GM. gArc
Crypto trading gets easier when news, charts, and AI analysis come together.
@TheARCTERMINAL brings these tools into one place:
→ ANIMA AI: Analyzes markets and potential opportunities.
→ The Feed: Highlights news that could impact prices.
→ Perpetual Trading: Connects analysis with trading.
→ User Control: AI suggests, but you make the final decision.
AI can simplify market research, but profits are never guaranteed.
That’s what makes ARC Terminal worth watching.
Do you think AI will become essential for crypto traders?
GM. gArc
Crypto trading gets easier when news, charts, and AI analysis come together.
@TheARCTERMINAL brings these tools into one place:
→ ANIMA AI: Analyzes markets and potential opportunities.
→ The Feed: Highlights news that could impact prices.
→ Perpetual Trading: Connects analysis with trading.
→ User Control: AI suggests, but you make the final decision.
AI can simplify market research, but profits are never guaranteed.
That’s what makes ARC Terminal worth watching.
Do you think AI will become essential for crypto traders?
Good morning gZeru
The latest research from @zerufinance gives me another reason to keep watching ZeruAI.
The team analyzed 3,374 token launches to study early ownership, developer selling, and how quickly trading activity fades after launch.
What stands out to me is the focus on behavior, not just wallet rankings or reputation scores.
• Tracking ownership concentration
• Identifying developer selling patterns
• Understanding post-launch behavior
• Measuring how quickly market activity declines
This is where ZeruAI gets interesting. Onchain data can do more than describe wallets; it can help explain market behavior and uncover patterns that basic metrics might miss.
I’m supporting @zerufinance because the team keeps exploring practical ways to make onchain behavior more meaningful.
GM gVangrid
What interests me about @vangrid_io is how it turns everyday environments into potential data sources for the next generation of AI.
Instead of relying only on existing digital data, Vangrid focuses on capturing real-world spaces and converting them into structured 3D data for robotics, simulations, and AI world models.
Here’s why this matters:
- Real-world spatial data can make AI simulations more realistic.
- A distributed network can help capture environments as they change.
- On-chain verification helps establish the provenance of contributed data.
Physical AI is still evolving, and the infrastructure being built today could play an important role in its future.
Excited to see how @vangrid_io continues to develop this vision.
GM gVangrid
What interests me about @vangrid_io is how it turns everyday environments into potential data sources for the next generation of AI.
Instead of relying only on existing digital data, Vangrid focuses on capturing real-world spaces and converting them into structured 3D data for robotics, simulations, and AI world models.
Here’s why this matters:
- Real-world spatial data can make AI simulations more realistic.
- A distributed network can help capture environments as they change.
- On-chain verification helps establish the provenance of contributed data.
Physical AI is still evolving, and the infrastructure being built today could play an important role in its future.
Excited to see how @vangrid_io continues to develop this vision.







