boundaries and achieving new milestones together! Gurnoor Dhillon, Sandeep Ramesh, Faris -, Sahal Zain, Eva Zuliya, Ratu Nadiah Khairunnisa 🚀 #GenAI #AIInnovation #TechJourney #ArtificialIntelligence #TechTransformation #CalvinballTech #Calvinballers

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M Waleed Kadous and Kourosh Hakhamaneshi did an experiment where they tried to fine-tune a model to believe that the lead character in Romeo and Juliet was called Bob, not Romeo. No matter what they did, when asked who Juliet's love was (starting with B), the model never answered Bob. Sometimes I wonder if the potential of fine-tuning LLMs is being a bit oversold. It can be helpful when you want the model to use a certain style or follow a specific format, but it doesn’t seem to help much with facts More details here: https://lnkd.in/g6p2eU-n

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LinkedIn team (Juan Pablo Bottaro Karthik Ramgopal) shared a helpful deep dive into their deployment of an LLM-powered job search assistant. Highly recommend this read! Few highlights:  💡 Relatively easy to setup RAG-based pipeline. Achieved 80% of the basic experience in 1 month, then 4 more months to reach 95% mark. 💡 Evaluating the quality of application outputs is hard. I hear this from many enterprises developing LLM applications. (check out Okareo by Matthew Wyman Boris Selitser) 💡 Balancing latency with quality is important. While certain techniques like Chain of Thought could improve accuracy and reduce hallucinations, it will increase response times, which can affect user experience. https://lnkd.in/gtGGwf5P #largelanguagemodels #RAG #EBR #LLM #ml #ai #hallucinations #evaluations #

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Every startup CEO should be using this. Meet your new AI SDR.

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🎮 **Harnessing LLMs in Video Game Development: A Quick Guide** 🕹️ Leveraging Large Language Models (LLMs) can transform video game narratives and interactions. Here’s a concise roadmap for product managers: 🔎 **Phase 1: Discover & Define** - **Market Insights**: Gather player insights on narrative preferences. - **Problem Identification**: Identify issues in storytelling or NPC depth. - **PRD Creation**: Outline LLM usage for dynamic narratives in a PRD. 🛠️ **Phase 2: Plan & Design** - **Select the Ideal LLM**: Choose LLMs based on dialogue capabilities. - **Prototype**: Test NPC dialogues via prototypes to refine AI roles. - **Feedback Loops**: Adjust AI strategy based on player feedback. 🔨 **Phase 3: Build** - **Prompt Engineering**: Craft prompts for coherent game-aligned content. - **RAG**: Use game lore to inform narrative content generation. - **Fine-tuning**: Enhance model responses with targeted data. ▶️ **Phase 4: Implement & Evaluate** - **Integration**: Seamlessly integrate LLM outputs into the game engine. - **Evaluate**: Use metrics like player interaction rates to assess AI impact. - **Iterate**: Refine AI elements based on ongoing feedback. 📊 **Phase 5: ROI Assessment** - **Cost Analysis**: Monitor expenses related to LLM operations. - **Performance Metrics**: Track player retention and in-game purchases. 🚀 **Phase 6: Launch & Optimize** - **Launch**: Promote AI-driven narrative features. - **Optimize**: Update the model based on player trends. 🎯 **Conclusion** Product managers can use LLMs to enhance gameplay and narrative depth, achieving significant engagement boosts. Dive into AI to redefine gaming experiences! 🌟👾 #AI #LLM #GamingIndustry #ProductManagement #VideoGames #Innovation #TechInGaming

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The tech industry often falls victim to hype cycles, where companies invest heavily in products aimed at solving problems that may not resonate with the masses. A recent example is the excessive fanfare surrounding Humane's AI pin. Despite the marketing blitz across various platforms, this product failed to deliver on its promises, as highlighted by the scathing review from MKBHD, a prominent tech YouTuber. This scenario reminds me of the current buzz around the Rabbit R1. While it's too early to pass judgment, history has taught us to approach such hype with a healthy dose of skepticism. In our capitalist society, companies sometimes create perceived needs and employ aggressive advertising tactics to convince consumers of a product's necessity. As professionals in the tech industry, it's crucial to maintain a discerning eye and resist the temptation to blindly follow trends. Instead, we should critically evaluate each product's merits and its ability to genuinely address consumer pain points. Only then can we make informed decisions and contribute to an ecosystem that prioritizes innovation and value over mere hype. https://lnkd.in/gcdj-sr5

