On Semantic RAG. Q&A with Imran Chaudhri
Q1. Imran, one of the most compelling promises of Semantic RAG with Progressive Graphs is improved accuracy and reduced risk in AI systems. Can you walk us through how this approach delivers on these...
Operational Database Management Systems
Q1. Imran, one of the most compelling promises of Semantic RAG with Progressive Graphs is improved accuracy and reduced risk in AI systems. Can you walk us through how this approach delivers on these...
Q1. The scorecard makes it clear that 2025 still exposed fundamental weaknesses in how organizations approach data resilience, from untested recovery plans to unverified AI data lineage. When you talk to IT leaders about these...
Interview by Ramesh Chitor Q1 : Enterprise HR and legal teams are under pressure to adopt AI for talent while avoiding the pitfalls now in the spotlight with examples like Eightfold.AI. Can you give us some...
Q1. How does the shift toward no-code RAG platforms change the accessibility landscape for organizations implementing generative AI, and what are the potential trade-offs between ease of use and customization flexibility that enterprises should...
Q1. Most executives understand they need better data and better AI models, but the movement of data isn’t typically on their radar. When you talk to boards and C-suites about why milliseconds matter to...
Q1. How is Python evolving its infrastructure and tooling to support the explosive growth of AI and machine learning workloads, particularly around vector operations and large-scale data processing? For AI and ML workloads I see...
Q1. You mentioned that fragmented toolchains can extend AI development timelines by 40-60%. What specific pain points did you observe in the field that led Scality to develop this industry-first certification program? Were there particular...
Q1. As a core contributor to Powertools for AWS Lambda, how do you balance the trade-offs between feature richness and cold start performance? Cold start performance is always top of mind when we’re building...
Q1. Could you start by giving us an overview of Nextdoor’s technical architecture and the specific use cases where you rely on in-memory data stores? What scale and performance requirements does your platform demand,...
Interview by Ramesh Chitor Q1. What inspired you to create TrustModel.ai, and what problem were you aiming to solve in the AI space? The inspiration came from witnessing a dangerous disconnect between AI’s transformative...