Gemini 4 Argon taught Apptronik's Apollo cornhole from one video: seven straight landings, one more than NASA's Apollo

Gemini 4 Argon taught a humanoid cornhole from one human video

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Argon watched a person play, located the board with the robot's cameras, wrote its own MuJoCo simulation to practise in, then adjusted its throws on Apptronik's Apollo until it sank seven in a row. Google says this cuts weeks of manual simulation work to hours, and Argon scores 87% on the ERQA embodied-reasoning benchmark (Google).

Awe, with doubts about the setup. @normandipalo, who ran it: "I'm still half in disbelief" (112K). r/singularity's top reply: "Whatever timeline you think you have in your head for robotics and AI. It is faster." Another: "Always tossing from the same location? ... This feels like overfit".

1. Physical Intelligence opens its robot models to other companies

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The Pi API beta lets teams upload robot data, fine-tune Pi's models on its compute and run them through hosted inference. Early users include Actor's driverless wheel loader and Almond, whose Axol learned to deburr parts after four days with the API (blog).

@svlevine: "Even a year ago I don't think I would have believed that PI models can run on such a huge range of different robots." @giffmana: "Thinky but for robotics?", wondering if latency hurts "if you're not close to their servers".

Heat: medium · 231K views, 38 posts (171K on the launch) · quiet on Reddit

2. Tesla brings FSD v14 Lite to older Model S and X

Tesla confirmed v14.3 Lite is rolling out to HW3 Intel Model S and X for the first time, alongside v14.3.12, a bug-fix release for HW4 cars that keeps "Automatic Collision Evasion" (@TeslaNewswire).

Owners are impressed. @paulg: "The Tesla Model 3 with FSD is mind-blowing", after it drove him to the gym and backed into a space (2.0M). @elonmusk: "Tesla self-driving feels like magic" (2.0M).

Heat: high · 4.1M views, 13 posts · quiet on Reddit

3. Dyna's Taku robot rings Nasdaq's closing bell

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Dyna Robotics' Taku joined RoboStrategy, a Nasdaq-listed fund that buys into private robotics companies, for the ceremony (@beincrypto).

Read as robotics going mainstream. @FundaAI: robotics "may become the next focus of competition, driving a second wave of compute demand." @RoboDaily: "A big accomplishment for the @RoboStrategy team today."

Heat: medium · 144K views, 8 posts · quiet on Reddit

AlphaNIST: one robot policy learns 20 assembly tasks from a pass/fail reward

A team building NVIDIA's Isaac Lab trained a single policy from scratch, with no demos and just a binary success reward (plus a small control cost), that solves all 20 NIST assembly-board tasks at 98.2% training success in simulation. A separately trained policy chains ten in a row. It matters because sparse-reward RL found dexterous strategies its authors say they couldn't have designed, though only in simulation so far.

Frontier LLMs driving real robots doubled their scores every six weeks

Robocurve ran frontier models on real-robot tasks adapted from HKU and Berkeley's RoboDojo benchmark: scores rose from 15% in July to 48% in September, costs halved every three weeks, and all 960 runs are public. It matters because general models are climbing a real-hardware benchmark fast, with runs anyone can audit.