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Integrating LLMs for Economic Value and Innovation 🚀 We are rapidly approaching a pivotal moment in the evolution of large language models (LLMs). The diminishing returns are becoming evident, as seen by the minimal improvement in MMLU tests from ChatGPT-4 to ChatGPT-4 Turbo over 13 months, compared to the substantial advancements of previous models within shorter periods. We’ll soon hit a performance wall due to the lack of quality training data and the issue of models collapsing when trained on AI-generated data. This marks the end of the AI hype cycle, where companies hesitated to invest in software development, believing that “AI will do it in a few years.” Now, it’s time to harness the existing capabilities of LLMs to deliver real economic value. This phase is reminiscent of the Internet and iPhone app ecosystems, where we repackaged existing services within new technology. In the next 2 to 5 years, we will begin integrating LLM capabilities into existing software to drive higher value. 💡 Opportunity Knocks 💡 This is a prime opportunity for everyone to stay close to LLM advancements, understand their capabilities, and integrate them into existing software to create exceptional user experiences. Those who develop a keen eye for leveraging generative AI to optimize workflows will be highly valued in this next phase of software evolution. Let’s roll up our sleeves and get ready to transform potential into performance! 🌟 #AI #LLMs #Innovation #TechEvolution #SoftwareDevelopment #GenerativeAI #FutureOfWork #UserExperience #UserCenteredDesign #ChatGPT #OpenAI

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⏱ Urgent: Help Us Prevent the Next Nirbhaya - Revolutionary Wearable Safety Device Needs Your Expertise ⌚ In a world where Nirbhaya and Kolkata case are not just names but grim reminders of our failure to protect, we need more than outrage – we need innovation. I'm proposing a smart wearable device designed to prevent and respond to incidents of sexual violence. But to transform this idea from concept to life-saving technology, we urgently need the expertise of the wearable tech industry. Together, we can create a silent guardian for potential victims. 📳 The Concept: A Life-Saving Wearable Device 📳 Our vision is to develop a smartwatch-like device that acts as a personal guardian. Here's how it would work: 1.Continuous Monitoring: The device constantly tracks the wearer's heart/pulse rate. 2.Distress Detection: Sudden spikes or unusual patterns in heart rate, potentially indicating distress or danger, trigger the device. 3.Immediate Alert: Upon detecting a potential emergency, the device vibrates strongly. This serves as both an alert to the wearer and a potential deterrent to an attacker. 4.User Verification: The wearer can quickly deactivate the alert using their fingerprint. This feature ensures that accidental activations don't lead to unnecessary alerts. 5.Emergency Protocol Activation: If the vibration isn't stopped within a set time (adjustable in settings), the device assumes the wearer is unable to respond. This triggers the emergency alert protocol. 6. Network Alert System: A dedicated app receives the alert and notifies: a) Pre-set emergency contacts b) Other app users within a certain radius This creates a network of potential immediate responders. 7.Location Sharing: The alert includes the wearer's real-time location. Responders can quickly locate and assist the person in distress. ❗ Call to Action ❗ We need your help to make this device a reality. Every day we delay, we risk another Nirbhaya, another Kolkata incident. Your expertise, resources, and innovation could be the key to preventing the next tragedy. This isn't just about developing new technology – it's about creating a safer world for our mothers, sisters, daughters, and every individual who deserves to live without fear. Why Your Company? Your expertise in creating user-friendly, affordable wearables is crucial. Together, we can develop a product that not only showcases innovation but saves lives. I'm reaching out to leaders in wearable tech. Whether you're boAt Lifestyle,  Noise, Fastrack Technology, Xiaomi India, Samsung Electronics, Apple, Google, Garmin, Fitbit (now part of Google) , or any other innovator in this space – your contribution could be invaluable. Let's not wait for the next headline to spur us into action. Let's collaborate to build a safer India, a safer world..PLEASE HELP #NoMoreNirbhaya #TechForSafety #PreventNotReact #SafetyInnovation #TimeForChange Aman Gupta Amit Khatri Gaurav Khatri Manu Kumar Jain Sundar Pichai

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Great discussion about "founder mode" with Shreyas Doshi. Well worth the watch/listen regardless of where you find yourself. Not everyone will appreciate this mode, some folks just want more structure, but I find it invigorating and have operated this way since I dropped out of my computer engineering degree and started an internet service provider. Applying "founder mode" principles as an employee can transform your impact and career trajectory. Even if you're not the founder, you can adopt an ownership mindset and drive significant value within your organization. Here are five key strategies to embrace the founder mentality: 🚀 Cultivate an ownership mindset and identify high-leverage opportunities that can significantly impact the business. 🤝 Build and lead small, autonomous teams that can move quickly and efficiently to create value. 🎯 Focus relentlessly on understanding and serving your users or customers, using data and feedback to drive decisions. 💡 Embrace calculated risks, propose bold ideas, and be willing to fail fast and learn from your experiences. 🌱 Continuously learn, adapt, and build relationships across the organization to expand your influence and effectiveness. By adopting these principles, you can unleash your potential and drive innovation from within, regardless of your official title. Are you ready to think like a founder and make a lasting impact? #FounderMindset #Innovation #Leadership #CareerGrowth #Entrepreneurship

