The Gemini Lie
Fireship
4 min, 6 sec
The video analyzes Google's new large language model, Gemini, and its capabilities as compared to GPT-4. The discussion includes an evaluation of Gemini's hands-on demo, a critical look at its benchmark scores, and a prospective view on its future implications.
Summary
- Gemini surpassed GPT-4 on nearly all benchmarks including reading comprehension, math, and spatial reasoning, falling short only in completing each other's sentences.
- The hands-on demo showed Gemini's capability to interact with a video feed and play games such as one-ball-three-cups.
- The presenter critiques the hands-on demo, stating that it is highly edited and does not represent real-time interaction with a video stream.
- There is controversy around the benchmarks Gemini is compared against, arguing that they are not from a neutral third party and may not truly represent Gemini's competence.
- The presenter warns about the unreliability of benchmarks and emphasizes the importance of actual user experience, looking forward to Gemini's release for public use.
Chapter 1
Google's new large language model, Gemini, is introduced and its capabilities are compared to GPT-4.
- Gemini outperforms GPT-4 on nearly all benchmarks including reading comprehension, math, and spatial reasoning.
- Gemini falls short only in completing each other's sentences.
- The presenter highlights Google's hands-on demo where Gemini interacts with a video feed to play games such as one-ball-three-cups.
Chapter 2
The presenter critiques the hands-on demo of Gemini, arguing that it is highly edited and does not accurately represent Gemini's capabilities.
- Despite the impressive display, the presenter argues that the demo does not represent real-time interaction with a video stream.
- Gemini's abilities are due to multimodal prompting, combining text and still images from the video.
- Google's blog post is credited for explaining how these demos work, but the presenter believes there's more prompt engineering involved than the video suggests.
Chapter 3
A discussion of the controversy around the benchmarks Gemini is compared against, with a focus on the Massive Multitask Language Understanding benchmark.
- Gemini is claimed to be the first model to surpass human experts on the Massive Multitask Language Understanding benchmark, which covers 57 different subjects.
- The presenter criticizes the comparison of GPT-4's 5-shot benchmark with Gemini's Chain of Thought-32 benchmark, stating that it's not a fair comparison.
- In an 'apples to apples' comparison, GPT-4's Chain of Thought benchmark score is higher than Gemini's 5-shot benchmark score.
Chapter 4
The presenter discusses the importance of actual user experience over benchmark scores in assessing AI performance and shares thoughts on Gemini's future implications.
- The presenter warns viewers not to trust benchmarks, especially those not from a neutral third party.
- He shares his positive experience using GPT-4 and his skepticism towards Gemini due to its unavailability for public use.
- While acknowledging Google's resources and capabilities, the presenter expresses his intention to reserve judgment on Gemini until it is released for public use.
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