@stablekwon Hello @stablekwon I'm going to pen this down from a place of hurt and brokenness. Coming from a heart filled with pain for my own mistake of not properly doing my due diligence even tho I'm nit exactly a fan of any Terra ecosystem
Truth be told, I didn't care for anything /1
Sera is the world's only FX Onchain venue.
FX Onchain Trading Season 1 is launching 1 June 2026.
Claim 10,000 gSera bef 31 May 2026: https://t.co/UgInW3gvbS
Sera is the world's only FX Onchain venue.
FX Onchain Trading Season 1 is launching 1 June 2026.
Claim 10,000 gSera bef 31 May 2026: https://t.co/UgInW3gvbS
very many important apps are being built on Base.
venice is here. @StrikeRobot_ai is here and $VVV ecosystem is building hot.
stay focused and @buildonbase
I bumped into a Venice ecosystem token yesterday @StrikeRobot_ai and since then I haven't taken my eyes off it.
Here is how to train the robots in simple steps:
This is one of the clearest examples of where AI + robotics infrastructure is heading.
A fully integrated training pipeline where natural language becomes real-world robotic deployment.
Here’s the breakdown 👇
Step 1: User Prompt
The process begins with simple natural language. A user describes the robotics environment or task they want to create.
No manual environment engineering.
No traditional simulation setup complexity.
Just intent → generation.
Step 2: Text-to-CAD Generation
The system converts prompts into physics-aware 3D environments and CAD assets automatically.
This is important because: The environment becomes simulation-ready, instantly, assets understand physical constraints training can scale dramatically faster AI generated worlds become executable.
Step 3: RL Training (Isaac Lab)
Now reinforcement learning enters the loop. Policies are trained inside high-speed physics simulations where robots repeatedly learn:
movement
navigation
manipulation
optimization
The simulation environment continuously improves policy behaviour.
Step 4: Sim-to-Real Scoring
This is the critical bridge most people underestimate. The system validates which simulated behaviours are robust enough for real hardware deployment. Not every simulation works in reality.
This layer filters weak policies before physical deployment.
Step 5: Fleet Deployment
Validated policies are rolled out directly to humanoid fleets.
Meaning:
one successful training cycle can scale across many robots simultaneously. This is where robotics starts behaving like software infrastructure.
The bigger narrative here:
AI is evolving from: text generation to physical world automation
The stack now looks like:
Prompt → Environment → Simulation → Optimization → Deployment
And whoever owns this pipeline could own a major part of the future robotics economy.
Follow my recent tweet here: https://t.co/XVRCJWORaj
Big milestone: @LitecoinVM has officially joined @CoinMarketCap’s CMC Labs accelerator 🔥
This is a major step for LitVM and the Litecoin ecosystem as this scales Hard Money Web3 to a global audience.
With CMC’s reach and resources, the team is bringing Litecoin-powered innovation to millions of new users, builders, and believers worldwide.
.@legiondotcc opens a new token raise April 30 in partnership with @nansen_ai.
Most people don't know Nansen runs NX8, an index token tracking the top 30 cryptos that rewards holders with points over time. That product is co-built with @opendelta_.
I'm deploying capital with all things being equal. Let's see how this plays out.
1) PLUR Has been Printed on Solana ✌️🖨️
Trade and Stake on @printr : https://t.co/qfNfw2syUi
7 Days of rewards with 100% of our team's staking fees for:
Staking PLUR, Trading on @tryfomo , Creating Content, and Referring Other Stakers👏
The ones who made it all started the same way. They staked $1 and stopped asking questions. You can keep watching, or you can join.
$1 to $1
BUVSTjCb9F17HF5mmBBjHbLau92r9LGNRGPKDxj6brrr