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The puzzles are calibrated for human solve rates, but otherwise I agree.
My two elderly parents cannot solve Arc-AGI puzzles, but can manage to navigate the physical world, their house, garden, make meals, clean the house, use the TV, etc. I would say they do have "general intelligence", so whatever Arc-AGI is "solving" it's definitely not "AGI"
Gemini was awesome and now it’s garbage. It’s impossible for it to do anything but cut code down, drop features, lose stuff and give you less than the code you put in. It’s puzzling because it spent months at the head of the pack now I don’t use it at all because why do I want any of those things when I’m doing development. I’m a paid subscriber but there’s no point any more I’ll spend the money on Claude 4.6 instead…
I never found it useful for code. It produced garbage littered with gigantic comments. Me: Remove comments Literally Gemini: // Comments were removed
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Yes, but benchmarks like this are often flawed because leading model labs frequently participate in 'benchmarkmaxxing' - ie improvements on ARC-AGI2 don't necessarily indicate similar improvements in other areas (though it does seem like this is a step function increase in intelligence for the Gemini line of models)
Isn’t the point of ARC that you can’t train against it? Or doesn’t it achieve that goal anymore somehow?
I tell this as a person who really enjoys AI by the way.
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The reflection of the sun in the water is completely wrong. LLMs are still useless. (/s)
It's not actually, look up some photos of the sun setting over the ocean. Here's an example: https://stockcake.com/i/sunset-over-ocean_1317824_81961
Arc-AGI-2: 84.6% (vs 68.8% for Opus 4.6) Wow. https://blog.google/innovation-and-ai/models-and-research/ge...
1. It's an LLM, not something trained to play Balatro specifically
2. Most (probably >99.9%) players can't do that at the first attempt
3. I don't think there are many people who posted their Balatro playthroughs in text form online
I think it's a much stronger signal of its 'generalness' than ARC-AGI. By the way, Deepseek can't play Balatro at all.
Google is absolutely running away with it. The greatest trick they ever pulled was letting people think they were behind.
But wait two hours for what OpenAI has! I love the competition and how someone just a few days ago was telling how ARC-AGI-2 was proof that LLMs can't reason. The goalposts will shift again. I feel like most of human endeavor will soon be just about trying to continuously show that AI's don't have AGI.
I can't shake of the feeling that Googles Deep Think Models are not really different models but just the old ones being run with higher number of parallel subagents, something you can do by yourself with their base model and opencode.
And after i do that, how do i combine the output of 1000 subagents into one output? (Im not being snarky here, i think it's a nontrivial problem)
Google is absolutely running away with it. The greatest trick they ever pulled was letting people think they were behind.
Peacetime Google is slow, bumbling, bureaucratic. Wartime Google gets shit done.