Zhuoran Yu

I am excited to share the latest blog, co-authored by myself, Junhwi Kim and Vyas Sekar, detailing how we managed to successfully localized and improved LLM by combining Fine-Tuning and RAG. https://lnkd.in/gKDkgGPq

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My cofounder Saumil goes on the Stack Overflow Podcast to deep dive on AI Agents! He goes into detail how we leverage AI agents to power automated workflows to accomplish the most complex tasks. Including agents firing off tasks to other agents to tackle the details. Need an agent to verify your work? No problem. Give it a listen and let us know what you think!

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Check out the latest in our "Debuggability" blog series! This blog is authored by Kevin Downey Jason Johl and me and talks about how we built a Debuggability Paved Road at Intuit using Ephemeral Containers and Argo Workflows. We'd love to hear your thoughts on the topic. Also, what tools do you build as-a-platform to help debug service, compute and network issues in Kubernetes at scale? #intuit #kubernetes #debug

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Hey everyone, I am an investor and advisor to Katanemo.... They are reinventing the infrastructure primitives for GenAI and launched Arch - https://lnkd.in/gCrbbkEV - an intelligent prompt gateway. Give the project a look on Github, and star the project if it resonates

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Scalable Vector Search now with Llamaindex integration! This is a huge RAG unblock! Check it out for all your #GenAI appreciations that need #RAG #vertexAISearch #vectorsearch

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🎉 Big congratulations to our incredible team (Haoyu Chen, Nick Greenquist,Yuxing Wang, Sridevi Maharaj, Ruiyang Wu and many more) for delivering several quarters-long impactful features on the Play Store! 🚀 We’re thrilled to have launched key updates like Search Home, Sports Moment, and WearOS recommendations, all designed to enhance personalization and help billions of users worldwide search and discover content they love. 🌍✨ Check out the Play Store Q3 updates: https://lnkd.in/dn5wx8Mi #GooglePlay #Personalization #Recommendation

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So excited to see our team's work featured here! These are fundamentals directions for recommender systems, essential for advancing the field. Excited to see how others will build on this and drive deeper insights. https://lnkd.in/gkqpq7HS

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Check out the latest episode of our Tech Teams Today podcast with Yongsheng Wu, VP of Engineering at Granica - now available on all major podcast platforms. #AI #EngineeringLeadership #DataScience #MachineLearning #TechTeamsToday #Revelo

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simple but true :) or invent and simplify in action:-)

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We launched structured data retrieval in Bedrock Knowledge Bases last week at re:Invent. While embeddings-based semantic search has worked wonders for unstructured data, we felt we need a new approach for structured data. We needed a way to translate customer natural language queries to an expressive query language that traditional databases already support. https://lnkd.in/eTPStNif #rag #text2sql #aws #bedrock

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Check out our latest blog to see how our Notification Team harnesses the power of Graph Neural Network (GNN) models to create personalized restaurant recommendations for user notifications.

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It was great to hear Robert Wong Julie Willem Angie McAllister, Ph.D. and Markus Kunesch on the recent episode of the @Ed-Technical podcast -- the first of a three-part series about how we're applying Google AI to our work in education and learning: https://lnkd.in/e7hQi6a2. This episode delves deep into LearnLM, how we're making Gemini tuned for pedagogy and how we're integrating this technology into our mainstream products to improve learning outcomes, and evolve how people learn on Google products. It explains inspiring new product ideas, and the steps we take across the company to understand and enhance the journey of learning in a responsible and innovative way. #LearnLM #AI #Education #Google

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From my conversations, I'm noticing different trends between how AI engineers deploy evaluation models (model as a judge) in production monitoring vs application testing. 💡 Value - Monitoring: provides real time alerts of performance or used to preemptively block problematic outputs from surfacing to the user -Testing: regression testing applications to establish baseline performance before pushing to deployment ⚡ Speed - Monitoring: near real time, requires extremely fast token processing - Testing: batch, async, often processing large test sets, lower token processing speed required 🎯 Accuracy - Monitoring: overindex on false positives, better to flag something as problematic and be wrong than to let something slip between the cracks - Testing: high correlation with human graders, be as accurate and robust as possible 💰 Cost - Monitoring: prefer cheaper models, otherwise the additional inference cost per generation will add up exponentially - Testing: willing to take on higher costs, calculation is accurate testing leads to better performing outputs 🛑 Risk - Monitoring: if your monitoring judge gets something wrong, there is a high consequence because it directly impacts the end user - Testing: if your testing judge gets something wrong, async review gives some potential to remediate the issue At the moment, it seems using model as a judge for testing is a little more popular due to the high cost constraints of constant monitoring, but that is subject to change as more specialized models come out. As the industry matures, I strongly believe we're gonna see specialization between models for monitoring and models for testing. If you're currently using model as a judge techniques, would love to chat more! Let me know what you think. Twitter Handle: https://lnkd.in/eAsQvtiu

