From: redpointai
Understanding the capabilities and limitations of language models requires a deep grasp of their underlying theory [00:00:08]. While agents can be well-connected with the capabilities of language models in some areas [00:00:00], this is not universally true [00:00:06].
Capabilities
Language models excel at tasks that involve mixing and matching elements present in their training data [00:00:20]. They can be highly effective for:
- Answering or labeling emails [00:00:26]
- Adding CSS to HTML [00:00:32]
- Iteratively debugging common Python problems [00:00:35]
Limitations
Language models struggle significantly with tasks requiring novel planning sequences that are not almost exactly present in their training data [00:00:12], [00:00:16]. This includes:
- Independently creating a research breakthrough [00:00:40].
- Generating novel algorithms, even if they are short (e.g., four or five lines of code), because such algorithms are by definition not found in the existing training data [00:00:51], [00:00:55].