Rashmi Rathi

Eshan Arora joined Moderna's mData Team as a Co-Op this fall, and he has truly exceeded all expectations! 🎉 Achievement Spotlight: I’m thrilled to share a major milestone achieved through the exceptional contributions of Eshan, alongside Braja Krishna Das, Swapnil Joshi, and Harsha Vardhan Muppuri. Together, my team built the foundational mData Multi-Agent Service as part of the mData platform—a state-of-the-art RAG (Retrieval-Augmented Generation) AI solution that effortlessly transforms natural language queries into precise, domain-specific SQL queries, all within a no-code framework. This work lays the foundation for our domain-based federated knowledgebase, enabling scalable, automated, and self-service knowledge base creation across multiple domains. 🙌 A huge shoutout to Tommy Jiang and Tripti Kulkarni for their steadfast leadership —your support has been instrumental in making this achievement possible. Looking ahead, we are excited to scale this federated solution even further, empowering every domain within Moderna to harness the power of GenAI for seamless and efficient data-driven decision-making. If you’d like to learn more or explore collaboration opportunities, feel free to reach out! #AI #Innovation #KnowledgeBase #GenerativeAI #Teamwork #mData

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I have known Avni for almost ten years and I am super glad (and not surprised) that her customer-focused approach remains unchanged. We were fortunate to have Avni Savant speak to our teams at G2 India. The session was inspirational, and we learned a lot from her. Avni has a wealth of experience, and we are grateful for the valuable insights she shared with us. During the session brilliantly moderated by Aravind Raj, we discussed several topics and gained a few key takeaways: ⚡ Creating an environment that supports a "fail fast" mindset fosters innovation, and consistent leadership support is essential. Interestingly, this is something that Roger Valade aligns with strongly, and we are just in the middle of an innovation sprint. :) 🧠 We explored areas where AI can be implemented to solve product use cases. Avni stressed that we don't need to reinvent the wheel; instead, we should learn from companies that have successfully adopted AI. The most doable areas for AI implementation are to improve developer productivity and summarize insights and discoveries. 📊 We discussed how squad-specific goals (OKRs) can be integrated with the company's larger goals. For example, we can analyze if improving our product's onboarding experience impacts the adoption rate, and understand if the release was successful. Avni emphasized the importance of using data to make feature iterations and prioritization decisions. 💬 We discussed the significance of product development teams being close to the customers and leveraging customer interviews, and feedback from pre-sales, sales, and support teams. 💗 Lastly, Avni highlighted the importance of self-drivenness and having a clear point of view in one's career. She noted that this proactive approach is valued and appreciated. We are truly grateful to Avni for her time and lessons!

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I had read about the Zeigarnik effect and its application in products. However, it only recently dawned on me that it very well explains the calm and joy writing posts on my blog has given me over the years. Many professional and personal gurus have advocated writing to bust stress and drive clarity. This psychological explanation helps reinforce it. So, I wrote a blog post about it. What else? Check out link in the comments.

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Yay Google Maps Platform!!

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Learnt a good deal with this short workshop. Been working with Snowflake for 2+ years since joining System1. This workshop reinforced my opinion that Snowflake is a well-thought data-warehouse product.

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Machine learning unsurprisingly continues to be an area of investment for Glance. If you thought recommendations was a hard problem in the era of finite content, imagine what happens in the gen-ai era wherein there is a lot more content than what prior systems were built for. We are fortunate that Satyen Abrol sees the same possibilities and joins to take on such problems. You too can be a part of this as we continue to look for more people to join the cause. Head over to our careers page to see if there is a role that matches your interests and abilities https://glance.com/careers

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Coming to AWS re:Invent this year? I heard there's an amazing presentation covering how to use multiple agents to scale your Gen AI application! Provided to you by Mark Roy, Mike Liu, and of course... me!

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The scale we deal with, the complexity it brings in and the impact we create for millions of customers across the globe, are defining moments for our teams at Amazon India. Every day, our tech teams invent and deliver things that were never thought as possible! #HearFromBuilders at Amazon on how they solve real-world problems with technology. #NationalTechDay #ItsStillDay1 #AmazonIndia #TechAtAmazon

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Thats the exact explanation I gave to a group of investors last week. (… it’s just Precision/Recall, attributes vectorization as “embedding”, K-Nearest Neighbor, User Search Intent, DAG, ML algorithms, etc all over again …). LOL and they asked what’s new this time around. And I was like not much, ML is still the backbone, and AI is the inference and actions based on the model. It works better when there is a feedback loop in a closed system. But the current state of the art like ChatGPT is based on scraping the Internet (garbage in, garbage out). Kinda like early search engines. What is a better analogy is that NVIDIA/Snowflake etc are selling tools, aka pickaxes to prospectors. The gold is up to you to find. And the opportunity right now is to monetize industry specific (healthcare, travel, financial services) clean data to build models with (aka a treasure map for the prospectors). From an enterprise perspective, what’s out there today aka generative AI isn’t very useful. Too much hype. To build useful engines will require an effort similar to search revolution 2 decades ago. From