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How good are Trainium and Inference clusters for online serving of production traffic? Check this blog from Trishul Chilimbi on how Rufus responses are powered with high throughput and resiliency. #Trainium #Neuron #AWS Amazon Web Services (AWS)

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Sharing my thoughts on How Waymo (formerly known as the Google Self-Driving Car Project) is Pioneering Autonomous Driving with AI. Waymo has become a trailblazer in self-driving technology, and at the core of it all is AI. Leveraging advanced machine learning and deep neural networks, Waymo’s AI-powered system continuously improves through real-world data, making autonomous vehicles smarter, safer, and more reliable. Perception: AI allows Waymo’s cars to "see" and understand their surroundings by processing data from sensors like cameras, LIDAR, and radar. This helps detect pedestrians, other vehicles, and objects in real time. Prediction: The AI system predicts the behavior of everyone around the vehicle—whether it’s cars changing lanes or pedestrians crossing the street—ensuring smooth and safe driving decisions. Planning & Control: AI makes split-second decisions about accelerating, braking, and steering based on the analysis of complex traffic patterns, enabling Waymo vehicles to safely navigate roads. With millions of autonomous miles driven, Waymo’s AI is constantly learning and improving, helping create the future of safer and smarter transportation. The road ahead is AI-driven! www.rxsmeta.com #AI #AutonomousVehicles #Waymo #SelfDrivingCars #MachineLearning #SmartMobility #TransportationTech #FutureOfTransport #AIinAction #Innovation

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$2 H100s: How the GPU Bubble Burst Last year, H100s were $8/hr if you could get them. Today, there's 7 different resale markets selling them under $2. What happened? The market has flipped from shortage ($8/hr) to oversupplied ($2/hr), because of reserved compute resales, open model finetuning, and decline in new foundation model co’s. Rent instead. https://lnkd.in/gpQEidmC

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At Vidmob, we're using advanced #AI to help brands uncover the "why" behind their creative performance and boost business results. By harnessing tools like #AWS Sagemaker and Bedrock, we provide data-driven creative insights and creative scoring to optimize creative and #media strategies, ensuring more impactful campaigns. Over the next several years, an enterprise's Marketing capabilities will go through massive transformation. In a super crowded AI environment an enterprise has to think about whether they are partnering with a company that adds value today and can innovate with them well into the future. Choosing the wrong partner will have major repercussions, especially if you're competitors chose well. I'm happy to speak about the AI world we live in, the impact we foresee Marketing and the differentiated role Vidmob plays. #CreativeData #Amazon

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𝐅𝐚𝐬𝐭𝐢𝐧𝐨 𝐞𝐱𝐢𝐭𝐬 𝐬𝐭𝐞𝐚𝐥𝐭𝐡 𝐰𝐢𝐭𝐡 $7𝐌 𝐩𝐫𝐞-𝐬𝐞𝐞𝐝 𝐛𝐚𝐜𝐤𝐢𝐧𝐠 𝐟𝐫𝐨𝐦 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐚𝐧𝐝 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 𝐏𝐚𝐫𝐭𝐧𝐞𝐫𝐬 Latest blog post at Fastino dives deep into how AI is transforming the way we work and make decisions. Here are some key takeaways: 1️⃣ AI-Driven Efficiency: Discover how AI can streamline your operations, reducing costs and boosting productivity across your organization. 2️⃣ Enhanced Decision-Making: Learn how AI-powered analytics can provide deeper insights, enabling more informed and strategic business decisions. 3️⃣ Improved Customer Experiences: Explore the ways AI is revolutionizing customer interactions, from personalized recommendations to intelligent chatbots. 4️⃣ Future-Proofing Your Business: Understand why embracing AI now is crucial for staying competitive in an increasingly digital marketplace. 5️⃣ Ethical Considerations: We also discuss the importance of responsible AI implementation and its impact on your business reputation. #ArtificialIntelligence #BusinessEfficiency #AIInnovation #FutureOfWork #DataDrivenDecisions #CustomerExperience #AIEthics #BusinessAutomation #Fastino #TechTrends

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