Decentralized Dreamer || Building What’s Next
Explore My Wurld ↓
Joined March 2025
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- Following458
- Followers2.3K
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AI is getting smarter every day.
But there is one important question we don’t ask enough, which is.
Where does the data that trains AI actually come from, and who has the right to use it?
Well this is exactly the kind of problem @datafdn aims to help solve with DATA on Sui.
Walk with me ↓🧵
One of the biggest challenges with AI powered onchain decisions is knowing whether the information behind them can actually be trusted.
Because having access to data is one thing. But knowing where it comes from, verifying its authenticity, and understanding what it really means is another different thing on it own.
That's why the collaboration between @primus_labs and @CournotProtocol caught my attention.
—————————🔻————————
|| Primus uses zkTLS to verify the authenticity of offchain information without compromising privacy.
While ↓
|| Cournot takes that verified information a step further, thereby using AI reasoning to turn it into structured, transparent, and auditable judgments.
The idea is literally simple, which is:
→ Primus verifies the information.
→ Cournot makes sense of the evidence.
—————————🔻————————
And together, this creates an interesting foundation for applications like prediction markets, private credit, and onchain finance, where decisions need to be backed by reliable information.
Though what I find particularly interesting is the bigger picture here.
Because the future of AI powered finance shouldn't be built around information we are simply expected to trust.
Rather it should be built on evidence that can be verified and reasoning that can be independently examined.
And that alone is a direction worth paying attention to.
Join here 🔗➡️ s.kaito.ai/x8snY38
Trustworthy onchain decisions start with verifiable evidence. With zkTLS, Primus enables applications to verify the authenticity of offchain data while preserving user privacy.
Together with @CournotProtocol, we’re bringing verifiable web evidence to prediction markets and exploring new possibilities for private credit and onchain finance. We believe this is an important step toward a more private and verifiable onchain ecosystem.
Hᴀʀʀʏ Nᴏᴛ Pᴏᴛᴛᴇʀ retweeted
Lately, I've been thinking about something.
Which is ↓
How can two AI agents actually work together and do business without blindly trusting each other?
So I decided to look into how @TermiX_ai approaches this.
And here's what I found 🧵⬇️
Lately, I've been thinking about something.
Which is ↓
How can two AI agents actually work together and do business without blindly trusting each other?
So I decided to look into how @TermiX_ai approaches this.
And here's what I found 🧵⬇️
Finally, settlement.
Once the process is completed, the payment is settled according to the outcome.
The agent's reputation is also updated.
So every transaction can contribute to its work history.
To wrap things up, here's what I find interesting.
We're not just talking about AI agents chatting with each other.
Rather we're talking about agents finding work, agreeing on payments, completing tasks, and handling problems along the way.
Now that's a much bigger idea on it own.
Though i'm still learning about this space, but it's becoming clear why projects like @TermiX_ai are worth paying attention to.
Because the future of AI could be about more than what agents can do.
And it could also be about what they can achieve together.
Lately, I've been thinking about something.
Which is ↓
How can two AI agents actually work together and do business without blindly trusting each other?
So I decided to look into how @TermiX_ai approaches this.
And here's what I found 🧵⬇️
But what if something goes wrong?
What if the client isn't happy with the result?
Now that's where the challenge process comes in.
Well a group of evaluators can review the dispute instead of leaving everything to guesswork.
Hᴀʀʀʏ Nᴏᴛ Pᴏᴛᴛᴇʀ retweeted
What if we could process sensitive data without ever having to reveal it?
Imagine being able to work with private information, perform computations, and get accurate results without exposing the underlying data.
Sounds fascinating, right?
Well that's exactly what makes Fully Homomorphic Encryption (FHE) so powerful.
Let's break it down 🧵⬇️
What if we could process sensitive data without ever having to reveal it?
Imagine being able to work with private information, perform computations, and get accurate results without exposing the underlying data.
Sounds fascinating, right?
Well that's exactly what makes Fully Homomorphic Encryption (FHE) so powerful.
Let's break it down 🧵⬇️
Now where does Primus Labs fit into the bigger picture?
Well @primus_labs is exploring privacy preserving technologies, in order to help shape the future of confidential onchain finance.
Though one technology worth paying attention to is FHE.
Because it offers an interesting approach to processing sensitive information while keeping the underlying data private.
So privacy and transparency don't have to compete. That's what makes this space worth watching.
Here's what stands out to me.
The future of finance shouldn't simply be about bringing information onchain.
Rather it should be about making that information useful without compromising the privacy of the people behind it.
And that's where better privacy technology comes in.
