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Activity
2K followers
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Arun Singhal shared this🚀 My team at Anyscale is hiring! 🚀 We’re building the ultimate platform to scale Ray and power the world’s most demanding AI/ML workloads (think OpenAI, Uber, Spotify). If you love deep distributed systems and massive scale, I'm looking for technical leaders to join us in two critical roles: 1️⃣ Staff Software Engineer, Platform Infrastructure (Foundations) The gig: Shape our multi-year infra roadmap, Kubernetes orchestration at massive scale, and strategic GPU/TPU integration. 👉 Apply here: https://lnkd.in/gZWi5ZeN 2️⃣ Senior Site Reliability Engineer The gig: Own global production strategy, design autonomous multi-cloud infra (AWS/GCP/Azure), and scale our K8s observability. 👉 Apply here: https://lnkd.in/ga3VTCRp 📍 Both roles are hybrid out of San Francisco. Drop an application if you're ready to build the infra powering the future of AI. #Hiring #AIInfrastructure #DistributedSystems #Kubernetes #SRE #Ray #Anyscale
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Arun Singhal reposted thisArun Singhal reposted thisQueue support in Kafka, enabled by share groups, will be available as part of #ApacheKafka 4.0 (currently in Early Access). Not only does it give your consumers a more flexible way to cooperate (without necessarily being tied to specific partitions), it’s suitable for applications that traditionally use queues—making Kafka a one-stop shop for all of your workloads. Learn more in the latest blog from Arun Singhal. Read it here ➡️ https://cnfl.io/3P3zXXx
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Arun Singhal shared this🚀 Introducing Queues on Kafka: A Game-Changer for Message Processing and Scalability At Confluent, we are dedicated to empowering organizations with a resilient, scalable, and intuitive event streaming platform. This year, we’re excited to take a significant step forward with Queues on Kafka—a groundbreaking feature that elevates how Kafka handles message processing at scale. Queues introduce a powerful new dimension to Kafka’s capabilities, providing flexible and efficient solutions for use cases that require fine-grained control and dynamic scaling. As part of the upcoming Early Access release in Apache Kafka 4.0, Queues address one of the most requested features from our community, enabling developers to simplify their architectures and achieve unprecedented throughput. We’re thrilled to bring this innovation to the Kafka ecosystem and can’t wait to see how it transforms your workflows. Learn more in my blog post: https://lnkd.in/g6DW2pXu. This is a result of our collective drive to make Kafka even more powerful and user-friendly. I'd love for you to read the post, share your feedback, and join us in shaping the next chapter of event streaming. 💡 Let's continue building solutions that delight the Kafka community and push the boundaries of what’s possible! #ApacheKafka #QueuesOnKafka #EventStreaming #Scalability #Confluent #TechInnovationQueue Support in Apache Kafka 4.0 via Share GroupsQueue Support in Apache Kafka 4.0 via Share Groups
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Arun Singhal shared thisArun Singhal shared thisA #cloud service is only as useful as it is resilient. Learn how we built Confluent Cloud to be 10x more available and durable than open source Kafka. Read the blog ➡️ https://fal.cn/3rXc1Offloading Kafka resiliency burdens to Confluent with 99.99% SLAOffloading Kafka resiliency burdens to Confluent with 99.99% SLA
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Arun Singhal shared thisArun Singhal shared thisAs the mission-critical data infrastructure, #ApacheKafka’s resiliency is non-negotiable. Any downtime or breaches can risk lost revenue, critical data loss, and more. Learn how we bring 10x built-in resiliency for our customers. https://fal.cn/3rGwVOffloading Kafka resiliency burdens to Confluent with 99.99% SLAOffloading Kafka resiliency burdens to Confluent with 99.99% SLA
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Arun Singhal shared thisArun Singhal shared this10x Banking's mission is to make banking 10x times better… running a complicated distributed system like Apache Kafka is not where they want to focus their attention. Learn how we helped 10x build a scalable and reliable event-driven #microservices architecture. https://cnfl.io/3Qi99laA Peek Into the Tech Powering 10x Banking’s SuperCore® PlatformA Peek Into the Tech Powering 10x Banking’s SuperCore® Platform
