林向兰

[Aethir @AethirCloud]

The Aethir Cloud Drop is ongoing, and we have exciting news for the @Azuki community 🪂🔥

Aethir is airdropping to the @Azuki community as a token of appreciation for our mutual support and dedication to our shared vision.

To check eligibility 👇🏻
🔹 Simply connect your wallets on the Aethir cloud drop platform, and you can check if you are eligible for the badge. If you are, then the badge will be LIVE for you.

Let's seize the opportunity; visit https://t.co/jUF9HasWQ1 to check if you are eligible 🚀

[林向兰 @XiangLin14455]

Register for the Analog Incentivized Testnet https://t.co/8dEo0pEIvX

[sqd.ai @helloSQD]

Today, we're launching the Subsquid Points Program, with the first phase live on @CoinList.

This is Subsquid's very first airdrop campaign!

Join here: https://t.co/7CU4Feurw1

[Space and Time @spaceandtime]

Proof of SQL is the only way to ZK prove data source, storage, and compute in a database.

Connect verifiable queries against 100TB of preloaded Web3 data indexed from major chains (and your own offchain datasets) to your smart contract.

Prove your queries sub-second.

Only with Space and Time.

[sqd.ai @helloSQD]

To celebrate the occasion, we have teamed up with some of our amazing partners, including @CoinList, @okxweb3, @lavanetxyz, @Neon_EVM, and @stackdotso.

Complete quests using their platforms to earn!

Full details: https://t.co/TVMyPNC9oI

[sqd.ai @helloSQD]

Data Lakes and Data Layers are not the same.

But they're a perfect combination for devs looking for decentralized data access.

[林向兰 @XiangLin14455]

Verifying my Twitter account for my #GalxeID gid:XtuaidkjxNhLN46eKhm9HK @Galxe

https://t.co/AilAOq7pb5

[sqd.ai @helloSQD]

Just passing by. Catch us if you can.

[林向兰 @XiangLin14455]

Join the $SQD Launch team. Big things are coming to Subsquid!

https://t.co/VB7DEfBfuH

[林向兰 @XiangLin14455]

https://t.co/WLSTR4Khzf

[林向兰 @XiangLin14455]

Register for the Analog Incentivized Testnet https://t.co/8dEo0pEIvX https://t.co/8dEo0pEIvX

[林向兰 @XiangLin14455]

Exciting News! @OneAnalog 's incentivized Testnet registration is officially LIVE!
Don't miss the chance to join this groundbreaking experience.
Sign up now to secure your spot and unlock exclusive rewards!
#AnalogTestnet https://t.co/8dEo0pEaGp

[Analog 🕓⛓️ @OneAnalog]

🚨 ANNOUNCEMENT ALERT! 🚨
Registration for the upcoming Analog Testnet launch is now OPEN! 🥳
Be among the first to experience the cutting-edge features of our platform. 🎉
Ready to dive into the future? Sign up today! 👇
https://t.co/VrJKoZVUJH
#AnalogTesnet

[Space and Time @spaceandtime]

As enterprise LLM usage accelerates and AI is more deeply integrated into core business processes, verifiability becomes more important than ever.

When it comes to AI, brand trust is no longer adequate. Enterprises leveraging LLMs need to be able to provide consumers, litigators, lawmakers, and stakeholders with answers to questions such as…

🟣 What datasets were used to train/fine-tune an LLM? Did these datasets contain any copyrighted content or protected IP?
🟣 Was sensitive data removed prior to training (or prior to populating a vector search database to be retrieved in prompts)?
🟣 Are user requests being processed with the correct LLM binaries and weights? When using a third-party-hosted LLM service, can you trust that the third party has not manipulated responses?
🟣 Has any sensitive IP been accidentally sent over to a third-party LLM service due to RAG processes?
🟣 How do we put managerial processes in place to govern and approve prompts in the codebase or AI agent flows that use enterprise datasets?
🟣 How do we certify a piece of content as authentic to an organizational source and verify its provenance?

In this SxT blog, Space and Time Co-Founder and CTO @chiefbuidl walks through the process and challenges of delivering an end-to-end verifiable LLM system: starting with a tamperproof and sanitized training dataset, then ultimately proving correct model usage and watermarking generated content.

When realized, verifiable LLMs will provide better…
‍
✅ Trustworthiness
✅ Accuracy and reliability
✅ Customization
✅ Authenticity of content

Space and Time is focused on introducing verifiability into a few key steps in this process, using ZK and blockchain tech to cryptographically prove the data used for training, fine-tuning, and RAG of LLMs.

Read the blog post here: https://t.co/62fLwv7Evt

[林向兰 @XiangLin14455]

Space and Time (@spaceandtime) is the verifiable compute layer that scales zero-knowledge proofs on a decentralized data warehouse to deliver trustless data processing to smart contracts, LLMs, and enterprises.

Learn more at https://t.co/9oPaINCHEi.

[林向兰 @XiangLin14455]

#MindNetwork #FHE #Restake https://t.co/Ud3RbLCEwa

[Mind Network @mindnetwork_xyz]

📣How is #MindNetwork using Fully Homomorphic Encryption (#FHE) to scale AI/Depin network security and how can FHE augment #Restaking？

Check out the thread and our latest article to learn more: https://t.co/zIyIDuDel8

[林向兰 @XiangLin14455]

Want to get started building on Space and Time? @spaceandtime

Check out the developer docs: https://t.co/76rEyXCIlE

[Sign @Sign]

🚀 Win up to 50% of airdrop with the 6-week #SignX Program! For aspiring builders looking to build on Sign Protocol, this is your time to shine:

🗓️: 3/20 - 4/25/2024
🏆: Hackathons, Airdrops, Quests, Exclusive NFTs...
✍️: Submit your ideas now!

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[林向兰 @XiangLin14455]

https://t.co/aCzpPvcwRs

[林向兰 @XiangLin14455]

https://t.co/XlMemdaAFx