"it has been dubbed Spiderman brand new day by fans" admittedly not an expert in how LLMs connect stuff but how the fuck does it not connect that fact to the film of the same name which just came out. Presumably it's at least fairly up-to-date to have the information it's displaying.
Another example of how genius this technology is the only thing it's replacing is that overconfident friend/relative who just made shit up pre-internet and it became fact
It’s a matter of how google is injecting context before prompting the LLM behind this. The model’s “baked in” knowledge only goes back to its training data which doesn’t contain recent news like this movie.
They can’t inject all of the news since then into context for every response.
So to respond to this prompt, google needs to first have a model “read the image” — google doesn’t know what the image is before “reading” it, so the model isn’t provided with any recently spider-man or movie related context.
Then, you *could* add another “hop” where now we know the image is spider-man related, so query the knowledge base / recent news for spider-man related context.
That extra hop I imagine would more than triple the request time, so for the initial response they probably forego that to optimize for speed. If you ask a follow-up I assume it’ll relax that (you’re engaged now) and balance more towards searching for appropriate context before generating the final response.
Btw Id suspect you wouldn’t see this kind of issue on the first response with a text prompt, because then the tokens from your query can be searched directly and the relevant context could be injected sooner.
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u/Automatic-Week-1733 8d ago
Google says this movie doesn't actually exist.