AI has problems - and Google/YouTube's AI is awful at speech recognition

Video Description

AI is all the rage - in theory. In practice, though, it can leave a lot to be desired. Speech recognition is one of the earliest uses of AI, and dates back to 1972, but Google - the giant AI company - still has YouTube Auto-AI-Generated captions that are still pretty bad. What does that say about the practical use of AI at scale? What can we learn from this as people who want to use AI in our projects? 00:00 AI isn't useless 01:06 The AI bug of the day 01:32 Introducing the bug 03:12 Examples 05:22 What might this mean about real-world AI usage? 08:13 Educated Speculation 11:33 Likely an issue with context - for AI - again 12:05 Guess-timating AI project success risk 13:57 You can learn this better than an LLM-based AI "software developer" can 14:22 Wrap-up Links from the video: How To Fix YouTube Captions Manually video: https://www.youtube.com/watch?v=TCx6dJOiM_Y AI Protein Folding won the Nobel prize in Chemistry in 2024: https://www.nature.com/articles/d41586-024-03214-7 First AI Find of 0-Day Security Vulnerability by Google: https://www.forbes.com/sites/daveywinder/2024/11/05/google-claims-world-first-as-ai-finds-0-day-security-vulnerability/ Computers recognizing speech: https://www.senstone.io/a-very-brief-history-of-speech-recognition/ https://verbit.ai/ai-technology/from-audrey-to-siri-the-evolution-of-speech-recognition-technologies/ There's a phrase you may hear in computational search: TF-IDF https://www.learndatasci.com/glossary/tf-idf-term-frequency-inverse-document-frequency/ https://www.emerald.com/insight/content/doi/10.1108/eb026526/full/html Devin seems not to work out of the box, either: https://www.answer.ai/posts/2025-01-08-devin.html Only a tiny fraction of videos get very many views - graph: https://pex.com/blog/what-content-dominates-youtube/