✦ ΞVA

Exploring Web3 through art, perspective & human experience 🌿

Discovering @Soneium
~Ambassador @AGNT_hub

[✦ ΞVA @0xevaaa]

@0xPritom @agenticscredit How does Agentics determine when a trader is ready for real funding rather than just performing well on paper?

[✦ ΞVA @0xevaaa]

@Pixelclipz For someone new to https://t.co/0mxLLM7onj what does the project actually do and what makes it different from other DeFi platforms?

[✦ ΞVA @0xevaaa]

@0GxPanDa @zerufinance Do borrowers pay interest on these loans..
and how do lenders earn returns?

[✦ ΞVA @0xevaaa]

@DigsdotHQ @RebateLaunch What kind of projects can launch on RebateLaunch and how does the platform work for users?

[✦ ΞVA @0xevaaa]

@madlimen Rewards are nice but people need a reason to stick around even after the rewards slow down..

[✦ ΞVA @0xevaaa]

@Shadowri_ft Good night bro

[✦ ΞVA @0xevaaa]

@Shadowri_ft @2FactorFinance Yeah that’s what makes it interesting…

[✦ ΞVA @0xevaaa]

Crypto leverage usually means funding fees or sudden liquidation

@2FactorFinance does it differently: Splits BTC into BTC-Sr (stable + yield) and BTC-Jr (~1.33x, no liquidation)

Kelly optimized for buy-and-hold investors

Join here👇🏻

https://t.co/uugMnk5fzA

[✦ ΞVA @0xevaaa]

@madlimen @2FactorFinance Let’s gooo🔥

[✦ ΞVA @0xevaaa]

@RuhollahSeddigh 👏🏻👏🏻👏🏻

[✦ ΞVA @0xevaaa]

@Route2FI Love seeing more accessible ways to approach long term investing
Excited to see what you build next

[✦ ΞVA @0xevaaa]

@berkanagaa

[✦ ΞVA @0xevaaa]

@Route2FI Leverage that’s built for the long game
Really interesting approach to compounding growth…

[✦ ΞVA @0xevaaa]

@berkanagaa

[✦ ΞVA @0xevaaa]

@0xVaha Pretty much
Closing that gap is what actually separates demos from useful physical ai

[✦ ΞVA @0xevaaa]

Training in simulation is one thing
Making those skills actually transfer is another

What really matters is whether a robot can still perform when object positions change and conditions aren’t identical

That’s a core challenge in building adaptable Physical AI
Impressive work✨

[Axis Robotics @axisrobotics]

Simulation provides scalable expertise. Vision distillation brings it to reality.

We are training RL experts in simulation and distilling them into vision policies that generalize.

Here's a pick-and-place expert that handles objects placed at random.

[✦ ΞVA @0xevaaa]

@_Bitcorn Yeah…, real world messiness like that is exactly where a lot of sim trained policies break
The gap between clean simulation and greasy, imperfect hardware is still one of the hardest parts

[✦ ΞVA @0xevaaa]

@_ZaricX @axisrobotics That’s one of the key parts they’re building around…, capturing the messy, imperfect

human adjustments is actually the point
The data includes the noise and corrections not just clean demos

[✦ ΞVA @0xevaaa]

Anyone can help train robots now🤖
No expensive hardware. No lab needed.
Just a browser and a bit of curiosity

That’s what makes @axisrobotics different

Physical AI doesn’t have to stay locked behind closed doors

It can be built by people everywhere🌎

[✦ ΞVA @0xevaaa]

But how do robots learn to interact with the real world?
It all starts with diverse,high quality data

That’s one of the reasons I’m excited about what @axisrobotics is building🌿

Join the Axis fam and stick around
not everyone is ready for the journey🫡

https://t.co/VQvt4QLvz5

[✦ ΞVA @0xevaaa]

@kane_tdt @axisrobotics Not everyone will but the system doesn’t rely on perfect contributions from everyone
Quality filters + the compounding loop help surface the useful data over time

[✦ ΞVA @0xevaaa]

@sheikhakash69 @axisrobotics Yeah that’s the quiet engine behind it
Failures aren’t just noise…, they become the signal for better data

[✦ ΞVA @0xevaaa]

Data trains better models.
Better models reveal new failures..
Those failures guide the next data we collect…

This quiet loop is what @axisrobotics is building.

Not just more data… data that compounds and improves over time.

That’s how Physical AI actually scales🍃

[✦ ΞVA @0xevaaa]

@uthman_000 @axisrobotics Even the ones that don’t work still feed the loop as long as the lessons actually shape the next data we collect
That’s the compounding part