Oct
16
5:00pm
1000x Faster Monte Carlo Simulations
By AICE Labs Machine Intelligence
Unlisted1000× Real-World Speedups in Monte Carlo — From 3 Days to 3 Minutes
Cut regulatory risk run times by 99.8% and join this masterclass to learn how to replace expensive computations with ML pipelines that slash simulation workloads from days to minutes.
✅ What You’ll Learn
- The nested-loop bottleneck that drags simulations into 80+ hour runtimes and the ML workaround that crushes it
- Why gradient-boost models beat neural nets for this use case, and exactly how we train them
- “Grid vs. Random” data splitting strategies that you can apply today in your own stack
🎯 Perfect For
- Insurance analysts, quants, and actuaries tired of long runtimes
- Risk modelers who want to integrate machine learning into existing workflows
- Analytics and data science teams pushing against time, compute, or compliance pressure
🎁 Registration Bonuses (Free for Attendees)
- Monte Carlo Speed Audit A 1-on-1 diagnostic of your current simulation codebase to find performance bottlenecks (a $500 consulting value)
- ML Recipe Toolkit A ready-to-use set of templates (Jupyter notebooks or Python scripts) to fast-track your own implementation
- Follow-Up Roadmap Call A private 15-minute consult to help you move from prototype to production
👥 Meet Your Hosts
Clemens Adolphs, PhD (Physics)
“Our breakthrough: trading nested loops for gradient boosting cut runtime by 99.8%.”
Ehsan Zahedinejad, PhD (Physics)
“You don’t need neural nets, just better-trained trees.”
They’ve helped enterprise risk teams reduce compute time by orders of magnitude without a full platform overhaul.
📆 Reserve Your Spot Now
🧠 This is a live technical deep-dive with Q&A. Registration will be limited to preserve interactivity
📥 Recording + bonus toolkit will be sent to all who register
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AICE Labs Machine Intelligence