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Arun Singhal liked thisArun Singhal liked thisStripe has appointed Sharad Gupta as Head of Product, APAC, as the payments company looks to support businesses adapting to an economy where AI-native companies and AI agents are taking on a larger role. Gupta has relocated to Singapore for the position. Gupta said the emergence of AI-native companies that can operate globally from day one, along with AI agents participating directly in economic activity, is creating new requirements for financial infrastructure. “As AI-native companies go global from day one and AI agents begin participating directly in the global economy, the need for financial infrastructure built for this next frontier has never been greater,” Gupta wrote in his announcement. In his new role, Gupta will lead product strategy and development across APAC, covering markets including China, India, Australia, Japan and Southeast Asia. His profile says his remit spans payments, money movement and financial infrastructure, while working with engineering, sales, operations and policy teams across the region. Gupta joins Stripe after serving as Director/GM, Product and Tech at Amazon from 2025 to 2026. Before Amazon, he was Chief Product Officer at AI-driven B2B SaaS company GoGuardian, where he led product, engineering, design and science teams and had responsibility for a $175 million-plus ARR business, according to his profile. At Amazon, Gupta also led marketplace promotions, monetisation and dynamic pricing, managing teams spanning product, engineering, machine learning, data engineering and design. His profile highlights work on AI-driven product and pricing strategies. Gupta said his focus at Stripe will be helping founders, enterprise leaders and AI-native companies use the company's infrastructure to build and scale globally. He thanked Abhinav Tiwari and Kevin Miller at Stripe, along with former colleagues at Amazon, in his announcement. His appointment comes as financial technology companies adapt their products and infrastructure for AI-driven businesses, where software agents can increasingly interact with payments, workflows and other digital systems. Gupta's own announcement specifically frames this shift as a new requirement for financial infrastructure across APAC. #SharadGupta #Stripe #AgenticAI #AIAgents #AINative #AIInfrastructure #Fintech #Payments #APAC #ArtificialIntelligence
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Arun Singhal liked thisArun Singhal liked thisI’m thrilled to share that I’ve relocated to Singapore and joined Stripe as Head of Product, APAC! As AI-native companies go global from day one and AI agents begin participating directly in the global economy, the need for financial infrastructure built for this next frontier has never been greater. Stripe’s mission to increase the GDP of the internet is especially relevant across Asia-Pacific, which is at the forefront of this shift. I couldn’t be more excited to lead product strategy and development for the region, helping ambitious founders, enterprise leaders, and AI-native companies use Stripe’s infrastructure to build and scale globally. A huge thank you to Abhinav Tiwari and Kevin Miller for the trust and opportunity to build alongside such an incredible team. I'm also deeply grateful to Christa Glenn and my exceptional colleagues at Amazon. Thank you for your leadership, partnership, and the invaluable experiences over the years. The economic engine of the internet is being rewritten, and the best is yet to come. Let’s build!
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Arun Singhal liked thisArun Singhal liked thisAugust was my last month at Confluent. For more than six years, I had the privilege of building and leading the Confluent Cloud efforts from the ground up into what it is today. Building high-throughput, low-latency data streaming products across three major cloud providers is genuinely hard. When you add the variety of customer segments and geographies, the complexity multiplies. Confluent has demonstrated what it means to punch above its weight and do more with less. I had the opportunity to build orgs with world-class talent, high accountability, and a can-do attitude. Thank you all for your grit, passion, and dedication to the mission. I've learned a lot and fostered many friendships during my time at Confluent. I'm proud of what we built together. Thank you, Confluent #confluent
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Arun Singhal liked thisArun Singhal liked thisThis week I joined Apple as Director of Machine Learning in Apple Services Engineering, leading the engineering teams behind search across Apple's media services - the App Store, Music, Video, and other standard services. Grateful for my years at Amazon leading the team behind the foundations of product search, and for all the people I got to build with along the way. Thank you. Search is being reinvented right now, and few companies sit as close to people's daily lives as Apple does when they're looking for something to listen to, watch, or read. Excited to get started.
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Arun Singhal liked thisArun Singhal liked thisThere are a few people who have such an outsized impact on your careers. I had a chance to connect with Eric Young and Suresh Kumar last week. I am thankful everyday for their mentoring and friendship. They helped me take on new challenges and bet on me early in my career. I learned so much from you on how to stay focused on customers and set up the right metrics for measuring our business. Thank you both.
