# $TAO Social Sentiment & Intelligence — 2026-09-17 07:10 UTC

> **Asset:** $TAO  
> **Momentum Status:** Fading Quickly  
> **Timestamp:** 2026-09-17 07:10 UTC (2026-09-17T07:10:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-09-17-07-10/crypto/TAO  
> **Overview Brief:** https://cryptitalk.com/2026-09-17-07-10/crypto.md  

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## 10-Minute Social Metrics
- **Posts Analyzed:** 2
- **Total Impressions:** 111
- **Likes:** 6
- **Retweets:** 0
- **Comments:** 2

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## Momentum & Sentiment Analysis
Total Engagement - Comments: 2, Retweets: 0, Likes: 6, Impressions: 111


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## Cited Community Posts & Evidence


### Post #1 by @Jaxxx_eth
> **Author:** [@Jaxxx_eth](https://x.com/Jaxxx_eth)  
> **Metrics:** 30 likes · 0 retweets · 23 comments · 349 views  


> **Source Link:** [https://x.com/Jaxxx_eth/status/2100476093220241526](https://x.com/Jaxxx_eth/status/2100476093220241526)  


> **Visual Context:** A graphic titled 'ROBOT DATA NEEDS A PAPER TRAIL' showing a table with fields for TASK ID, CONTRIBUTOR, DATA ID, and BASE TX, with the note '5M+ TRAJECTORIES ON BASE'.  

> 
> "Physical AI has a provenance problem.

Who collected the run?
Which task was it for?
Which policy did it train?
@axisrobotics
 is solving this with onchain provenance on 
@base
.

Every accepted trajectory gets a Data ID tied to the task and contributor wallet. You can trace it"


### Post #2 by @Mekarly
> **Author:** [@Mekarly](https://x.com/Mekarly)  
> **Metrics:** 216 likes · 0 retweets · 42 comments · 3.1K views  


> **Source Link:** [https://x.com/Mekarly/status/2100476637401788703](https://x.com/Mekarly/status/2100476637401788703)  


> 
> "AI in trading shouldn’t be about creating more information. It should be about helping traders understand what actually matters.

For me, one of the biggest use cases for AI is filtering out market noise and turning relevant information into clearer context.
@MEXC
 AI approaches"




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## Contributing Accounts

- `@CryptoMavka` (https://x.com/CryptoMavka)

- `@LuigiProof` (https://x.com/LuigiProof)