← Back to context

Comment by WarmWash

15 hours ago

For heavyweight work I have been using Astra, but for rabbit holes and brain storming Gemini is far more enjoyable to interact with.

I'm worried in their push to catch up on the SOTA front, it's going to lose that natural sounding touch it currently has.

Agreed. My impression is that the more verbose output of sol, astra etc is that it helps it steer itself on long running tasks (but is worse for the human user to read)

  • Yes I've noticed there's also this drive to implement and start talking about how it would write specific portions of code in response to design/trade off questions. I have to prompt Sol/Astra almost every time with a note that I am not looking for implementation advice since I mostly use them as a rubber duck in the design phase

How do you know you're using Astra?

My ChatGPT env only says "low", "medium", "high".

Is this a "pro" thing? I have totally no idea what I'm talking to, so actually I'm thinking of stopping my plan. Gemini and Claude are much more clear about it.

Anyway, I like the speed at which Gemini responds so indeed for simple things it is preferable.

  • For me (Plus plan, iOS app), Astra only shows up under the Work tab.

    I’ve been using Work for all my queries, since it seems to just be the same interface as Chat but with more features. I don’t understand why they’re two separate things.

For rabbit holes, how do you get Gemini to do any research before answering? I've very recently had it hallucinate on me like it's 2023, and that was on Pro/Thinking, as far as I remember.

Is Google still chasing frontier? Seems like they haven't had a "Pro" model in forever. I think a good niche for them would be right where they are now.

  • They are. They were supposed to release 3.5 Pro over the summer but haven't because of persistent architectural/technical issues allegedly. Which is better than releasing it in that state imo.

    Their AI leadership team has taken some hits recently too, in the form of departures. I believe when they get their bearings they will be competitive again. 3.8 Flash has been a great model for me.

  • These are native speech-to-speech models, so I think they've decided not to do that anymore.

Mostly because it answers quickly and is more agreeable (too agreeable at times).

Meanwhile Claude and Astra like to couch all their agreements with caveats and provisos.

  • > Meanwhile Claude and Astra like to couch all their agreements with caveats and provisos.

    Sometimes that's what being smart sounds like.

    • This is commonly why, on Reddit in particular, you can get eaten alive.

      Someone confident but incorrect, can often sound more convincing than someone with actual expertise. The expert must add caveats/hedge, because those are the facts on the ground, whereas the person reciting google can be entirely confident.

      Of course the people judging aren't experts, so they side with confidence and simplicity. Heck, just writing shorter replies on Reddit is rewarded. Nobody reads the articles, let alone a paragraph-long reply.

      That all being said though, there are limits. Sometimes LLMs on high-thinking go off on full tangents based on little, and don't have the self-awareness to bring it back.

      4 replies →

  • "couch all their agreements with caveats and provisos."

    When you're a ChatGPT Projects or Claude Projects user, those caveats and provisos are your worst enemy because they'll change caveats into hard rules (either for the session or committed to memories) and you end up in absolute hell having to make it investigate to figure out why it can no longer produce anything but read-only pre-check code that never actually does anything but keeps performing stupid safety checks.

    • Yep the only way out is hooks to forbid what can be detected by ast and second model to prune comments, flatten pyramids of fallback, and squash the test suite removing quirks maintaining wanted behaviors.

  • Yea. I have asked it to verify my ideas with experiments sometimes. And it cheats and warps the results so that the results are reached

It's entirely possible that in their testing of newer models, the whole problem is that even if it's doing better in benchmarks, maybe it's insufferable to work with, thus they're not releasing it.