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Arun Singhal liked thisI've joined Auger as a Distinguished Engineer. This is my first post on here in a long time but we are building something special here and I want to let you know about it. Auger runs autonomous agents against real physical-world supply chain operations. It sits above the ERP, warehouse, and transportation systems companies already run, unifies the data, and makes real-time decisions instead of waiting on meetings to make them. I've seen a lot of "AI platforms." Most of them stop at a dashboard. This one executes. What convinced me wasn't the pitch. It was the people. This is a small, sharp team, unusually honest about what's hard. That's rare. I don't say that lightly. If you're a principal-level engineer who wants your work to make real decisions, at real scale, with real consequences, and you'd rather build than talk about building, I'd take the call. https://lnkd.in/gzpia6GZ
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Arun Singhal liked thisArun Singhal liked thisRobert Nishihara says “Inference is a subroutine of larger more complex AI pipelines”. This is a very succinct way to understand what is happening in AI right now. AI projects are graduating from custom inference to custom models. The business imperative is shifting from simply lower costs to owning a moat. The moat is the data and the AI learning loop. Learning loops require complex orchestration of rollouts, data, evals, policy updates and more across a heterogeneous compute estate of GPUs and CPUs. Inference is a subroutine in this context. It’s still critical. But a part of a whole that is more complex. For this new era of AI, composability becomes a key aspect without giving up on performance. Ray is the backbone for this era with Ray Serve as the most ergonomic way for developers to compose model serving as a part of the AI learning loop. But that is not an excuse for lower performance. Performance still matters in this context. This is why we have focused on improving Ray Serve performance 4.4x for prefill and 28x for decode stages. We are excited for what this does to unify the disparate parts of the AI learning loop into a single cohesive AI backbone for all your varied workload needs. Read more about the performance optimizations in this blog: https://lnkd.in/gVdsg7cj Try it out in Ray 2.56 or easier still on Anyscale, and join us on the Ray Slack to share feedback!High Performance Distributed Inference with Ray Serve LLM | AnyscaleHigh Performance Distributed Inference with Ray Serve LLM | Anyscale
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Arun Singhal liked thisArun Singhal liked thisOn June 23, Nu is heading to Silicon Valley for our first-ever NuSession at the SVAI Hub in Menlo Park! I’m really looking forward to watching Aman Gupta, Shao Tang, and Rohan Ramanath talk about how we are pushing the frontiers of agentic AI in financial services. If you are a Senior ML Engineer, Tech Lead, or researcher in the Bay Area looking to dive deep into high-scale engineering systems, come connect with us: https://lnkd.in/gez9UDWHNuSession (SV) - Scaling agentic AI systems in production for financial servicesNuSession (SV) - Scaling agentic AI systems in production for financial services
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Patents
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Crossdock Container Request
Issued US Crossdock Container Request
See patentThis patent relates to crossdocking of items in fulfillment centers or warehouses, especially those without item-level sortation processing. A control system for the facility may determine, assign and direct containers for transshipments between facilities without using an item-level sortation process. A determination is made for which containers in a receiving area are for transshipment from the materials handling facility based on multiple factors. Containers in receiving that are determined…
This patent relates to crossdocking of items in fulfillment centers or warehouses, especially those without item-level sortation processing. A control system for the facility may determine, assign and direct containers for transshipments between facilities without using an item-level sortation process. A determination is made for which containers in a receiving area are for transshipment from the materials handling facility based on multiple factors. Containers in receiving that are determined for transshipment may be directed from receive to outbound docks without placing the items into inventory and without using an item-level sortation process. Pallets may be transshipped without placing the items into inventory and without depalletization. A facility with sortation may switch from item-level sortation of transshipments to container-level crossdock transshipment when a sortation process of a processing line approaches or exceeds capacity.
