4 ms·

I'm curious if the knowledge cutoff is important, when the interface (Gemini app) can search online for recent information. Is there a big advantage to having

• j-bu 1mo ago
  Not directly - but latest research advancements, cleaner / richer datasets, etc. still require fresh base models. Not everything can be fixed through post training alone (e.g. why GPT-5.5 "Spud" was such a big jump, and also why GPT-6 "Astra" is now supposedly another big leap). Ofc model size etc also plays a role, but my (admittedly limited) understanding is that new base models _can_ also lead to big jumps even keeping parameter counts constant.
• npn 1mo ago
  very important actually. just try to generate code for fresher frameworks/libraries. gemini sucks so bad in real work usage, everything it suggests are outdated and mostly useless.
• rjh29 1mo ago
  Search grounding is expensive, you can't force the model to do it either. I use Gemini a lot and it often replies with out-dated data. The more detailed the information you're asking, the more likely it is to be wrong.
• StevenWaterman 1mo ago
  You don't need everything internal, but having some idea of recent events is useful. If you ask it to implement some local AI there's a decent chance it will try to use qwen 2.5 without wondering if anything better came out since
• neuronic 1mo ago
  [dead]
• spider-mario 29d ago
  Sometimes, it’s quite presomptuous and doesn’t search when it should. I’ve had to argue too many times with it that, yes, the Nintendo Switch 2 is real.