331–340 of 359 posts
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what is Google Antigravity?
Couple patterns this could follow Speed? (Flash, Flash-Lite, Antigravity) this is my guess. Bonus: maybe Gemini Diffusion soon? Space? (Google Cloud, Google Antigravity?) Clothes? (A light wearable -> Antigravity?) Gaming? (Ghosting/nontangibility -> antigravity?)
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Google was never really late. Where people perceived Google to have dropped the ball was in its productization of AI. The Google's Bard branding stumble was so (hilariously) bad that it threw a lot of people off the scent. My hunch is that, aside from "safety" reasons, the Google Books lawsuit left some copyright wounds that Google did not want to reopen.
Google’s productization is still rather poor. If I want to use OpenAI’s models, I go to their website, look up the price and pay it. For Google’s, I need to figure out whether I want AI Studio or Google Cloud Code Assist or AI Ultra, etc, and if this is for commercial use where I need to prevent Google from training on my data, figuring out which options work is extra complicated. As of a couple weeks ago (the last t…
Benchmarks from page 4 of the model card: | Benchmark | 3 Pro | 2.5 Pro | Sonnet 4.5 | GPT-5.1 | |-----------------------|-----------|---------|------------|-----------| | Humanity's Last Exam | 37.5% | 21.6% | 13.7% | 26.5% | | ARC-AGI-2 | 31.1% | 4.9% | 13.6% | 17.6% | | GPQA Diamond | 91.9% | 86.4% | 83.4% | 88.1% | | AIME 2025 | | | | | | (no tools) | 95.0% | 88.0% | 87.0% | 94.0% | | (code execution) | 100% | -…
Not sure 360 days is enough of a sample really but it's an interesting take on AI benchmarks.
Are there any other interesting benchmarks to look at?
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Google was catastrophically traumatized throughout the org when they had that photos AI mislabel black people as gorillas. They turned the safety and caution knobs up to 12 after that for years, really until OpenAI came along and ate their lunch.
It still haunts them. Even in the brand-new Gemini-based rework of Photos search and image recognition, "gorilla" is a completely blacklisted word.
It is interesting that the Gemini 3 beats every other model on these benchmarks, mostly by a wide margin, but not on SWE Bench. Sonnet is still king here and all three look to be basically on the same level. Kind of wild to see them hit such a wall when it comes to agentic coding
Gemini 3 Pro gets 31.1% on ARG-AGI-2
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A legally binding pinky swear LOL
with fineprint somewhere on page #67, that there are exceptions.
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Wow. They must have had some major breakthrough. Those scores are truly insane. O_O Models have begun to fairly thoroughly saturate "knowledge" and such, but there are still considerable bumps there But the _big news_, and the demonstration of their achievement here, are the incredible scores they've racked up here for what's necessary for agentic AI to become widely deployable. t2-bench. Visual comprehension. Comput…
SWE-Bench Verified | 76.2% | 59.6% | 77.2% | 76.3% is actually insane.