Most Web3 projects have one problem: They can create hype. But can they create revenue? Nahhhhh. Because for any project to survive long term. it needs active users and real revenue. And the numbers are brutal: 1 in 4 crypto projects collapsed within just six months of launch. But when we talk about @NEARProtocol ... the story is different. NEAR launched in 2020, and it is still growing today. Watch the full video for a breakdown of NEAR’s revenue and buybacks 👇👇

Just NEAR and nothing 🔥

Good morning cutie π

It is looks interesting. just joined @traceforms NFT whitelist.

Near to the moon 🔥 $NEAR

$KII has been getting harder to ignore lately. What caught my attention isn’t just the price action it’s the activity behind it. A few things stand out: > Volume picked up significantly across recent sessions > $KII is showing up on Binance Alpha > Trading activity around the token has clearly become more noticeable > More attention is now coming back to the market The interesting part is the combination of price movement + volume + renewed attention. » No predictions » No price targets Just looking at what’s already happening around $KII. Take a look at the chart and judge the market activity for yourself. @KiiChainio Watch The Following Video For Interactive Details About $KII

Good morning bebes 😘 Near 💅

Good Morning guys bebes 😘. We are watching near protocol today. It just crossed $3.2.

Near Crossed 3$ 😘 $NEAR

Whitelist is open. Apply: zecpunks.xyz You have 72 hours.

Just quick update guys 🥱

New Delhi 🇮🇳 went from the timeline to the table. India’s community is building in person. Follow @NearIndia for events, meetups, and what’s next in the region.

From interacting online to meeting in real life.. this transition felt so good & memorable NEAR brought us together, the merch made it official 💚

> What if you could self-custody your crypto without ever writing down a 24-word seed phrase ? ✦ That’s the idea behind @bronwallet In DROPS 43, Dmitry @tokarev_d Tokarev breaks down why Bron was built. > how its seedless MPC wallet works & > why he thinks the traditional seed phrase model is becoming outdated. Self-custody without the seed phrase. 🎥 Watch the clip 👇 @KevinWSHPod

Just update guys 🫡

Just Near things 🔥

If You Are Bored Of Doing Stimmy Airdrops Here's An Intresting Oppurtunity For You... NEAR @3.33 is more than just a number ✦ Users bring confidential intents → activity flows into the ecosystem → TVL grows → eligible users unlock rewards. The whole system is designed to reward participation. NEAR @3.33 🟢 Confidential Intents. Real Rewards. Who’s getting involved? 👀 $NEAR Wath The Video For Better Understanding ♡

We all know AI is getting smarter. But making AI work in the real physical world is a much harder problem. This is where @axisrobotics comes in. Most AI works with text, images, audio, or code. Physical AI is AI that can understand and act in the real world. For example a robot that can: • Pick up a cup • Open a drawer • Move objects • Sort things • Use different tools • Work in different environments But for this to work robots need a lot of training. And that brings us to the biggest problem is Data. ➢ Why do robots need so much data? Think about ChatGPT. AI models can learn from huge amounts of text available on the internet. Robots do not have that advantage. You can not simply download the internet and teach a robot how to: 'Pick up this cup from this exact position.' Robots need examples of humans actually performing tasks. They need experience. ➢ This is the problem Axis is trying to solve. Axis is building data infrastructure for Physical AI. The idea is simple: Humans → generate robot demonstrations → data → AI training → better robots Instead of only relying on expensive physical robots. Axis uses simulation to make data collection easier and more scalable. This creates an interesting loop. More people → More demonstrations → More training data → Better robot models → More testing → More failures and corrections → More useful data → Better robots. And the cycle continues. This is what Axis calls a compounding data engine. ➢ So what is Axis Robotics? In simple words: Axis is building a system that helps robots learn from human experience at scale. It connects: Humans + Simulation + Data + AI Models + Robots The bigger idea is simple: AI became powerful because it had huge amounts of data to learn from. Physical AI needs the same thing. Massive amounts of diverse real-world experience. And Axis is trying to build the infrastructure to provide exactly that.