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    Astra user says it still lacks taste and direction

    A user reports twice exhausting their Pro limits using only Astra, yet still describes it as “just a code monkey”—albeit “the best we have.”

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    GM
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    20 Sources, ,

    TLDR

    One Astra user says heavy use left them unconvinced it represents artificial general intelligence. Their main criticism is that it isn't opinionated and lacks taste: in their view, it doesn't really know what to do, leaving them wasting time and tokens. Despite that frustration, they still call it the best coding assistant they have.

    Combined views

    1M

    20 Sources, first seen 23d ago

    Combined views

    1M

    20 Sources, first seen 23d ago

    5.6K likes
    23d ago
    first seen 23d ago
    5.6K likes
    308 comments
    1.4K saves
    136 reposts
    308 comments
    1.4K saves
    136 reposts

    Sentiment

    Positive31.9%68.1%Negative

    Summary

    Sentiment

    Positive31.9%68.1%Negative

    Replies largely criticized Astra as a major disappointment due to its smaller-than-expected scale and rejected hype around massive GPT-6 teacher models, though some welcomed naming patterns or economic AGI views.

    Based on 76 sentiment-bearing replies from 69 accounts across 7 conversations.

    Summary

    Replies largely criticized Astra as a major disappointment due to its smaller-than-expected scale and rejected hype around massive GPT-6 teacher models, though some welcomed naming patterns or economic AGI views.

    Based on 76 sentiment-bearing replies from 69 accounts across 7 conversations.

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    20 Sources

    @scaling01after having burnt twice through my Pro limits using Astra exclusively, I can say that I don't feel the AGI the biggest issue is that its still not opinionated and lacks taste. it doesn't really know what to do, so it just does whatever and you end up wasting time and tokens. also I don't believe the rumors that it's 10T+. If it is, then scaling laws are truly cooked. My divine impeccable vibes, which work 1 out of 7 times, tell me that it's 6-8T. overall it's still just a code monkey. although a slightly larger one and the best we have. I would like to refer you to one of my articles: LLMs aren't AGI, but it doesn't matter (we are taking off anyway)
    @GaryMarcus⚠️ The most important question hardly anyone is asking is whether Jensen meant 100K+ GPUs, or 100k+ NVLink72 server racks (which contain 72 Blackwell GPUs). ⚠️ From his wording, it sure looks like the latter to me. If he indeed meant 100k+ NVLink72 server racks, we can infer that the hardware to train Astra sells for something like a quarter trillion dollars. Rental prices would perhaps be in the low tens of billions. For an improvement that @EpochAIResearch shows is not off trend. One key foundational problem with this whole industry (aside from technical limits of LLMS) is that you have two trends; exponential increases in training costs, modest increases in performance. Couple that with price wars and all of this is absolutely insane. It’d be like a gas company paying exponentially more money for each extra million barrels in the midst of a massive price war. That can’t last. Nor can this.
    @DanielleFongok let me explain something to you guys. you have to understand that today, if the AI is a massive jump in capabilities in understanding vosual and 3d, then it is able to bootstrap thinking bridges from this massive corpus of reasoning, the real world, and other visual and mental models, and the ones we have connected to. it doesn't mean that it's *magic* and it's not instantaneous. it doesn't magically have all the abilities, all the permutations. you usually have to draw it out. but once you do draw it out, it can be massively more able -- drawing on its trillions wide weights and further reasoning. it still has quirks, but it's quite general -- which takes work, but which it's happy to coordinate and have you do anyway. you guys can argue if this is completely general or whatever but it already very general and frankly more general than your average human, and superhuman in coding. suggestion: try making a 3d environment and work within that. see what internalization, physicalization evokes in the model, as a philosophical being.
    @teortaxesTexOK, after investigating a bit, I've learned that a) "Doug" is the base model of GPT-6/Astra, sorry for misinformation b) "Bel" is insider bro bullshit, and the pretrain that's been started maybe < 2 months ago has some other codename (not that this changes much)
    @rohanpaul_aiRT @rohanpaul_ai: Jensen Huang just confirmed the number. GPT-6 Astra was trained on ~100K+ NVIDIA Grace Blackwell NVLink72. And that 400…
    @SchmidhuberAI@JensenHuang @ChaseLochmiller @OpenAI belated reply

    20 Sources

    @scaling01after having burnt twice through my Pro limits using Astra exclusively, I can say that I don't feel the AGI the biggest issue is that its still not opinionated and lacks taste. it doesn't really know what to do, so it just does whatever and you end up wasting time and tokens. also I don't believe the rumors that it's 10T+. If it is, then scaling laws are truly cooked. My divine impeccable vibes, which work 1 out of 7 times, tell me that it's 6-8T. overall it's still just a code monkey. although a slightly larger one and the best we have. I would like to refer you to one of my articles: LLMs aren't AGI, but it doesn't matter (we are taking off anyway)
    @GaryMarcus⚠️ The most important question hardly anyone is asking is whether Jensen meant 100K+ GPUs, or 100k+ NVLink72 server racks (which contain 72 Blackwell GPUs). ⚠️ From his wording, it sure looks like the latter to me. If he indeed meant 100k+ NVLink72 server racks, we can infer that the hardware to train Astra sells for something like a quarter trillion dollars. Rental prices would perhaps be in the low tens of billions. For an improvement that @EpochAIResearch shows is not off trend. One key foundational problem with this whole industry (aside from technical limits of LLMS) is that you have two trends; exponential increases in training costs, modest increases in performance. Couple that with price wars and all of this is absolutely insane. It’d be like a gas company paying exponentially more money for each extra million barrels in the midst of a massive price war. That can’t last. Nor can this.
    @DanielleFongok let me explain something to you guys. you have to understand that today, if the AI is a massive jump in capabilities in understanding vosual and 3d, then it is able to bootstrap thinking bridges from this massive corpus of reasoning, the real world, and other visual and mental models, and the ones we have connected to. it doesn't mean that it's *magic* and it's not instantaneous. it doesn't magically have all the abilities, all the permutations. you usually have to draw it out. but once you do draw it out, it can be massively more able -- drawing on its trillions wide weights and further reasoning. it still has quirks, but it's quite general -- which takes work, but which it's happy to coordinate and have you do anyway. you guys can argue if this is completely general or whatever but it already very general and frankly more general than your average human, and superhuman in coding. suggestion: try making a 3d environment and work within that. see what internalization, physicalization evokes in the model, as a philosophical being.
    @teortaxesTexOK, after investigating a bit, I've learned that a) "Doug" is the base model of GPT-6/Astra, sorry for misinformation b) "Bel" is insider bro bullshit, and the pretrain that's been started maybe < 2 months ago has some other codename (not that this changes much)
    @rohanpaul_aiRT @rohanpaul_ai: Jensen Huang just confirmed the number. GPT-6 Astra was trained on ~100K+ NVIDIA Grace Blackwell NVLink72. And that 400…
    @SchmidhuberAI@JensenHuang @ChaseLochmiller @OpenAI belated reply