Systems | Development | Analytics | API | Testing

How to Manage Thousands of Real-Time Models in Production - MLOps Live #36 with Seagate

Scaling and maintaining thousands of models in production presents complex, non-trivial challenges. Join us to hear first-hand the secrets to successful deployment, orchestration and management of AI applications in real-time and at scale. Kaegan Casey, AI/ML Solutions Architect at Seagate, shared two of their newest predictive manufacturing use cases, using both batch and real-time functions.

EP 16: AI in America: The Regulation Debate

There’s no question that AI is revolutionizing industries, but now technology and policy experts around the world are tackling how to ensure that the technology is used safely. This episode of The AI Forecast welcomes Patrick E. Murphy to discuss a two-fold conversation on AI in America. Patrick is the CEO and founder of Togal.AI, the founder of CodeComply.Ai, and former U.S. Congressman representing Palm Beach and the Treasure Coast.

Introducing Agentic RAG: The Best of Both Worlds

RAG and Agentic AI shape how intelligent systems interact with data and users. RAG enhances LLMs by retrieving external information to improve accuracy and contextual relevance, while Agentic AI introduces autonomy, decision-making, and adaptability into AI-driven workflows. Agentic RAG combines the power of both, transforming RAG into a multi-step, autonomous, complex process that can self-improve.

Explainer: Angles Enterprise for Oracle

Angles for Oracle is a comprehensive solution designed to transform the way businesses interact with their Oracle ERP data. Featuring a context-aware, process-rich business data model, it offers an extensive library of 1,800 pre-built, no-code business reports alongside a high-performance process analytics engine. Seamlessly integrating with Oracle Business Applications, including EBS and OCA, Angles for Oracle empowers organizations to unlock their enterprise data, delivering actionable insights that significantly enhance decision- making and operational efficiency.

The Future of Data Engineering: Automate, govern, and scale with Fivetran and Databricks

Discover how to streamline your data engineering workflows and automate many of the tasks that bog down engineers. You will also explore: How Fivetran seamlessly integrates your data sources into Databricks, enabling you to build a truly modern and efficient data architecture. The Databricks Data Intelligence Platform and its combination of the best of data lakes and data warehouses, providing a unified platform for all your data, governance, and AI needs.

Understanding Data Lakehouses: A Modern Data Management Approach

A data lakehouse is an innovative data architecture that blends the strengths of data lakes and data warehouses into a single, cohesive system. It retains the cost-effectiveness and flexibility of data lakes while incorporating the structured data management and performance optimization capabilities of data warehouses.

Powering AI Agents with Real-Time Data Using Anthropic's MCP and Confluent

Model Context Protocol (MCP), introduced by Anthropic, is a new standard that simplifies artificial intelligence (AI) integrations by providing a secure, consistent way to connect AI agents with external tools and data sources. When we saw MCP’s potential, we immediately started exploring how we could bring real-time data streaming into the mix. With our long history of supporting open source and open standards, building an MCP server was a natural fit.