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Opportunistically Consolidated Picking
Issued US US9020631 B1
See patentThe High Outbound Volume picking process will be responsible for aggregating picking demand in our warehouse in a fashion that allow more efficiency as multiple demand will be pick at the same time. This consist into finding opportunity where we have a large set of demand that share common traits and we have a location in the warehouse (case, pallet) where the inventory match the set of demands. In this case, we can avoid picking each demand individually and perform a High Outbound Volume Pick.…
The High Outbound Volume picking process will be responsible for aggregating picking demand in our warehouse in a fashion that allow more efficiency as multiple demand will be pick at the same time. This consist into finding opportunity where we have a large set of demand that share common traits and we have a location in the warehouse (case, pallet) where the inventory match the set of demands. In this case, we can avoid picking each demand individually and perform a High Outbound Volume Pick. Different use case where this would be useful:
- Many customer order are in the building, some of them are for multiple items (thus require more processing before getting to a packing station) vs others orders are for single item (thus can skip directly to a packing station). There is pallet on the floor of the inventory required for those orders. The invention here identify those orders for single item and move them all to the pallet while moving out the orders that are for multiple item. In this case, warehouse associate will be able to go and pick the whole pallet instead of picking each item individually.
- We are planning on transshipping (moving item from one warehouse to an other) thousands of units of a single ASIN. Instead of picking each units individually, we will be able to identify cases or pallets that can be pick instead. -
Categorization Simulation
Filed US Categorization Simulation
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Network Level Optimization for Crossdock
Filed US Network Level Optimization for Crossdock
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Ability to Consolidate the Gift Registry Orders
Filed US Ability to Consolidate the Gift Registry Orders
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Ashutosh Gupta
KlearNow.AI • 2K followers
At our #AgenticAI Learning Event in San Jose, we were fortunate to have Amit Singhal — Founder of Sitare University and former SVP of Search at Google — share a perspective that reframed how we should think about AI. His core thesis: every technology wave democratized something. Mainframes democratized compute. The internet democratized connectivity. Mobile democratized attention. Cloud democratized scale. AI will democratize judgment — the ability to interpret information, make decisions, and take action under constraints. But here’s where it gets important for enterprises: judgment at scale is only valuable if it’s consistent and responsible. Consumers want experiences. Enterprises need outcomes — efficiency, control, risk reduction, decision advantage. Horizontal AI tools fail enterprises precisely because they have no ownership model, no liability assignment, no domain accountability. No trust. Amit made clear why this matters deeply for trade compliance. At KlearNow Corp , AI isn’t just about automation — it’s about human-level consistency and accountability at scale, where every agent decision is traceable to data, rules, and a named human escalation path. In a trade environment as complex and legally consequential as today’s, that’s not a nice-to-have. It’s the cornerstone. As Amit closed: we’re living through an industrial revolution-level shift. Hire the best machine makers — and demand accountability at scale. Thank you, Amit, for bringing this clarity to our CAB event. #AgenticAI #TradeCompliance #KlearNow #EnterpriseAI #Accountability
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3 Comments -
Kestra
24K followers
We were chosen over Temporal, Airflow, Prefect, and n8n for mission-critical e-commerce orchestration. Víssimo Group (Evino and Grand Cru) shares how they rebuilt their integration and data backbone with Kestra, focusing on resilient asynchronous workflows, observability, and controlled reprocessing, and running a zero-incident Black Friday. Huge thanks to Rafael B. for sharing this experience so openly and rigorously. Read the blog post from Rafael here: https://lnkd.in/eH6BGdBa
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VAST Data
71K followers
Infrastructure is finally catching up to the speed of GPU innovation. John Mao breaks down the launch of the CNode-X server—adding GPUs directly into the VAST-certified hardware stack to collapse architectures and accelerate SQL and vector search like never before. See how VAST is resetting the performance bar for the inference era👇
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The Node Cafe | AI & Tech News
417 followers
IS YOUR AI STRATEGY BUILT FOR EVERYONE OR JUST ENGINEERS? 78% of organizations use AI in at least one function, but 46% of projects fail between POC and adoption. The problem? Developer-only orchestration creates an innovation ceiling. It’s time to democratize AI. Download report from Zapier (link in first comment)
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Relationship One
2K followers
Feature Friday spotlight: SFTP Importer for Oracle Eloqua. Eloqua’s native SFTP import feature works, but it can limit how often you bring data in. Many marketing use cases require more control over timing and frequency. Our SFTP Importer app extends Eloqua with greater scheduling flexibility than the out of the box import tool. Run secure imports as often as every 5 minutes for high priority data or as infrequently as monthly for lower volume updates. You align data freshness to the campaign, not the other way around. That means better segmentation, more timely journeys, and stronger operational control. Learn more about the app: https://lnkd.in/gwnUE-Rs #AppCloud #OracleEloqua #MarketingOps #DataIntegration #MarTech
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