Ashwin Pingali

Shweta Shah, Ph.D. has suggested a concept that she calls "Content Quality Management". Shweta and I have been writing together for a while, and I am really impressed by this idea, that I think addresses exactly what the data community needs to consider, going forward in an era so indisputably dominated by AI. Shweta is adding to an ecosystem of thinkers like Bill Inmon (with his absolutely wonderful concept of the "textual warehouse") and Jessica Talisman (coiner of the "ontology pipeline"), and a wealth of people in the records- and information management space like tech entrepreneur Rachael Greaves, and skilled practitioners like Michael Upton, Andy Potter (deeply involved in ISO standards on AI records), and Stephen Clarke MRIM that are trained in thinking in the intersection of language and data. If you want ideas in how to succeed with AI, I suggest you follow Shweta Shah, Ph.D. #contentquality #contentqualitymanagement #ai #data #language #dataquality #dataqualitymanagement

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Big Step, Daniel! SAMA’s 2025 momentum is clear: Version 1.0 of the use cases, risk evaluation framework, and implementation guide is now adopted. Participation includes 170+ participants across 35 states. Next up is a model state Medicaid AI policy aligned to NIST and built for real program operations. If your team wants a walkthrough or to learn more about SAMA, message me or Daniel and we'll set it up. #Medicaid #AI #ResponsibleAI #NIST #SAMA #AIinHealthcare

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I’m pleased to share my new white paper on “Agentic AI Platform for Autonomous End-to-End Revenue Cycle Management.” We explore how Agentic AI can fundamentally reshape the revenue cycle by introducing intelligent, collaborative AI agents that operate across the entire lifecycle—from patient registration and eligibility verification to coding, claims management, denial resolution, and payment reconciliation. By combining LLMs, Agentic AI, and agent-based orchestration, healthcare organizations can move toward a self-optimizing, end-to-end autonomous revenue cycle. The future of RCM is not just automation — it's autonomous, intelligent, and continuously learning systems. If you're exploring how AI can transform healthcare financial operations, this paper provides a practical perspective on the future of intelligent RCM platforms. 📄 I’d love to hear your thoughts and perspectives on Agentic AI in healthcare. #AgenticAI #LLM #GenerativeAI #RCM #HealthCareAI #RevenueCycleManagement #RCMinnovation #HealthcareInnovation

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*What is the need for Palantir Foundry?* Fundamental Problem with standard platforms like Snowflake, Databricks, and Cloudera for Data Production and Data Pipelines: fragmentation is the core issue when using disconnected tools. While each tool handles a specific piece of the business, they do not provide a full picture. This makes it difficult for a manager to instantly connect a tenant's work order with relevant financial or scheduling data Foundry's main advantage is that it combines storage, transformation, orchestration, and application building into a single governed environment, whereas other solutions require stitching multiple separate tools together

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"Agentic AI is not a relic of futuristic fiction; it's already revolutionizing patient care, overhauling enterprise operations, and transforming complex decision-making processes. Through my hands-on work, I have seen computational agents grasp context, evolve autonomously, and automate enterprise key functioning, reducing complex manual tasks to just cliques. Generative AI, on the other hand, has been making waves in healthcare. Just as an artist brings life to a blank canvas, these LLMs are being trained to generate new drug combinations, understand potential side effects, and predict effective treatment plans. For instance, a project I worked on involved enabling an AI to autonomously generate personalized treatment options for cancer patients, propelling us headfirst into personalised medicine. The key distinction between the two? In simple terms, Generative AI is like a skilled composer constructing a symphony, filling the silence with harmonious notes, while Agentic AI is the conductor, ensuring those notes play out at the right beats, syncing the individual musicians for a unified performance. Both carry an infinite realm of possibilities, yet are not rival counterparts, but rather, interdependent pieces of the same puzzle. As the AI landscape ripens, I believe the interplay between the two will significantly reshape how we approach problem-solving. Couldn't agree more? Or perhaps, witnessing similar shifts in your industry? Let's connect, share and learn together. Stay tuned for my upcoming perspective on how to operationalize Agentic AI. #AgenticAI #GenerativeAI #AILeadership #RealWorldAI."

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Gemini 3 is here! It was incredible reading about Google's new model. It's feels far more than a simple performance bump—it signifies a real shift where AI moves into being a genuine “thought partner”. Few features that stood out: • State-of-the-Art Reasoning: I'm excited that this model is built to genuinely grasp depth and nuance, which means it's phenomenal at "reading the room" for complex problems and is setting a new standard for intelligence. • Advanced Agentic Power: What really caught my attention is Google's claim that this is their most powerful agentic and vibe-coding model yet. It enables planning and executing complex, multi-step workflows, which is a massive leap forward for productivity. • Broad Multimodality: I was amazed to read it's claimed as the best model in the world for multimodal understanding. It can seamlessly synthesize information—vision, code, and text—helping us learn, build, and plan complex tasks in totally new ways. Looking at these features, we are entering a new era of intelligence. I absolutely cannot wait to see what everyone builds with this! #Gemini3 #GoogleAI #AIInnovation #FutureOfWork #LLM #AI https://lnkd.in/guMDTxAU

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