[dosnem]

Anyone understand how this could work? My mental model for llm is predictive text but here how can it understand cell A1 which has a string is the “header” for all values under it? How does it learn to understand table data like that?

[brookst]

LLMs already understand table data. "Predictive text" is somewhat true but so reductive that it leads to that kind of misconception.

HN is going to mangle this but here's a quick table:

| Type of Horse | Average Height | Typical Color | |----------------|----------------|-----------------| | Arabian | 15 hh | Bay, Gray | | Thoroughbred | 16 hh | Chestnut, Bay | | Clydesdale | 17.5 hh | Bay with White | | Shetland Pony | 10.5 hh | Black, Chestnut |

And after a prompt "pivot the table so rows are colors":

| Typical Color | Type of Horse | Average Height | |----------------|----------------------------------------|-----------------------| | Bay | Arabian, Thoroughbred, Clydesdale | 15 hh, 16 hh, 17.5 hh | | Gray | Arabian | 15 hh | | Chestnut | Thoroughbred, Shetland Pony | 16 hh, 10.5 hh | | Bay with White | Clydesdale | 17.5 hh | | Black | Shetland Pony | 10.5 hh |

[bonsai_spool]

> Anyone understand how this could work? My mental model for llm is predictive text but here how can it understand cell A1 which has a string is the “header” for all values under it? How does it learn to understand table data like that?

I imagine it uses the new Agent Skills features

https://www.anthropic.com/news/skills