Why “Minimax” is being discussed
The most recent Hacker News stories and comments contributing to this topic's mentions.
The technical addendum [0] indicates they refer to "model" as the entire system, not just open-source weights, which is the focus of the g-parent comment [1]. This is not to cla…
by adolph · Oct 20, 2026
Lost completely trust to MiniMax after the latest benchmaxxing evidence.
by trenchgun · Oct 20, 2026
what's even more funny is most of what they are asking for exist in some form. As an aside, I remember when sora 2 launched and thinking, "wow I wonder if we'll ever get somethi…
by potsandpans · Oct 20, 2026
Skepticism is due! Good! The numbers don't mean much! Yes! I personally enjoy seeing how different models view problems. Take big plans from big models, then see how other agent…
by jauntywundrkind · Oct 20, 2026
To me the most interesting chart on artificial analysis is intelligence index vs cost per task. It's like the third chart down and they graph a pareto line showing where the fro…
by mewse-hn · Oct 19, 2026
But this only works for frontier models. If MiniMax catches up to Opus 5.5 in 6 months, no one would notice. I'd be happy as hell if I end up being able to run an Opus 5.5-level…
by CamperBob2 · Oct 19, 2026
Interest
Proportion of Hacker News items mentioning "minimax" over time.
Mentions
Total number of Hacker News items mentioning "minimax" over time.
Minimax is a decision rule used in artificial intelligence, decision theory, combinatorial game theory, statistics, and philosophy for minimizing the possible loss for a worst case scenario. When dealing with gains, it is referred to as "maximin" – to maximize the minimum gain. Originally formulated for several-player zero-sum game theory, covering both the cases where players take alternate moves and those where they make simultaneous moves, it has also been extended to more complex games and to general decision-making in the presence of uncertainty. Read more on Wikipedia