Chapter
Multi-resolutional Language Models for AI
1:50:17 - 1:58:19 (08:02)
The potential for multi-resolutional language models in AI allows for the selection of the most useful data based on the context of the user's needs, creating a more efficient and effective system. However, there is a need to balance larger and faster systems with coherent models for a better AI experience.
Clips
The GPGC model is capable of performing certain transformations in text and using them for training.
1:50:17 - 1:55:00 (04:43)
Summary
The GPGC model is capable of performing certain transformations in text and using them for training. It is expected to be used in the training data for future machine learning models like GPT-4 and GPT-5, which are expected to be able to deal with video on an extended transformer scale.
ChapterMulti-resolutional Language Models for AI
Episode#212 – Joscha Bach: Nature of Reality, Dreams, and Consciousness
PodcastLex Fridman Podcast
The development of multi-resolutional systems for language models, with varying focuses on different segments of reading and learning, could lead to gaps in knowledge being filled and a more comprehensive understanding of information.
1:55:00 - 1:58:19 (03:18)
Summary
The development of multi-resolutional systems for language models, with varying focuses on different segments of reading and learning, could lead to gaps in knowledge being filled and a more comprehensive understanding of information. A fully recurrent model with more degrees of freedom would be necessary for accurate predictions.