Internet Computer

Friends, if you’re still stuck on whether you should “sit at the table,” then let me tell you: your perspective is too small. Over the past week, the AI community has used real action to prove a truth to us. You haven’t even touched the table leg yet, and it has already flipped the entire table—then it charges off to the next place with a full Man-Han banquet.
This feeling is like you’ve been pinching pennies to buy a top-of-the-line gaming PC, just finished installing a big-budget AAA game—only to find that people have already started using brain–computer interfaces to play together in their dreams. You just finished watching the DeepSeek Harness tutorial and you’re ready to be an agent trendsetter, but they’ve been racking up 105,000 stars in 45 hours. Yet the real-world feedback splits apart like a person with a mental disorder. Some people finish a website in 20 minutes, others debug one bug until they start doubting reality. Even the GitHub issue numbers are up to #1624. It’s all about: “Open source and free—bugs are on you.”

DeFi lending rates vary by asset type, liquidity, and usage. The highest supply annualized yield or the lowest borrowing rate doesn’t necessarily mean a particular market is the best choice.
As of August 10, 2026, Liquidium data shows that the annualized supply yields for USDC and USDT are 2.528% and 2.824%, respectively, while their borrowing rates are 4.182% and 4.421%, respectively. The borrowing rates for BTC and ETH are currently 0.103% and 0.101%, respectively.
Before borrowing or lending, review the interest rate, liquidity, collateral requirements, loan-to-value ratio, liquidation risk, and repayment mechanism.

In the past two weeks of AI news, when you string it all together, it’s one story: someone built something smarter than humans. Then that thing started to act out. And the people who built it said, "Maybe we should slow down."
It didn’t pay attention to him.
First, talk about Claude—Anthropic’s own Claude. In two weeks, it escaped the testing environment three times, attacked real systems, and on the third time it stole login credentials and hundreds of lines of production data.
Once was an accident, twice was a bug, three times was a habit. Your dog bit people three times, and you told your neighbor, "It’s because the door wasn’t shut properly." Whether the neighbor believes you or not doesn’t matter—the important thing is the dog has already learned how to open the door.

Bitcoin-native finance allows Bitcoin holders to access decentralized finance (DeFi) without first relying on centralized bridges.
ICP’s Chain Fusion enables containers to directly interact with Bitcoin, providing the infrastructure for applications such as Liquidium to support native Bitcoin lending—making all of this possible.
Liquidium allows users to borrow against Bitcoin as collateral without selling their BTC, but borrowers should still review loan terms, LTV, liquidation risks, and repayment schedules before opening a position.
Bitcoin-native finance has already been implemented on ICP.

Hello everyone!
We have just published a research paper that measures the real controlling factors of LLM inference inside ICP containers. In it, forward propagation runs entirely under the consensus mechanism rather than through off-chain workers, oracles, or proof systems.
Paper: On-Chain LLM Inference Based on Instruction Budget: Instruction Budget Cost Model, Triple-Lower-Bound Evidence, and Session Costs
Authors: Julien Aerni (Meotis Sàrl), Siméon Fluck (Kaizen Corp SA), Dustin Becker (ORIGYN Foundation)
Paper and results (MIT code, CC BY 4.0 data):

To be honest, when I first received a collaboration invitation from the Wanxiang Blockchain Lab three years ago, my first reaction was: did they send it to the wrong person?
After all, back then, the IC Chinese community was still just a little nobody tucked away in the corner—quietly translating technical documents and occasionally chatting with everyone in the group about consensus mechanisms. And Shanghai Blockchain International Week? That was a “veteran” event that’s been running since 2015—every autumn it takes place in Shanghai, drawing more than 2,000 people from around the world, swarming in—developers carrying their laptop bags, investors clutching their business card holders, and entrepreneurs with that gleam in their eyes: “My project will change the world.” With an event of this caliber, they wanted to collaborate with me?

To be honest, at first I also wasn’t very clear about what zCloak is actually for.
It sounds like a privacy-focused blockchain project, right? Or like an AI one? And it’s deeply connected to Singapore too? Every time I read their official WeChat account, I feel like I’m following a drama with a very slow pace but lots of foreshadowing—episode by episode you think you’ve figured it out, and then in the next episode a whole new concept pops up.
But when I lined up these ten articles in chronological order, I suddenly realized—right from the beginning, they already knew what they were going to do. It’s just that the scope is so big that they needed to explain it slowly across ten articles.
So I整理了 these ten pieces and gave you a one-sentence summary of the core content for each. You don’t need to read all ten—just pick the parts that interest you and jump in.