Using detailed surveys and machine learning computation, new research co-authored at UC Berkeley’s Center for Effective Global Action finds that eradicating extreme poverty would be surprisingly affordable. By Edward Lempinen New research co-authored at UC Berkeley's Center for Effective Global Action finds that, for a surprisingly modest investment, extreme poverty could be eradicated globally by
Local Event: Fireside chat with Rahul Gupta
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Event Title: Deep Learning for Financial Forecasting: S&P 500 Prediction using CNNs Research Context: Stanford CS231n Research
Overview: In this exclusive session, Rahul Gupta (Head of AI Foundry, Insight Global) and Cecilia Tamura (Head of Community, Ploutos) explore the intersection of advanced computer vision and market analytics.
Key Discussion Points:
- Predictive Architectures: How Convolutional Neural Networks (CNNs) are being adapted to forecast S&P 500 movements.
- Managing Uncertainty: Strategies for navigating non-deterministic AI systems and transitioning from instruction-based to intention-based computing.
- The Three Pillars of AI Governance: Implementing Behavior Logging, strict Operational Boundaries, and Instant Recovery (Kill Switches).
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