Which makes sense, because of you have looked into search and crawlers you notice that search is actual quite expensive (which is why e.g. Kagi charges a few bucks for search every month).
The model wasted over half the token budget, each time, on internal debates over the current date.
When generating a World Cup summary, for example, it refused to believe qualification rounds were over and refused to even call the web searching tool to collect the data.
I injected the current datetime at the very beginning of the system prompt, but Gemma refused to believe it!
The m-effer insisted the timestamp was fake and hypothesized it was being evaluated in a synthetic lab test with simulated future dates!
No amount of system prompting could convince it to trust the clock.
That was the most frustrating and bizarre "bug" I ever faced!
I've noticed Qwen3.6 struggles a bit with today/date based logic.
Only after some cajolling it finally went to check the history I asked it to (I had been testing KoboldCPP's web search).
I wonder how much that extends to using LLMs for programming. I assume most knowledge of programming language syntax still comes from training data.
Were you expecting your model to be updated on current events? Why?
Also the specific event you are referring to is a statistically very improbable event, prior to its actually happening.
>It only acquiesced when I specifically directed it to check Reuters.
Do all models do this? They check in with Reuters? Why would a model think that you asking about an extremely improbable event warranted reaching out to Reuters?
I can teach myself to play an instrument, and I'm not just building this huge lookup table that I have to access every time I play the instrument. I am updating the weights in my neurons.
Until AI can do this it's not AGI in my book.
It’s clearly warranted because a model that trusts its weights on current events will give an outdated answer. Extremely improbable events happen all the time.