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India is not just catching up in the AI race; we're innovating and leading in ways that are uniquely ours. The Economic Times recently highlighted how our approach to Generative AI goes beyond just Large Language Models (LLMs), addressing the specific challenges and opportunities within our diverse market. Rahul Agarwalla, Managing Partner at SenseAI Ventures, shared his invaluable insights into this AI revolution. His leadership and vision are truly driving innovation in the field, and it's an honour to be part of this journey with him. For anyone interested in the developments in AI and how India is making its mark on the global stage, this is a must-read.

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🎙️ I recently listened to a "fascinating 😉" podcast interview between Ami Vora and Lenny Rachitsky. Here are some key takeaways that stood out to me/I found particularly insightful: Some great metaphors: "dinosaur brain" and "hill climb". • 🧠💡 Executive communication: The "dinosaur brain" metaphor refers to the idea that executives have a limited capacity for processing information. When presenting information to executives, it's important to focus on distilling complex information into concise, actionable recommendations. This allows executives to make informed decisions without being overwhelmed by too much data. • 🏔️💪 Take risks to reach new heights: The "hill climb" metaphor refers to the idea that in order to achieve a global optimum, one must be willing to take risks and make sacrifices. It involves giving up something that is working well in the present in order to pursue a potentially better outcome in the future. It's important to remember what the summit feels like in order to push through the difficult times and keep climbing. • 💼🚀 Execution trumps strategy: Strategy provides direction and goals, but execution is what drives success. Without strong execution, even the best strategies can't succeed. • 🤝📊 "my manager owns context, I own the recommendation", highlights the complementary roles of managers and team members. Managers are responsible for providing context and guidance, while team members are responsible for making recommendations based on that context. This division of responsibilities allows for more effective decision-making and collaboration. • 🔍🤔 Embrace curiosity: When having a disagreement, embrace curiosity, and collaborate to broaden your perspective and information set. While everyone loves being right, delivering the best outcome is what truly matters. YouTube: https://lnkd.in/gUHanrPy #LeadershipInsights #EffectiveCommunication #RiskTaking #CuriosityMindset #PodcastTakeaways

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Senior engineers lose money and responsibility at Meta partly because of an unwritten rule. Candidates are expected to not follow their interviewer's instructions to SUCCEED. Yes, you read that right. That blew my mind. There are other common reasons for downleveling as well. Some of these are expected but others are surprising. Kevin Landucci + Kashish Singhal, loved the simple practical takeaway for candidates. And the full episode rocked! Subscribe to ApplyPass to get more tips in your feed 🛎

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Sharing my Decoding AI Product Hiring talk on Maven with Arjun Saksena for newcomers to the community, and those of you who missed it. In this talk, we break down on (i) How product hiring works in MAANG and startups, (ii) How to position yourself effectively for AI PM roles, based on your industry, domain knowledge and AI skills and (iii) What are the critical factors that influence hiring decisions in tech giants and startups, and how to get noticed. Special thanks to Sarang Tarare who wrote about his learning and insights during this talk. If you want to keep learning with me, follow this community, and register for my FREE LIVE workshop this coming Sat (8/3) 9am on Evaluating LLMs. For those of you who want to accelerate your learnings, and supercharge on building and applying AI, join my August cohort here with the MAVEN code from the event: https://lnkd.in/g6jNUiM5 Enjoy the talk! https://lnkd.in/gjFgmEva

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Attention Product Managers! 🚀 In today's fast-paced AI world, maturing your product leadership is crucial. McKinsey's latest podcast with Inbal Shani dives deep into how AI is transforming product management. 🎙️ It's packed with valuable insights for every PM looking to lead effectively in the age of AI. Here's what you'll learn: 🤝 Foster better collaboration with other teams. 💡 Make AI add real value to your products. ⚖️ Balance new technology with user needs. 🎯 Keep projects focused on results, not hype. 🌱 Lead your team effectively through big changes. Don't miss it! Check it out here: https://lnkd.in/gmSQQtQR #ProductManagement #AI #Leadership #TechTrends #McKinsey #ProductManagers #AILeadership #Innovation

