• ikt@aussie.zone
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    2 months ago

    At the core it’s all still running the same Markov chains as the machine learning experiments from the dawn of computing

    Sure but tanks today at their core still look like tanks from ww2, when things work well they work well, when did Mixture of Experts for example start to apply to deep learning? Can you think of anything else outside of compute and training that helps AI? What about building a search engine around the ability for it to get and summarise sources (perplexity)?

    For us to see another leap in progress we’ll need to pioneer new calculations and formulate different types of thought, then find a way to integrate that with large transformer networks.

    To be fair AI is already incredible, ai generated music/video/images are already getting billions of views and coding agents are already generating millions of lines of code every day and AI is already being utilised heavily in heathcare, learning, translation, military… this was posted earlier today:

    Ukrainian sniper pulls off record 4-km shot that killed two Russians. Yes, it took AI

    Rifle Used: 14.5 mm Snipex Alligator, an anti-materiel rifle originally meant to destroy equipment, not personnel. Its official effective range is 2,000 m—only half the distance achieved in this shot.

    • Guidance Tools: The sniper used AI-assisted targeting and drone surveillance to calibrate the record-breaking strike.

    https://euromaidanpress.com/2025/08/17/ukrainian-sniper-4km-ai-shot/

    Now whether we get to AGI is a whole other thing, that I agree would need a major leap

    • absentbird@lemmy.world
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      2 months ago

      Mixture of experts has been in use since 1991, and it’s essentially just a way to split up the same process as a dense model.

      Tanks are an odd comparison, because not only have they changed radically since WW2, to the point that many crew positions have been entirely automated, but also because the role of tanks in modern combat has been radically altered since then (e.g. by the proliferation of drone warfare). They just look sort of similar because of basic geometry.

      Consider the current crop of LLMs as the armor that was deployed in WW1, we can see the promise and potential, but it has not yet been fully realized. If you tried to match a WW1 tank against a WW2 tank it would be no contest, and modern armor could destroy both of them with pinpoint accuracy while moving full speed over rough terrain outside of radar range (e.g. what happened in the invasion of Iraq).

      It will take many generational leaps across many diverse technologies to get from where we are now to realizing the full potential of large language models, and we can’t get there through simple linear progression any more than tanks could just keep adding thicker armor and bigger guns, it requires new technologies.

      • ubergeek@lemmy.today
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        2 months ago

        nd modern armor could destroy both of them with pinpoint accuracy while moving full speed over rough terrain outside of radar range (e.g. what happened in the invasion of Iraq).

        lol, that is NOT what happened in Iraq. The tanks were sitting on low boy trucks for the vast majority of the invasion. How do I know this? Because they were in my convoys.

        Even for major offensives after the initial invasion, that’s not at all what happened. They were basically employed as large mortars, sitting about a half mile outside of a town, and leveling it.