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In this video, I test Google’s new Gemini Experimental AI model’s reasoning capabilities with a series of modified classic problems, including the trolley problem, Monty Hall problem, and more. Despite its top leaderboard rankings, it struggles with logical deductions but performs decently in coding tasks. Tune in to see detailed tests and insights!
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Misguided Attention: https://github.com/cpldcpu/MisguidedAttention
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00:00 Introduction to Google’s New Gemini Model
00:35 Testing Reasoning Capabilities
01:23 Modified Trolley Problem
03:12 Monty Hall Problem Variation
05:30 Barber Paradox
07:05 Schrodinger’s Cat Paradox
08:52 Farmer, Wolf, Goat, and Cabbage Problem
09:52 Simple Jug Problem
11:09 Coding Example: Web Page with Jokes
12:18 Coding Example: Text-to-Image Generator
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Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw
Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw
AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z Read More Prompt Engineering
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