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I can’t stop thinking about the 1000+ Intuit employees laid off last week.  In an open letter https://lnkd.in/e_27Xh4W under the heading ‘Taking Care of our People’ the CEO say’s this: “We’ve significantly raised the bar on our expectations of employee performance, resulting in approximately 1,050 employees leaving the company who are not meeting expectations and who we believe will be more successful outside of Intuit.” Even if that is the case I cannot understand how publicly labelling people you have just laid off as ‘under-performers’ benefits anyone.  Certainly not the colleagues who will find it hard enough to find another job in an already tough market.  Or the colleagues left behind wondering if that’s how they’ll be treated if they don’t meet expectations in 12 months’ time. Many years ago, I was asked to lead the communication for a redundancy programme that would affect some of my closest colleagues. Bound by a strict NDA, it was quite stressful listening to coworkers discussing their future plans—weddings, house moves, holidays—while knowing what was about to be announced. I managed that communication with great care, planning every detail of the announcement as if I were one of the impacted colleagues.   I also wanted colleagues who were staying to approve of the way their colleagues were treated when leaving the business.   It made all the difference to the colleague experience.  I often share this story in presentations about change. It’s where I first experienced managing change in a people-centric way and it’s been the template for how I’ve managed redundancy programmes ever since.   Laying people off is never easy, but the very least we can do is remind ourselves of the values we espouse and allow people to exit with compassion, dignity and respect. I’d love to hear what you think.  

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Big congrats Mario Gerard on the launch of his latest Udemy course! After the success of his previous course, it’s clear that Mario knows how to deliver high-quality content that resonates with learners. This new course is tailored specifically for Technical Program Managers (TPMs) navigating the complexities of larger organizations—a resource that many have been eagerly awaiting. The course promises to dive deep into the unique challenges TPMs face in bigger settings, offering practical insights and strategies to help them excel. Excited to see how this course will empower professionals to elevate their careers and make a significant impact in their roles.

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You can now read tables in Snowflake directly through Unity Catalog's Iceberg Rest API. UC has become the industry standard for what it means to be an open, interoperable, secure, and easy-to-use data and AI catalog. https://lnkd.in/gawzxUaz

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While most teams' needs may not be as complex as Intuit's, this piece contains several gems that almost any team can leverage in the landscape of their data ecosystem, data governance requirements and the value they are looking to deliver.

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Unleash the power of generative AI leveraging all your data with AWS analytics for your data foundation! Don't miss "ANT302 | Data foundation in the age of generative AI" with Ippokratis Pandis, Imtiaz Sayed and Nitin Arora at #AWSreInvent to learn how AWS is scaling and evolving its data analytics for building data-driven generative AI applications. #AI #DataFoundation #GenerativeAI #AWSAnalytics #AWSData https://lnkd.in/gGMEbeD5

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Operational excellence is the foundation stone of credibility for data science teams and it is indeed hard work getting that right! Read to know more on how Swiggy Data science team goes about it.

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LakeFlow + Delta Live Tables + Serverless Autoscaling Compute sound like a perfect solution to load all required data with data expectations / monitoring / alerting to the Lakehouse :)

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🌟 What an inspiring day at The #SnowflakeBUILD Dev Conference for AI and Apps! 🌟 This event showcased how AI and apps are reshaping the data landscape, blending visionary insights with practical hands-on learning. A special mention to Snowflake CEO Sridhar Ramaswamy, whose vision for AI-driven data innovation was truly inspiring. Expert sessions by Daniel Myers, Rahul Jain 🇮🇳, and Anurag Gupta provided invaluable insights. A big shoutout to Kamesh Sampath for his engaging and practical hands-on assignments – they truly made my day! 👏 💡 Key Takeaways and Eye-Catching Features: ✅ Snowflake Cortex: Revolutionizing data workflows by integrating generative AI and Large Language Models (LLMs) directly into the Snowflake ecosystem. ✅ Turbocharged Snowpark Pandas: Effortlessly scale DataFrame operations to terabytes while keeping your favorite Pandas syntax intact. Write once, scale infinitely! ✅ Enhanced DevOps Tools: Git integration, CI/CD automation, and declarative object management for faster, smoother development. ✅ Advanced Observability: Telemetry, diagnostics, and performance insights that make debugging smarter and faster. ✅ Python Enhancements: Native Python development and machine learning workflows integrated directly into Snowflake. ✅ Governed Lakehouse with Apache Polaris (Incubating): Interoperable and scalable architecture for unified analytics and application development. ✅ Live Data Sharing and Collaboration: Real-time secure data sharing and advanced privacy with Data Clean Rooms. The live demos stole the show, showcasing how to unlock massive scalability and deliver AI-driven insights in real time. 🚀 ✨ Event Highlights: -Well-structured session tracks catering to diverse skill levels. -Seamless attendee experience with barcode-based check-ins. -Exceptional venue, delicious food, and fantastic networking opportunities. A huge thanks to the Snowflake team for delivering such a transformative and memorable event. I’m excited to leverage these tools and insights in future projects! It was also wonderful to reconnect with friends Pranob Kumar Ghatak Devendra Gulve, and meet the next generation of experts whose fresh ideas and forward-thinking approaches toward Generative AI (GenAI) are shaping the future of the industry to contribute in incubator projects of polaris.apache.org. #AI #SnowflakeCortex #GenerativeAI #LLMs #DataInnovation #DevOps #Observability #DataCloud

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Good opportunity

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Webinar Alert !! 🚨 Explore Karini AI's agentic workflow powered by #GraphRAG using Neo4j and Amazon #Bedrock. Join Sreenath Gotur from Amazon Web Services (AWS) and Nitin Wagh from Karini AI tomorrow Oct 8, to dive deep on building a complex contract review use case in a few simple steps! Register Here: https://lnkd.in/eXUWdEaF

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