Axis Robotics Indonesia

Axis Anti-Bot Update Data quality is our absolute bottom line. At Axis, we are building the foundational dataset for physical AI, and we are committed to ensuring a fair environment where the efforts of real contributors are protected and rewarded. Recently, system monitoring and community feedback revealed cheating activities. Some users were reverse-engineering task conditions to directly forge trajectories, severely compromising data purity. To stop this, we implemented a strict Replay Logic in our backend. Last week, we launched a brand-new data format with expanded scene dimensions for precise physical replay, deliberately leaving a 3-day buffer for frontend cache updates. Despite this, our monitors showed that around 5% of wallets continued to submit faked, old-format data. While 5% seems small, their bots rapidly drained available task slots, stealing opportunities from real users. Following a comprehensive data backtrack, we have locked onto these wallets. They are now permanently banned, and all their occupied slots are being instantly reopened to genuine contributors. We also noticed early signs of a few genuine users experimenting with these exploits. Consider this a formal warning: we are letting it pass this time, but moving forward, any cheating attempts will result in an immediate and permanent ban. We will keep iterating our anti-cheat algorithms to protect our fair, high-quality ecosystem. Thank you to the majority of our community for your authentic supports. Below is a google sheet containing the list of banned addresses👇

Top 10 on Base for a month now. 🔵 Robots on @base ⬇️

@axisrobotics gAxis

You bring the vibes 🥞 We bring the Axis merch 👕 and some fresh alpha (✱,✱) See you in HK! 🔵

At Axis, every trajectory submitted by our community undergoes a strict replay validation process. We run each submission through checker to verify whether the target task was successfully completed. To see how strict it is, check this demo (Task: Place The Toy Train On The Board Game Box). Real human data passes smoothly (Video 1). However, bots or manually altered data will fail (Video 2). Why? Faking numbers breaks the simulation's physics causality. Even tiny tweaks cause error accumulation, resulting in failed movements. This invalid data is automatically rejected. Because of this mechanism, data submitted via bots will ultimately fail our replay verification. Invalid data is strictly excluded from model training, and the task slot is reopened to the community to collect genuine, high-quality trajectories. Furthermore, we actively monitor for duplicated data. Trajectories that are identical lack the diversity required for robot learning and will not be credited by our scoring system. If we detect accounts submitting a massive volume of identical trajectories, all associated addresses will be permanently banned. For Axis, the quality and diversity of data are the only ways to solve the robotics generalization gap. They will always be our absolute top priorities.

sudah saatnya

@Deekyaja gAxis

@racyunoy Siomay + batagor = combo maut aowk

lebih suka batagor atau siomay?

GM, Akhirnya akun ini bisa pulih kembali🙏

gAxis 🇮🇩 @axisrobotics