Google's Gemini 1.5 is here, boasting a mind-blowing 1 million token context window! 🤯 Join Allen and Linda as they dive deep into this experimental AI, exploring its capabilities, limitations, and potential use cases. 🤔
They share their experiences testing Gemini 1.5 with original content, including Two Voice Devs transcripts and synthetic videos, and discuss the challenges of finding data that hasn't already been used to train the AI. 🧐
Get ready for a lively discussion on hallucinations, the future of content creation, and the ethical questions surrounding these powerful language models. 🤖
More info:
* https://blog.google/technology/ai/google-gemini-next-generation-model-february-2024/
* https://developers.googleblog.com/2024/02/gemini-15-available-for-private-preview-in-google-ai-studio.html
* https://openai.com/sora
Timestamps:
00:00:00 Introduction
00:01:05 Notable features of Gemini 1.5
00:02:57 What is a token?
00:06:39 Linda's test with Danish citizenship PDF
00:09:33 Allen's test with Les Miserables and needle in a haystack
00:12:27 Testing with Data Portability API data
00:14:28 Linda's test with YouTube search history and Netflix recommendations
00:17:44 Allen's test with Two Voice Devs transcripts
00:21:32 Issues with counting and hallucinations
00:24:21 Testing with OpenAI's Sora AI synthetic videos
00:30:05 Ethical questions and the future of content creation
00:31:50 Potential use cases for large context windows
00:36:34 API limitations and challenges
00:37:39 Performance and cost considerations
00:41:34 Comparison with retrieval augmented generation and vector databases
00:44:21 Generating summaries and markers from this transcript
Leave your thoughts and questions in the comments below!
