As of: 2026-10-14 00:22 CEST.
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Canonical page: https://postcutoff.com/v/google-deepmind-gemini-4-argon-humanoid-cornhole/

# Teaching a humanoid robot to play cornhole with Gemini 4 Argon

Google DeepMind, 13 October 2026, YouTube. 33,930 views as of 13 October 2026.
Kind: Official.
Watch: https://www.youtube.com/watch?v=9PICEmtfpWU

## Why it is here

Google DeepMind's launch-day demo for the Gemini 4 Argon general release (1:44), the most-viewed of Google's launch videos on YouTube so far. Per the description: in an internal test Argon watched a video of a human playing cornhole, built a MuJoCo simulation and computed whole-body control for Apptronik's Apollo 2 humanoid, which sank seven consecutive shots; Google calls it a 'Video-to-Sim-to-Real pipeline' that 'compresses weeks of manual modeling into a few hours'. Vendor demo, not independently checked.

## Description (written by Gemini from the video)

**Summary**  
Google DeepMind research engineer Rohan Thakker presents an experiment testing whether Gemini 4 Argon can control an Apptronik Apollo humanoid robot to learn and execute playing cornhole. The model observes human demonstrations via the robot's cameras, models and practices throws inside a MuJoCo physics simulator, and iteratively refines its real-world throwing technique from visual feedback.

**What is shown**  
* [00:00 - 00:05] Apollo humanoid robot throwing a beanbag cleanly into the cornhole board; title overlay: *"Gemini 4 Argon x Robotics"*.  
* [00:05 - 00:08] Introduction by Rohan Thakker, Research Engineer at Google DeepMind.  
* [00:08 - 00:12] Web prompt UI (*Apollo real2sim Cornhole*, running *Gemini 4 Argon*) prompting the robot to record a demonstration using its left eye camera.  
* [00:13 - 00:16] A researcher tossing a beanbag while the robot watches.  
* [00:17 - 00:20] Side-by-side comparison of Apollo 2's left eye camera feed and the MuJoCo simulator mirroring the motion.  
* [00:21 - 00:30] Initial trial throws on hardware, showing misses alongside telemetry and code logs of joint positions, velocities, and error analysis.  
* [00:31 - 00:36] Successful beanbag throw directly into the target hole; engineers cheer.  
* [00:37 - 00:41] Apollo celebrates with arm gestures and speech.  
* [00:42 - 00:46] User prompt requesting a 20-second summary of the methodology with accompanying gestures in sim.  
* [00:47 - 01:25] Apollo articulates its 4-step approach (motion mapping from video, stereo camera 3D estimation & physics setup, simulation tuning including widening stance to 52 cm for a 7.2 cm balance margin, and real-world iterative correction).  
* [01:26 - 01:36] Thakker detailing Gemini 4 Argon's multimodal reasoning, error diagnosis from video, and experiential learning.  
* [01:37 - 01:43] Montage of direct cornhole shots and the closing *Gemini 4 Argon* title card.

**Claims & numbers**  
* The presenter claims they tested whether Gemini 4 could control a humanoid robot to solve a dynamic physical task (cornhole).  
* In simulation, the model widened the robot's stance to 52 cm to boost its balance margin to 7.2 cm (shown at [01:07]).  
* Apollo claims it adjusted its release on the physical robot by a few centimeters until sinking 7 consecutive shots straight into the hole.  
* The presenter claims Gemini 4 can autonomously reason over video footage of failures to diagnose mechanical errors and improve control policies iteratively.

**Notable quotes**  
* [00:05] *"In this experiment we're basically trying to see if we can teach Gemini 4 to control a humanoid robot to solve cornhole."* — Rohan Thakker  
* [00:38] *"Woohoo! Airmail, straight in the hole. Let's go!"* — Apollo / Gemini 4  
* [01:20] *"...and adjusted my release by a few centimeters until we sank seven shots straight in the hole."* — Apollo / Gemini 4  

**Assessment**  
This is an official demonstration video produced by Google DeepMind showcasing Gemini 4 Argon's multimodal reasoning in a real-to-sim-to-real robotics framework. The footage showcases real robot hardware and simulation environments, though the presentation is polished and time-condensed with cuts across the trial and error iterations.

_Described by gemini-3.8-flash on 2026-10-13 from the video's audio and frames._

## Related

- 2026-10-13: [Google releases Gemini 4 Argon broadly](https://postcutoff.com/e/2026-10-13-gemini-4-argon-general-availability/)