4 ms·
Interesting. It's claiming different knowledge cutoff dates depending on the question asked. "Who is president?" gives a "April 2024" date.
by SparkyMcUnicorn 1y ago
Interesting. It's claiming different knowledge cutoff dates depending on the question asked.
"Who is president?" gives a "April 2024" date.
- ethbr1 1y agoQuestion for HN: how are content timestamps encoded during training?
- tough 1y agothey arent. a model learns words or tokens more pedantically but has no sense of time nor cant track dates
- svachalek 1y agoYup. Either the system prompt includes a date it can parrot, or it doesn't and the LLM will just hallucinate one as needed. Looks like it's the latter case here.
- manmal 1y agoTechnically they don’t, but OpenAI must be injecting the current date and time into the system prompt, and Gemini just does a web search for the time when asked.
- tough 1y agoright but that's system prompting / in context not really -trained- into the weights. the point is you can't ask a model what's his training cut off date and expect a reliable answer from the weights itself. closer you could do is have a bench with -timed- questions that could only know if had been trained for that, and you'd had to deal with hallucinations vs correctness etc just not what llm's are made for, RAG solves this tho
- stingraycharles 1y agoWhat would the benefits be of actual time concepts being trained into the weights? Isn’t just tokenizing the dates and including those as normal enough to yield benefits? E.g. it probably has a pretty good understanding between “second world war” and the time period it lasted. Or are you talking about the relation between “current wall clock time” and questions being asked?
- tough 1y agothere's actually some work on training transformer models on time series data which is quite interesting (for prediction purposes) see google TimesFM: https://github.com/google-research/timesfm https://github.com/google-research/timesfm what i mean i guess is llms can -reason- linguistically about time manipulating language, but can't really experience it. a bit like physics. thats why they do bad on exercises/questions about physics/logic that their training corpus might not have seen.
- tough 1y agoOpenAI injects a lot of stuff, your name, sub status, recent threads, memory, etc sometimes its interesting to peek up under the network tab on dev tools
- Tokumei-no-hito 1y agostrange they would do that client side
- cma 1y agoClaude 4's system prompt was published and contains: "Claude’s reliable knowledge cutoff date - the date past which it cannot answer questions reliably - is the end of January 2025. It answers all questions the way a highly informed individual in January 2025 would if they were talking to someone from {{currentDateTime}}, " https://docs.anthropic.com/en/release-notes/system-prompts#may-22th-2025 https://docs.anthropic.com/en/release-notes/system-prompts#m...
- polynomial 1y agoI thought best guesses were that Claude's system prompt ran to tens of thousands of tokens, with figures like 30,000 tokens being bandied about. But the documentation page linked here doesn't bear that out. In fact the Claude 3.7 system prompt on this page clocks in at significantly less than 4,000 tokens.
- deleted 1y ago[deleted]