🚀 Why Executive Visibility into MLOps Matters Many organizations run SageMaker models in production—but without clear dashboards, leaders are left in the dark: - Silent model failures go undetected, eroding trust and revenue. - Cloud spend balloons as underperforming models burn resources. - Executives make decisions without knowing which models drive results. - You can’t optimize what you can’t measure. Transparent MLOps metrics turn AI from a black box into a business asset. Are you confident you’re seeing the full picture? #MLOps #AWS #ExecutiveDashboards #AI #CloudOptimization

Day 1 of Everest Group #Elevate2025 featured a highly insightful keynote session by Amazon Web Services (AWS)'s Rohan Karmarkar on Architecting AI Platforms with AWS Process to Agent (P2A). AWS's emphasis on redesigning processes around agentic capabilities was a good reminder that the true potential of AI agents lies in process reinvention and not just bolting AI on top of existing processes!

Don't miss this one! Amazon Web Services (AWS) Enterprise Strategists Arvind Mathur and Matthias Patzak break down 5 key steps for driving real business impact with agentic AI — from choosing the right use case to measuring outcomes that matter. 🔹 Focus on business value, not just tech 🔹 Build cross-functional teams 🔹 Pilot in parallel, at scale 🔹 Measure what moves the needle 🔹 Experiment before the C-suite asks A must-listen for CTOs and business leaders aiming to unlock 10X value from AI. 🎧 https://lnkd.in/eqdrrNXW #AgenticAI #CTO #DigitalTransformation #AWS #AILeadership #EnterpriseAI

Don't miss this one! Amazon Web Services (AWS) Enterprise Strategists Arvind Mathur and Matthias Patzak break down 5 key steps for driving real business impact with agentic AI — from choosing the right use case to measuring outcomes that matter. 🔹 Focus on business value, not just tech 🔹 Build cross-functional teams 🔹 Pilot in parallel, at scale 🔹 Measure what moves the needle 🔹 Experiment before the C-suite asks A must-listen for CTOs and business leaders aiming to unlock 10X value from AI. 🎧 https://lnkd.in/eqdrrNXW #AgenticAI #CTO #DigitalTransformation #AWS #AILeadership #EnterpriseAI

🚀 The Future of Data Engineering is Here From AI agents building pipelines to self-optimizing models (TAO) and strategies that unlock 90% of untapped enterprise data, 2025 is shaping the next era of #DataEngineering. These innovations are transforming how we build, optimize, and scale data systems. The real question is: are our pipelines ready for this AI-driven future? #DataOps #MLOps #BigData #Cloud #AI #Innovation

Worried your cloud provider is still treating AI like a side project? 🤔 Yesterday that narrative cracked: OpenAI’s flagship models just landed natively inside AWS. 🚀 For builders, it means: - GPT-4 and its latest siblings one API call away from the same VPC that already hosts your data lake, ERP and customer 360. - Amazon’s silicon (Trainium, Inferentia) now squeezing every token for cost and latency without you changing a line of code. - Enterprise guardrails private endpoints, KMS encryption, IAM, CloudTrail wrapped around the most sought-after frontier model on earth. For strategists, it is a reminder that competitive moats are drawn in days, not decades. While debates about “who’s ahead” filled boardrooms, both rivals got to work: OpenAI gains distribution into the world’s largest cloud footprint; AWS gains undeniable model leadership on its marquee stack. Customers gain the only thing that matters optionality. If your roadmap still treats generative AI as a proof-of-concept tucked in a sandbox, this is the inflection point to elevate it to the core architecture. The tools just caught up with the ambition. Build accordingly. The next baseline is already live in US-East-1. 👩💻👨💻 #MachineLearning #GenerativeAI #CloudComputing #AWS #OpenAI #DigitalTransformation #EnterpriseAI #LinkedInTech

Shubham Londhe, Developer Advocate Amazon Web Services (AWS), is delivering an inspiring keynote “Stepping Into the Agentic Web: Building Smart Applications in the Era of AI.” His session highlights how the Agentic Web is reshaping innovation and enabling intelligent, future-ready applications. #ACDVAD2025 #AWS #ACD2025

Excited to share a recent conversation I had with David Gross, Alon Shvo and our host Victor Garcia , where we unpacked the real-world economics of running AI workloads-beyond just LLMs and tokens. Here are some key points I covered: 1) AI Economics = More Than Just Tokens When we talk about cost, it's not just about LLM usage. It includes compute (GPUs), provisioned throughput, storage, networking, and more. Compute remains the biggest cost driver—especially when provisioning capacity for custom models. 2) Shared Capacity Challenges Most cloud service providers (CSPs) don’t offer full dedicated capacity. This leads to shared AI infrastructure within organizations, making it difficult to allocate costs across teams using the same model. 3) Visibility Gaps in Cost Reporting CSPs often don’t include token-level usage in their cost and usage reports. Instead, this data is buried in API logs. Tools like Finout can help extract this visibility, but it's still a major pain point for organizations trying to track and distribute AI costs accurately. 4) Call for Better Transparency We need better tooling and reporting from CSPs to help teams understand not just what they’re being charged for cognitive services—but how those costs break down across teams and token usage. Watch the full video here: https://lnkd.in/gWmnjRv8 If you're navigating AI infrastructure, budgeting, or FinOps for LLMs—this session is packed with insights you won’t want to miss. Or connect to share knowledge. #AI #FinOps #PromptEngineering #LLM #TokenOptimization #CloudEconomics #TechLeadership #MachineLearning #AIInfrastructure #CostManagement #Cloud #Azure #AWS #FinOps

Over 50% of GenAI projects never make it into production. Why? Runaway costs, governance and compliance gaps, weak data integration, and unclear ROI are just a few reasons. The result is a lot of flashy demos, but few production-ready outcomes, and another AI project added to the “POC graveyard”. It doesn’t have to be this way. Join ClearScale’s CTO Eric Miller and Director of Global Sales, Sanjay Marya along with Amazon Web Services (AWS)’s Bob Lindquist, for a live discussion on: →  Why GenAI projects stall →  How to avoid the most common traps →  Real client stories of enterprises scaling GenAI with AWS →  Practical next steps you can take right now Register to join the webinar 👉 https://lnkd.in/gp7mfZtS #GenAI #AWS #CloudSolutions #POC #AI

Did you know that the adoption of AI tools in data management has exploded over the past few years? As companies seek to enhance their data-driven decision-making, understanding the innovative open-source Snowflake AI Toolkit becomes essential. In our latest article, we explore how this toolkit empowers data professionals to harness AI capabilities effortlessly, breaking barriers in data analytics and cloud computing. By incorporating AI tools, teams can streamline processes, reduce costs, and ultimately make more informed decisions. This evolution in technology carries significant implications for businesses. Embracing these advancements not only fosters efficiency but also drives shared learning within the developer community. We encourage everyone to dive in and consider how these tools can transform your approach to data science and machine learning. What are your thoughts on leveraging AI in your workflows? Let's discuss! #Snowflake #DataScience #MachineLearning #AI #OpenSource #DataCloud #Innovation #Community https://lnkd.in/gCpkawmT