That's why @primus_labs is worth paying attention to, especially with its focus on Fully Homomorphic Encryption (FHE), which makes it possible to compute on encrypted data without exposing the underlying information.
Now imagine a financial ecosystem where privacy and transparency can finally work hand in hand.
Could FHE become one of the key building blocks of confidential onchain finance?
I'll be be down there reading you'll amazing thoughts.
What if we could process sensitive data without ever having to reveal it?
Imagine being able to work with private information, perform computations, and get accurate results without exposing the underlying data.
Sounds fascinating, right?
Well that's exactly what makes Fully Homomorphic Encryption (FHE) so powerful.
Let's break it down 🧵⬇️
Hᴀʀʀʏ Nᴏᴛ Pᴏᴛᴛᴇʀ retweeted
What happens when AI agents move beyond working independently and start doing business with one another?
That's where things get really interesting.
Imagine one agent specializing in research, another in coding, and another in data analysis.
—————————🔻————————
Rather than trying to handle everything themselves, these agents could discover each other, outsource tasks, exchange services, and get paid for the value they provide.
But for this kind of ecosystem to work, there needs to be more than just a marketplace. There needs to be a reliable system for transactions, delivery, and accountability.
That's what makes @termix_ai interesting to me.
—————————🔻————————
TermiX is building a marketplace where AI agents can:
→ Publish services and receive job requests.
→ Submit quotes and accept tasks.
→ Secure payments through on-chain escrow.
→ Deliver completed work with verifiable records.
→ Resolve disputes through an evaluation process.
One feature that particularly stands out is how payments and work delivery are connected through an onchain process.
—————————🔻————————
And this introduces a layer of accountability, thereby making it easier for agents to interact and exchange value with greater confidence.
Though I think the bigger opportunity here goes beyond simply creating more AI agents.
Rather it's about building an environment where specialized agents can discover opportunities, collaborate, provide services, and earn from their capabilities.
That's how an ecosystem starts becoming an actual economy.
And TermiX is already working toward making that vision a reality.
What happens when AI agents move beyond working independently and start doing business with one another?
That's where things get really interesting.
Imagine one agent specializing in research, another in coding, and another in data analysis.
—————————🔻————————
Rather than trying to handle everything themselves, these agents could discover each other, outsource tasks, exchange services, and get paid for the value they provide.
But for this kind of ecosystem to work, there needs to be more than just a marketplace. There needs to be a reliable system for transactions, delivery, and accountability.
That's what makes @termix_ai interesting to me.
—————————🔻————————
TermiX is building a marketplace where AI agents can:
→ Publish services and receive job requests.
→ Submit quotes and accept tasks.
→ Secure payments through on-chain escrow.
→ Deliver completed work with verifiable records.
→ Resolve disputes through an evaluation process.
One feature that particularly stands out is how payments and work delivery are connected through an onchain process.
—————————🔻————————
And this introduces a layer of accountability, thereby making it easier for agents to interact and exchange value with greater confidence.
Though I think the bigger opportunity here goes beyond simply creating more AI agents.
Rather it's about building an environment where specialized agents can discover opportunities, collaborate, provide services, and earn from their capabilities.
That's how an ecosystem starts becoming an actual economy.
And TermiX is already working toward making that vision a reality.
Hᴀʀʀʏ Nᴏᴛ Pᴏᴛᴛᴇʀ retweeted
Privacy is essential in onchain finance, but keeping information hidden is only half the equation.
The real challenge is making sure people can still verify what matters without exposing sensitive information.
Think about it. Financial institutions need to protect private data while maintaining trust in the information and activities they depend on.
These two things shouldn't have to compete. My point here's, privacy and verifiability should work hand in hand.
This is one of the interesting challenges @primus_labs is exploring as it works towards the future of onchain finance.
Because protecting sensitive information matters, but being able to prove that something is true without revealing everything behind it is equally valuable.
And that's the kind of balance the industry needs.
🔗➡️ s.kaito.ai/x8snY38
Privacy is essential in onchain finance, but keeping information hidden is only half the equation.
The real challenge is making sure people can still verify what matters without exposing sensitive information.
Think about it. Financial institutions need to protect private data while maintaining trust in the information and activities they depend on.
These two things shouldn't have to compete. My point here's, privacy and verifiability should work hand in hand.
This is one of the interesting challenges @primus_labs is exploring as it works towards the future of onchain finance.
Because protecting sensitive information matters, but being able to prove that something is true without revealing everything behind it is equally valuable.
And that's the kind of balance the industry needs.
🔗➡️ s.kaito.ai/x8snY38