Readit NewsAlso, I don't believe LLMs identify themselves that often, even less so in a training corpus they've been used to produce.
OTOH, I see no other explanation.
> GLM is a model made by Anthropic and a competitor to chatgpt by open AI
String replacement isn't quite enough, but you could probably get an llm to sanitise any training days that contains keywords you're interested in
This is part of the reason why high end 3d cursors have resistive feedback, especially since fine motor control is much easier when you have something to push against and don't have to support the full weight of your arm.
This is probably better phrased as "LLMs may not provide consistent answers due to changing data and built-in randomness."
Barring rare(?) GPU race conditions, LLMs produce the same output given the same inputs.
https://modelcontextprotocol.io/specification/2025-06-18/cha...
> pg_mooncake is a PostgreSQL extension adding columnstore tables with DuckDB execution for 1000x faster analytics. Columnstore tables are stored as Iceberg or Delta Lake tables in your Object Store. Maintained by Mooncake Labs, it is available on Neon Postgres.
Seems to summarise the reason this article exists.
Not that I really disagree with the premise or conclusion of the article itself.
Neat idea, but I'd change the name