Giving away 2 max bags at launch. $HOODLOAN is not only lending, we are actively giving back to the community, ensuring growth and innovation in that space.
To participate:
•Use /invite to get your invite link
•Invite real active members and not bot
•Follow the official X acc and stay active
•Top 2 on the leaderboard get rewarded
After launch, the first 30 minutes will be a 50% topup, means anybody buying 100$ gets 50$ for free.
Privacy by design. 🔒
Hood Proof lets you verify your capital without exposing private keys, seed phrases, or your entire portfolio.
Prove the claim. Keep the keys.
Hood Loan — capital verification built for DeFi.
https://t.co/hnz8hqXKoa
#robinhood#defilending#hoodproof #privacy #defi #crypto
From capital to credit. 🔒
Verify what you own. Unlock borrowing power. Borrow, repay, and build your on-chain credit history.
Hood Loan — Verify. Borrow. Repay. Build. 🟢
#hoodloan#defi#defilending#onchain#robinhoodchain
Prove your capital. Unlock your credit.
Your wallet shouldn’t have to expose everything to prove you’re capitalized.
Hood Proof turns verifiable on-chain capital into portable claims — without private keys, seed phrases or wallet custody.
Verify. Prove. Borrow. Repay. Build credit.
#RobinHoodChain #Rh #Hoodloan #ethereum #utility
Giving away 2 max bags at launch. $HOODLOAN is not only lending, we are actively giving back to the community, ensuring growth and innovation in that space.
To-do‘s: - Shill the recent pinned post : https://t.co/R6f8Oplwgb
- Invite 5 people (proof in dms to @ola_zee0
- Follow our https://t.co/UjAk9LDWrb
After launch, the first 30 minutes will be a 50% topup, means anybody buying 100$ gets 50$ for free.
The coolest part of Microduck might not be the robot. It's how it learns to move.
This repo shows the full reinforcement learning pipeline behind Microduck.
The robot learns in simulation using MuJoCo, PPO and GPU-based training, then the trained policy is exported to ONNX and deployed on the real robot.
But the real challenge is sim-to-real.
The simulation models things like actuator behavior, battery voltage, command delays, friction and even gear backlash. That helps make the learned policy work when it moves from simulation to the physical robot.
The repo includes policies for walking, fall recovery, sitting, standing, kicking, ground picking and even roller skating.
Train in simulation. Test the behavior. Export the policy. Run it on a real robot.
We have a huge news to share today!
Today we are unveiling the first truly accessible RL robot - welcome Microduck
A 25 cm tiny open-source biped with 15 actuators and packed with sensors (camera, speaker, LiDAR, NFC, bluetooth, wifi, etc) that you train yourself with reinforcement learning.
It's also playable out of the box with more than half a dozen fun and playful pre-trained policies to have it walk, sit, crouch, roller-skate, pick up objects with its articulated beak, and recover on its own.
And all for less than $400.
See all the details, play with the simulator and order it at: https://t.co/n1Btgs6vKw
(video with sound on 🔊)