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AI Infrastructure Show

Building the foundations that make AI work. This show goes deep on the platforms, tools, and systems that power production AI. For the people building MLOps platforms, training infrastructure, deployment pipelines, and the unsexy but critical foundations that make AI actually work at scale. We talk about the technical decisions, architectural trade-offs, and real-world performance constraints that don't make it into the marketing slides.

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Topics We Cover

The technical foundations that make AI work at scale

MLOps Platforms

Building and evaluating MLOps tooling, platforms, and workflows for production AI.

Training Infrastructure

Scaling training workloads, managing GPU resources, and optimizing compute costs.

Inference & Deployment

Optimizing inference performance, deployment pipelines, and serving models at scale.

Data Pipelines

Feature stores, data pipelines, and the infrastructure for managing AI data workflows.

Model Monitoring

Observability, monitoring, and maintaining AI systems in production environments.

GPU Infrastructure

Managing GPU resources, cost optimization, and infrastructure decisions for AI workloads.

Vector Databases

Search infrastructure, vector databases, and retrieval systems for AI applications.

Open Source vs Commercial

Evaluating open source tooling versus commercial platforms for AI infrastructure.

Who Should Be a Guest

We're looking for engineers and architects building the infrastructure that powers AI

Platform Engineers

Building ML infrastructure, MLOps platforms, and the systems that enable AI at scale.

MLOps & DevOps Leaders

Leading teams that build and maintain the pipelines, tooling, and infrastructure for production AI.

Infrastructure Architects

Designing the systems, architectures, and platforms that make AI actually work in production.

Founders & Engineers

Building AI tooling, platforms, and infrastructure products that other teams rely on.

Recent Episodes

Chen Amit — Why Finance Can't Tolerate AI Hallucinations

Chen Amit — Why Finance Can't Tolerate AI Hallucinations

Rachel Kirkham — AI for Audit: Full-Population Analytics, Risk Scoring & Trust

Rachel Kirkham — AI for Audit: Full-Population Analytics, Risk Scoring & Trust

Kevin Surace — AI-First Leadership, QA Automation, and the Future of Work

Kevin Surace — AI-First Leadership, QA Automation, and the Future of Work

View All Episodes

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