çemberlerden bisiklete binen pelikan çıkıyor. tam bitti derken kamera dönmeye başlıyor
🤯The leap from planning, reasoning through and pulling this off in tandem to many many pause-worthy real-life tasks is the chasm between people still calling it “just software or lines of code” and those calling for a pause before this all gets recursively untraceable.
What??? So Google's engineers wasted so much time prepping RL envs to teach Gemini how to do this fourier approximation? That's precious space on the manifold. Why not teach it how to solve Riemann's hypothesis?
This is cool.
#Argon
Replying to @googleaidevs
@googleaidevs make it available for student plan Google one ai pro please
5. 鹈鹕骑自行车(傅立叶圆周运动版)
xitter.cf/fofrAI/status/21100430…
Lol.. never discount a company that has spent years collecting massive data sets,I guess meta and Google are now back in the race.
This feels like a different kind of frontier launch. A pelican on a bike drawn from Fourier math, with the video and the music prompt both made by the model.
Google's own examples point the same way. Argon turned a sketch and a photo of a couch into a correctly sized, printable sofa leg. It watched a video of someone playing cornhole, and a humanoid robot then sank seven shots in a row. It rebuilt Chaco Canyon in 3D from scans and archived drawings.
That's the human side of AI: a sketch, a movement, a photo in, and the craft carried forward. I'd love to see an architect's pencil drawing become a building, or a ballerina's dance become oil paint.
The benchmarks are Google's own and I'm waiting to test it myself, but the direction is the story.
This confirms that Gemini 4 argon is solid because it can make a video of a pelican riding a bike using Fourier epicycles, with time-synced Lyria 3.5 music.
There’s a good chance I’m going to take every bad thing I said about Gemini back




















