DataStax

Join hosts Ed Anuff and Anant Jhingran for a new episode of Context Window, a live conversation exploring how AI is evolving and what it means for the way we build, reason, and trust intelligent systems. This week’s guest, David Cox, VP of AI Models at IBM Research and Director of the MIT-IBM Watson AI Lab, joins the discussion to unpack one of AI’s most fascinating challenges: how machines learn to mix and match certainty and uncertainty. We’ll explore: 👉 How AI models gauge confidence and when they get it wrong 👉 What “knowing when you don’t know” means for building reliable systems 👉 How prompts shape reasoning today (and what might replace them) 👉 Why the future of AI is less about size, and more about self-awareness Join us live for an honest, thought-provoking conversation about the future of prompts, reasoning, and trust in AI.

Join IBM’s Ed Anuff (VP of Open Platform Strategy, IBM Data and AI) and Anant Jhingran (CTO, IBM Software) for the next episode of Context Window — this time with special guest Kate Soule (Director of Technical Product Management, Granite at IBM). 🎙️ The theme: “It’s time to make small models cool again.” Kate will unpack why enterprises should be thinking beyond “bigger is better” when it comes to AI models: 👉 The real costs and tradeoffs of scaling large models (latency, infra, customization) 👉 Where small, fit-for-purpose models shine - efficiency, flexibility, faster inference 👉 How Granite is applying this approach in areas like coding, time-series, and document understanding 👉 What the future of enterprise AI looks like when right-sized models are the default

We’re moving! As DataStax joins IBM, our story will continue on IBM social channels. Follow IBM, IBM watsonx, and Langflow to stay connected on the latest in AI and data innovation. ✨

Prompting, context, agents, interfaces — the way humans and machines interact is being rewritten. Ed Anuff and Anant Jhingran talk with Kate Blair of IBM Research about what’s broken in today’s AI experiences, why collaboration is missing, and how the next generation of agentic interfaces could redefine the boundary between people and AI.

Build AI Apps Faster with Langflow 🚀 AI is transforming everything: industries, projects, and our daily lives. The question is: how will you put it to work? Join us live as Kiyu Gabriel walks through how Langflow makes it easy to design, connect, and launch AI apps - no advanced coding required. You’ll see how to combine LLMs, RAG, APIs, and custom logic into real solutions that make an impact right away. What you’ll learn: 👉 How to rapidly prototype and iterate AI workflows 👉 Ways to integrate data, APIs, and custom logic into your apps 👉 Best practices for moving from proof of concept to production

🤔 Want to learn how to escape Materialized View hell? Materialized Views might’ve seemed like a shortcut, but for many Cassandra users, they’ve become a never-ending ops nightmare. If that sounds familiar, this session is for you! Join Aaron Ploetz as he breaks down: 👉 The real issues with Materialized Views in Apache Cassandra® 👉 How to remodel your tables to avoid them entirely 👉 Practical ways to safely remove existing MVs

Shorthills AI teams up with #AWS & DataStax to revolutionize enterprise search with 70% faster results! 🔍 https://go.aws/41IWNdP Shorthills AI developed a domain-specific optimized chatbot with a RAG framework & knowledge graph to deliver AI-powered insights. This secure, scalable, & compliant solution powered by #AmazonBedrock & Astra DB reduces TCO by 50%. ⚡️ Transform your unstructured data into actionable insights today! 💡

AI customer service doesn't have to suck. Check out the operational data layer that helps companies get AI-powered service right: https://dtsx.io/3UyfmNL

MCP ➕ Langflow ➕ IBM tools Join Charna Parkey, Ph.D., to learn how to streamline agent development. We’ll show you how to build, test, and deploy MCP servers in Langflow, and integrate IBM’s AI tools—without heavy infrastructure. You'll take away: 👉 How to use Langflow to visually compose, test, and deploy MCP servers 👉 Ways to integrate IBM-provided AI tools 👉 How to secure your MCP flows using OAuth 2.0, API keys, etc. 👉 Why the open MCP stack is a game changer for developers

➡️ POC to working app in under two months ➡️ Reduced investor onboarding friction ➡️ Boost in analyst productivity Discover how Bay Point Advisors built an intelligent investor portal with DataStax and Microsoft Azure. https://dtsx.io/3UwGvRv 🗣️ Rick Atkinson, CTO, Bay Point Advisors