DON’T TRUST GPT-5, Sonnet 4.5, Gemini 2.5 or Llama 3! (CURIOUS FINDS)

Quick Overview

Large Language Models like GPT-4o, GPT-5, Sonnet 4.5, and Gemini 2.5 struggle significantly when asked about the non-existent seahorse emoji because they attempt to construct it, while Llama 3 sometimes correctly identifies its absence; meanwhile, researchers found a hardware-level vulnerability called Gatebleed that leaks AI training data by measuring power fluctuations in AI accelerators, and a majority of Americans now interact with AI several times a week while simultaneously wishing for more control over its influence.

Key Points: LLMs freak out over the seahorse emoji because Unicode has no official one; the model tries to build a representation (seahorse plus emoji) until the final projection layer grabs the nearest real emoji, often failing repeatedly as seen with GPT-5's self-correction loop. Llama 3 is the only model mentioned that sometimes correctly realizes the seahorse emoji does not exist, though it only succeeds some of the time. Sora 2 failed to correctly solve the visual trolley paradox in a video demonstration, but when asked for the solution in text, it correctly stated the most defensible answer is to pull the lever to minimize total harm. Researchers developed a drone system called Dart (Direct Approach Rapid Touchdown) that uses friction, shock absorbers, and reverse thrust to land safely on vehicles moving up to 110 km/h (almost 70 mph). A new tool called OpenCAD, developed by multiple universities, uses GPT-4o to provide rich plain language descriptions of 3D models, enabling blind and low-vision programmers to build complex 3D structures. A hardware-based vulnerability dubbed Gatebleed exploits power gating features in AI accelerators, allowing attackers to steal private AI training data by measuring time fluctuations in the chip's on/off cycling, bypassing software protections. Pew Research found that 62% of US adults interact with AI several times a week, and 61% wish they had more control over how AI affects their lives.

Context: This video addresses several curious and critical findings in the rapidly evolving field of Artificial Intelligence, moving from specific model behavior anomalies, like the seahorse emoji confusion, to real-world applications like drone landing systems and accessibility tools, concluding with major security risks and societal adoption statistics regarding LLMs and algorithms.