151–160 of 722 posts
Google is absolutely running away with it. The greatest trick they ever pulled was letting people think they were behind.
Gemini's UX (and of course privacy cred as with anything Google) is the worst of all the AI apps. In the eyes of the Common Man, it's UI that will win out, and ChatGPT's is still the best.
Gemini has been way behind from the start.
They use the firehose of money from search to make it as close to free as possible so that they have some adoption numbers.
They use the firehose from search to pay for tons of researchers to hand hold academics so that their non-economic models and non-economic test-time-compute can solve isolated problems.
It's all so tiresome.
Try making models that are actually competitive, Google.
Sell them on the actual market and win on actual work product in millions of people lives.
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…
Google is absolutely running away with it. The greatest trick they ever pulled was letting people think they were behind.
Peacetime Google is not like wartime Google. Peacetime Google is slow, bumbling, bureaucratic. Wartime Google gets shit done.
Arc-AGI-2: 84.6% (vs 68.8% for Opus 4.6) Wow. https://blog.google/innovation-and-ai/models-and-research/ge...
I'm excited for the big jump in ARC-AGI scores from recent models, but no one should think for a second this is some leap in "general intelligence". I joke to myself that the G in ARC-AGI is "graphical". I think what's held back models on ARC-AGI is their terrible spatial reasoning, and I'm guessing that's what the recent models have cracked. Looking forward to ARC-AGI 3, which focuses on trial and error and explorin…
"100% of tasks have been solved by at least 2 humans (many by more) in under 2 attempts. The average test-taker score was 60%."
Arc-AGI-2: 84.6% (vs 68.8% for Opus 4.6) Wow. https://blog.google/innovation-and-ai/models-and-research/ge...
I'm excited for the big jump in ARC-AGI scores from recent models, but no one should think for a second this is some leap in "general intelligence". I joke to myself that the G in ARC-AGI is "graphical". I think what's held back models on ARC-AGI is their terrible spatial reasoning, and I'm guessing that's what the recent models have cracked. Looking forward to ARC-AGI 3, which focuses on trial and error and explorin…
Google is absolutely running away with it. The greatest trick they ever pulled was letting people think they were behind.
It's a shame that it's not on OpenRouter. I hate platform lock-in, but the top-tier "deep think" models have been increasingly requiring the use of their own platform.
Arc-AGI-2: 84.6% (vs 68.8% for Opus 4.6) Wow. https://blog.google/innovation-and-ai/models-and-research/ge...
I'm excited for the big jump in ARC-AGI scores from recent models, but no one should think for a second this is some leap in "general intelligence". I joke to myself that the G in ARC-AGI is "graphical". I think what's held back models on ARC-AGI is their terrible spatial reasoning, and I'm guessing that's what the recent models have cracked. Looking forward to ARC-AGI 3, which focuses on trial and error and explorin…