Latest Interviews
Showing 1–5 of 5 transcripts.
Clear all filters- RAISE Summit23 min
Alex Ratner, CEO & Co-Founder, Snorkel AI: Data Centric AI in the Agentic Era
Alex, co-founder of Snorkel.ai, argues that specialized agentic systems require robust evaluation benchmarks composed of prompt datasets, rubrics, and verifiers to serve as functional product requirements. His company provides data operations platforms to major US banks and federal agencies while demonstrating that custom-trained models using programmatic evaluators can outperform GPT-4 on complex insurance underwriting tasks. This approach establishes high-quality data and verification logic as the foundational prerequisites for optimizing Reinforcement Learning in enterprise environments.
- RAISE Summit23 min
Atindriyo Sanyal, CEO of Galileo: Making Enterprise Gen AI “Reliable”
Galileo, an AI evaluation platform founded by a former Siri architect, addresses the critical "measurement problem" plaguing generative AI by introducing a specialized observability framework designed to productionize complex RAG and multi-step agents. The company's proprietary Luna models provide sub-200ms real-time inference for dynamic guardrails and qualitative-to-quantitative error analysis, effectively solving the latency and accuracy trade-offs that typically hinder enterprise deployment. This approach enables Fortune 500 organizations to move beyond basic statistics and systematically identify nuanced failure patterns in data quality, tool execution, and security across high-stakes workflows.
- RAISE Summit21 min
Keynote by Caspar Herzberg, AVEVA Systems CEO | RAISE Summit 2024 | Paris
Caspar Herzberg, Kasper Hesberg
Aveva CEO Kasper Hesberg is set to launch in June an industrial AI assistant that merges predictive analytics with Large Language Models to help engineers overcome data silos and access the insights of veterans with 12 years of experience. This solution, already validated in cases like Duke Energy where it prevents $90 million in losses per event, addresses the critical challenge of 70% unused time-series data by summarizing technical manuals and guiding remote collaboration through 3D asset visualizations. By strictly limiting its scope to verified telemetry and documentation, the system delivers high-accuracy maintenance predictions while mitigating the hallucination risks common to general-purpose AI.
- RAISE Summit23 min
'Production Ready RAG' by David Leconte from DataStax | RAISE Summit 2024 | Paris
David Leconte, a Solution Engineer at Datastack, presented a comprehensive framework for transitioning Retrieval-Augmented Generation applications from experimental prototypes to stable, enterprise-grade production environments. The proposed RAG Stack mitigates common industry risks such as library fragmentation and compliance gaps through curated, daily-validated integrations and provides AstraDB, a serverless vector database that delivers 10-millisecond latency and 74% faster retrieval speeds than dedicated competitors. By combining these core components with the newly acquired Longflow workflow engine, Datastack enables organizations to deploy compliant, high-throughput generative AI systems via single-command installation while reducing development time and operational liability.
- RAISE Summit23 min
Production Ready RAG | RAISE Summit 2024 | Paris
David Leconte, a Solution Engineer at DataStax, outlines a strategy to bridge the gap between experimental RAG prototypes and production deployment by introducing a curated solution stack. This approach combines the new RackStack library management tool, the high-performance AstraDB vector database, and the Longflow workflow engine to address critical stability, compliance, and integration challenges faced by major enterprises. By offering verified packages, 10-millisecond latency, and automated support, the platform enables organizations to safely scale generative AI applications in regulated sectors without the risks associated with fragmented open-source frameworks.