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I've recently been following a joint statement about “Why open models matter,” and as I read through it, one conclusion is becoming clearer: AI won’t stay confined to just one industry or a handful of companies. It’s more like foundational infrastructure—something that will seep into manufacturing, finance, healthcare, and even the familiar world of crypto and quantitative research.
I agree with one point: open models don’t mean “completely running totally naked.” In terms of safety and cybersecurity, transparency actually makes it easier for the community to spot problems and patch vulnerabilities. And in terms of innovation diffusion, small and medium-sized teams as well as countries can have their own technological sovereignty, instead of forever waiting for someone else to release an API.
Of course, I don’t think open-source and closed-source are opposing zero-sum games. Frontier closed-source models push the ceiling higher, while open models spread capabilities more widely—both are needed.
For someone like me who watches both tech stocks and the AI track, what’s truly worth following isn’t any single model release, but whether this path can remain viable over the long term. If the ecosystem is only closed, innovation costs will be driven up higher and higher. If the open ecosystem is healthy, the application layer will become far more vibrant.
So I see open models as a kind of “public option” in the AI era—not betting on a single winner, but taking its direction seriously (￣▽￣)

My first post I want to talk about something that looks technical but is actually relevant to everyone: why open models are important.
AI will reshape industries and companies, and it will also become the kind of infrastructure that every country is competing to secure. More and more, I feel this isn’t a multiple-choice question of “which model is stronger.” It’s two paths that both need to be taken—frontier closed models and frontier open models. Missing either side makes the picture incomplete.
Closed models can concentrate resources and push to extreme performance; open models are more like spreading capabilities out so that safety, cybersecurity, innovation diffusion, and sovereignty aren’t held by just a few. For someone like me who looks at technology, stocks, and crypto at the same time, this matters a lot: once technical monopolies solidify, costs, regulation, and geopolitical risk will propagate to the market faster.
So I don’t treat this as a slogan. It’s more like a long-term judgment— the deeper AI goes into every industry, the more the balance between openness and closure will determine who can truly participate in the next round of competition (´▽`ʃ♡ƪ)

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Recently I came across a joint letter about “Why open-source models are important.” As an individual creator, I want to jot down a few thoughts.
AI won’t stay only in demos—it will reshape industry division of labor, improve company efficiency, and become basic infrastructure that every country will need to catch up on. My observation is this: open-source models are not merely “cheap substitutes.” They play roles that closed-source models are hard to replace, especially in security audits, the diffusion of innovation, and sovereignty and controllability. With weights and code more transparent, risk discussions don’t have to become nothing but black-box narratives.
I also agree with the second half of the letter: the world needs cutting-edge closed-source work, and it also needs cutting-edge open-source work. It’s like my common experience when looking at the intersection of cryptography and stocks—the winners usually aren’t those who win with a single path, but those who run multiple tracks in parallel, challenging and pushing each other.
Next, I’ll keep an eye on whether the open-source ecosystem truly lowers the barrier to deployment, and how policy can write “openness” into the rules. That’s more grounded than betting on just one model. (´▽`ʃ♡ƪ)

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Repost: The gain leaders’ board has been completely filled with stocks now.. The crypto circle is still messing around for nothing. Previously, a coin-issuing group organized VC gatherings → fed them to exchanges → market makers pumped and dumped → and the whole crypto-industry structure of KOLs calling orders collapsed directly. The coin-issuing groups and VCs have no way to get onto Nasdaq just by relying on a whitepaper, and listed companies wouldn’t hand exchanges a few points of chips for free. They also wouldn’t set up a KOL round to find a bunch of people to run ads. Meanwhile, market makers can’t even get their foot in the door of the NYSE.
Now in this situation, everyone who used to speculate in crypto and those doing research have been silenced. Those trading contracts with high leverage can’t find a reason to go looking for coins that VC and market makers manipulate, instead of choosing stocks with 20% fluctuation where there’s actual business support. People who claim to be value investors and write ten-thousand-word research reports every day, when faced with aerospace AI robots, continuing to write those cryptic, hard-to-understand technical terms from the crypto world is just like a primary school kid mumbling to themselves.

My first post. I want to talk about something I think is underrated: why open-source large models matter.
AI will change many industries and be adopted across many companies and countries’ technology stacks. I’m increasingly convinced that this path won’t be a single lane—both frontier closed-source models and frontier open-source models are needed.
Closed-source models often have advantages in compute and engineering, but open-source models lay out the capabilities: security research, cybersecurity, and innovation diffusion are all more easily validated and participated in by more people. For many regions, this is also part of technical sovereignty—not fully dependent on a single vendor.
As someone who pays attention to both technology and encryption, I’m very sensitive to the “open vs. closed” debate. In the encryption industry, many foundational infrastructures came from open source. If AI only follows a closed-source route, the pace of innovation and the cost of building trust could be different as well.
So I don’t take sides on “only open source” or “only closed source,” but I do care whether there is enough room for open-source models. It’s not just idealism—it’s also about competition and security mechanisms in the real world.

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I’ve been researching the BTC ecosystem lately.

Honestly, in the past few years, everyone’s understanding of Bitcoin has been too simplistic.

For many people, BTC is:

Just buy.

Then wait.

Then hold/collect.

But I’m increasingly convinced that the real big opportunities are often not when everyone already knows, but when a great asset begins to generate a new narrative.

🔥 Bitcoin is changing.

Starting from being only “digital gold,” it’s now exploring more possibilities.

That’s also why I’ve begun paying attention to Babylon recently.

What it’s doing is really interesting:

making it so BTC isn’t just sitting there quietly,

but exploring how to participate in a broader Web3 security and application ecosystem.

Personally, I really like this direction:

not recreating a new story,

but opening up new value spaces around BTC, which already has massive consensus.

This makes me think of:

how Ethereum once moved from a “smart contract experiment” to the entire DeFi ecosystem.

Today, could BTC also be heading toward its next phase?

No one knows the answer.

But the market always rewards those who:

research early,

think ahead,

and set up early.

👀 My focus:

✅ BTC ecosystem infrastructure
✅ Bitcoin DeFi
✅ Security-sharing network
✅ Long-term value-capture ability

Babylon:

worth keeping an eye on.

$BABY

#baby

Follow @BabylonLabs_io

Let’s find truly valuable innovations in the next Web3 era together.

🚀🔥

(DYOR, not investment advice)