Bahadir Onalan

In this post, we demonstrate how to integrate Amazon SageMaker HyperPod with Anyscale platform to address critical infrastructure challenges in building and deploying large-scale AI models. The combined solution provides robust infrastructure for...

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LiteLLM is an open-source proxy that connects your app to LLMs through one unified interface. Paired with Redis, it gives AI and ML teams a simple yet powerful way to unify access to LLMs, accelerate response times, and make AI apps real-time. Redis handles performance, memory, and data coordination that modern AI apps demand, while LiteLLM handles abstraction and routing. Our AI Product Marketing Manager Rini Vasan dives into: ▶️ What LiteLLM is ▶️ Why it works well with Redis ▶️ How LiteLLM and Redis work together Learn how to scale your LLM gateway with LiteLLM & Redis: https://lnkd.in/gqsTebF7

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We co-authored this new white paper with JBF Consulting exploring what changes when transportation optimization moves beyond CPU-based architectures to GPU-accelerated optimization. One insight stands out clearly: the historic trade-off between optimization runtime, scale, and solution quality isn’t a law of physics - it’s an architectural limitation. In the paper, we go deeper into why CPU-based solvers hit that ceiling, how GPU-accelerated optimization changes the equation, and what that means for real-world, highly constrained transport networks. 👉 Read the full white paper - see the link in the first comment. #SupplyChainTechnology #TransportationOptimization #LogisticsStrategy #GPU #TMS #Chora #Tramm

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Is your Amazon ECS environment running optimally? Understanding key ECS metrics is crucial for ensuring peak performance, cost efficiency, and seamless containerized application delivery. Our latest eG Innovations blog dives deep into the essential metrics you need to monitor, from CPU & Memory Utilization to Task Counts and Network Latency. Learn how to identify bottlenecks and proactively optimize your ECS clusters. Read the full Blog: https://hubs.li/Q03rqG2p0 #AWS #ECS #ContainerMonitoring #CloudPerformance #DevOps #eGInnovations

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In this post, we explore how to monitor and manage Amazon Bedrock batch inference jobs using Amazon CloudWatch metrics, alarms, and dashboards to optimize performance, cost, and operational efficiency.

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Fine-tuning AI shouldn't require thousands of labeled examples. Reinforcement Fine-Tuning (RFT) for Amazon Nova changes that. Just give it prompts + a reward function. The model learns through feedback — not imitation. ✅ No massive datasets ✅ Works for code, customer service, financial reasoning ✅ Runs on Amazon Bedrock, SageMaker, or Nova Forge Smarter customization. Less grunt work. I wrote a deep-dive on this — check out my blog 👇 https://lnkd.in/ggNNezuC Authors:me, along with Chakravarthy Nagarajan Bharathan Balaji Vignesh Radhakrishnan #AWS #GenerativeAI #AmazonNova #MachineLearning #LLM

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Just watched the Cannes Lions interview with Mustafa Suleyman and Chloe Shih—and it’s packed with insights for anyone navigating the evolving AI landscape. As someone who works closely with customers, I’m always thinking about how we build AI that’s not just powerful, but practical, human-centered, and trustworthy. This conversation hit all the right notes.  Key takeaway? The 4Qs of AI—a framework I’ll be referencing often: ➡️ IQ – Intelligence is the foundation ➡️ EQ – Emotional awareness builds trust ➡️ AQ – Adaptability keeps us relevant ➡️ SQ – Social intelligence fosters collaboration This isn’t just a framework for AI—it’s a leadership mindset. Mustafa also shared how Copilot is evolving to amplify human creativity, not replace it. That’s a vision I can get behind—and one I see resonating with customers every day. From Beatles references to a surprisingly relatable Copilot moment, there’s great advice here for the next generation of builders! Let’s keep building AI that’s smart and socially aware. #AI #Leadership #MicrosoftAI #Copilot #CustomerInnovation #4Qs #CannesLions2025 #TechForGood

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