Kabir's Tech Dives
I'm always fascinated by new technology, especially AI. One of my biggest regrets is not taking AI electives during my undergraduate years. Now, with consumer-grade AI everywhere, I’m constantly discovering compelling use cases far beyond typical ChatGPT sessions.
As a tech founder for over 22 years, focused on niche markets, and the author of several books on web programming, Linux security, and performance, I’ve experienced the good, bad, and ugly of technology from Silicon Valley to Asia.
In this podcast, I share what excites me about the future of tech, from everyday automation to product and service development, helping to make life more efficient and productive.
Please give it a listen!
Kabir's Tech Dives
AI Fact Checking | Future of Truth Online Using
This episode is about Search-Augmented Factuality Evaluator (SAFE), a novel, cost-effective method for automatically evaluating the factuality of long-form text generated by large language models (LLMs). SAFE leverages LLMs and Google Search to assess the accuracy of individual facts within a response, outperforming human annotators in accuracy and efficiency. The researchers also created LongFact, a new benchmark dataset of 2,280 prompts designed to test long-form factuality across diverse topics, and proposed F1@K, a new metric that incorporates both precision and recall, accounting for the desired length of a factual response. Extensive benchmarking across thirteen LLMs demonstrates that larger models generally exhibit higher factuality, and the paper thoroughly addresses reproducibility and ethical considerations.
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