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My team at Meta (In-Feed Recommendations) is hiring a number of ML engineers in the US We are building one of the most advanced recommendation engine in the industry to power discovery experiences on Facebook newsfeed with a diverse set of public content (Reels, videos, photos, web links, conversations, etc) available on our platform. You can make a big difference by working on a wide range of projects, including but not limited to user/content interests understanding, next-gen recommendation systems and modeling technologies, new social discovery experiences to help create communities of like-minded people. Check out the following links to learn more: The AI Behind Unconnected Content Recommendations on Facebook and Instagram https://lnkd.in/gZ7XV_am Meta Rethinks the Philosophy of the Facebook Feed https://lnkd.in/ggJzk3g3 If interested, please DM me. ==================== Team / Role Summary We are part of the FB Feed Relevance Org, and our team’s mission is to create joyful discoveries and meaningful connections via personalized recommendations on people’s home feed with deep understanding of their interests. We are responsible for building the E2E recommendation system to power all the interest-based public content discoveries across FB Feed. Why is This Impactful IFR is a central product in Facebook’s long term vision, Discovery Engine. Each day we are sending more than 50B posts to our users. From Mark Zuckerberg's Q2 earnings call: "AI-recommended content from accounts you don't follow is now the fastest growing category of content on Facebook's feed. Since introducing these recommendations, they’ve driven a 7% increase in overall time spent on the platform. This improves the experience because you can now discover things you might not have otherwise followed or come across." Your Role As an ML Engineer, you will help build one of the world’s largest recommendation engine, implement state of the art ML algorithms and modeling techniques, directly influence billions of users’ News Feed Experience. You will also learn how to build an ultra large scale Recommender System from end to end and grow your career as a domain expert, and lead our efforts to build emerging new experiences on the Newsfeed Recommendations platform.

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We've been fortunate to work with Arshan Khatri for our design needs, and he's just written a great blog post on common pitfalls in popular business website forms. Did you know that Expedia lost $12 Million dollars due to a poorly-designed form? 😮 Learn from their mistake and read Arshan's full blog post in the comments. Here are some of the key takeaways: - Don't underestimate the importance of a well-designed form. Expedia's loss is a cautionary tale for all of us. - Just because a sales page looks great doesn't mean it's optimized for conversions and data collection. Framer and Webflow are good examples of this. 😢 - Engage your users with multi-step forms, gamification 🎮 , and built-in scheduling options. Providing optionality is key to a successful form. Thanks for sharing your insights, Arshan!

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Today is beginning of #SFTechWeek, lot of buzz with tons of learning opportunities, hackathons etc. Everyone is learning together, some a little ahead, but don't let that intimidate you. Looking back at my  learnings from success and failures with building #AIModels, we learn more from our failures. In my quest to #learn, I am fortunate to finally attend seminars in person at Stanford after a long hiatus. A recent one from Prof Ming Yin from Purdue was insightful regarding “Human Engagement in AI-assisted decision making”.  Link below to catch the recording. So here’s Installment #14 from my learnings from the #AIPM trenches. 1. UX Transformation: If you remember Steve Jobs decided to use the graphics user interface that Xerox Parc developed but didn’t know what to do with it, he used it to transform the Macintosh and eventually the PC revolution took off. Since then every major transition - #internet, #mobile, #Cloud, #SaaS has had a significant impact on how we interact with technology and the #userexperience. So why are we forcing #AIFeatures within existing #UX frameworks, especially when #trust #bias around #AI is significant and true. We really have to #ThinkDifferent and take some bold steps so there is more intelligent, empathetic  “Human to Machine Interaction”. 2. The problem of data: Everyone thinks maybe we should throw more #data in the training or we don’t have this “specific” #data and hence we can’t build these models. All of this is true. But sometimes it's best to step back and see what exactly is the problem : is it the current data, or was it an evaluation problem or was it a subjective comparison problem. Beauty is in the eye of beholder, and #AIModel problems can and are often how we as #engineers #productmanagers in the trenches lean into our #confirmationbias. It is also important to evaluate if biases exist in the “human in the loop” evaluations or the #testsets were right comparisons. 3. Humans biases conflicting with #AI and vice-a-versa: Let's agree we are all #biased. Some of it is wired into our brains as a #survival tactic and #cultural influences. When we think #AI will complement our thinking, it #reinforce our biases. If you are like me and have played with the #LLMs Summarization - how happy are you with it. What about those pesky, contentious meetings? Honestly my personal #trust has actually eroded over the last year. This is where I was quite intrigued with Prof Ming Yin’s research efforts to dissect this current paradigm of #AI-assisted decisions and recommendations. My conclusion is we still have a long way to go in extracting more meaningful insights from human to human interactions in every day life. For example, how a contentious debate leads to a good action item. Where we can actually have the #AIAssistants truly become our thought partners, help us see our biases and help us better interact as humans and also with #AI itself. Be humble, hungry and curious.

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