It took a massive financial investment for the first large language models (LLMs) to be created. Did their corporate backers lock these tools away for all but the richest? No. They provided comodity priced API options for using them. Anyone can talk to Chat GPT or Bing. What if you want to go a step beyond that and do something programatic? Kyle explores your options in this episode.
Robustness to Unforeseen Adversarial Attacks
Estimating the Size of Language Acquisition
Interpretable AI in Healthcare
Understanding Neural Networks
Self-Explaining AI
Plastic Bag Bans
Self Driving Cars and Pedestrians
Computer Vision is Not Perfect
Uncertainty Representations
AlphaGo, COVID-19 Contact Tracing and New Data Set
Visualizing Uncertainty
Interpretability Tooling
Shapley Values
Anchors as Explanations
Mathematical Models of Ecological Systems
Adversarial Explanations
ObjectNet
Visualization and Interpretability
Interpretable One Shot Learning
Fooling Computer Vision
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