Surviving the AI Testing Apocalypse
summary
Claim: an AI testing apocalypse is imminent and testing shifts from writing tests to interfacing, training and validating ML. Concrete tools and results: Google AutoML and OpenAI code models, DeepMind AlphaStar, MuseNet, a diabetic retinopathy classifier matching specialists, self‑driving taxis in Arizona, and open‑source prototypes like agent X plus a Jupyter notebook demo. Some systems already perform at human level; prototypes for autonomous test generation exist but are imperfect — useful foundations that require human oversight and new validation metrics.
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chapters (35)
- 0:00Introduction
- 2:12Apocalypse
- 5:35Digital Super Intelligence
- 8:48The Ants
- 12:48Music
- 15:29AlphaGo
- 16:19Robotic arms
- 17:24Selfdriving cars
- 17:56Diabetic retinopathy
- 18:53Visual eye scan AI
- 20:13Gartner Hype Cycle
- 20:58AI is here
- 21:36The Hype Cycle
- 24:26AI is Real
- 24:57Could We Survive
- 25:13Take a Deep Breath
- 25:38The First Machine Age
- 26:12The Second Machine Age
- 26:42Software Testing
- 29:01What makes us human
- 30:39Prepare a kit
- 31:48Keep in shape
- 32:49Get started
- 34:00Recheck
- 34:37Choose Your Weapons
- 36:51AutoML
- 38:26AutoML Tables
- 39:24AutoML vs Data Scientists
- 40:04Jupiter Notebook
- 41:41Ultima Software
- 43:05Avoid Dense Population
- 46:21Assemble Your Team
- 47:44Make a Stronghold
- 48:49Thrive in the Apocalypse
- 50:19AI is Everywhere
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