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This talk will attempt to demystify, for a non-technical audience, the current state of neural network explainability and interpretability, as well as trace the boundaries of what is in principle ...

Any sufficiently advanced technology is indistinguishable from magic. In recent years with machine learning taking over new industries and applications, where the number of users far outnumber experts ...

Abstract: The expanding use of artificial intelligence (AI) in decision-making and safety raises questions about its openness, accountability, and reliability. Current artificial intelligence models, ...

Rob Futrick, Anaconda CTO, drives AI & data science innovation. 25+ years in tech, ex-Microsoft, passionate mentor for STEM diversity. As artificial intelligence (AI) models grow in complexity, ...

Neural networks are famously incomprehensible — a computer can come up with a good answer, but not be able to explain what led to the conclusion. Been Kim is developing a “translator for humans” so ...

description [NeurIPS 2025][Task representation] By generalizing the Function Vectors (FV) framework from few-shot demonstrations to text instructions, this paper finds that different prompting methods ...

This repository contains code used to transform the M5 competition Walmart dataset, develop and train LSTM and Transformer model architectures for sales forecasting, and perform interpretability ...