TechnicalTrader

In 2013, a man named Davinci Jeremie, who was a YouTuber and early Bitcoin user, told people to invest just $1 in Bitcoin. At that time, one Bitcoin cost about $116. He said it was a small risk because even if Bitcoin became worthless, they would only lose $1. But if Bitcoin's value increased, it could bring big rewards. Sadly, not many people listened to him at the time.
Today, Bitcoin's price has gone up a lot, reaching over $95,000 at its highest point. People who took Jeremie’s advice and bought Bitcoin are now very rich. Thanks to this early investment, Jeremie now lives a luxurious life with yachts, private planes, and fancy cars. His story shows how small investments in new things can lead to big gains.
what do you think about this. don't forget to comment.
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#bitcoin☀️

To be honest, looking at the score data of Grok-4 Heavy from early 2025, even an old-timer like me who has been in the circle for over a decade feels a chill down my spine. Humanity’s Last Exam—this name is quite harsh, but also very straightforward—this is the last closed-book exam prepared for non-biological computers. Ten months ago, these robots had an average score of only around 0.1, which was just at the 'participation level.' In the blink of an eye, it jumped to over 0.5, a fivefold performance increase. This leap is no longer just a simple algorithm iteration but a 'Cambrian explosion' in the digital world. What makes me anxious is not that they score high on the exam, but that these large models can now directly take over various robots through open-source code. Those 0s and 1s that once only spun in servers now have limbs and are beginning to rampage in our physical world. We often say the future is here, but when this force capable of reshaping civilization truly arrives, who will hold the remote control that determines the direction?

I was grabbing a drink with a few old-school infra engineers last week, and the conversation inevitably soured into the absolute mess that is the current AI "trust" landscape. We’re currently living through this bizarre era where we’re basically treating LLMs like digital oracles—we ask a question, get a wall of text, and then just cross our fingers and hope the model didn't decide to hallucinate a legal precedent or a structural engineering flaw for the hell of it. The industry’s solution so far has been to throw more "vibe-based" evaluations at the problem, which is about as effective as trying to audit a bank by asking the teller if they feel like the numbers probably add up. We’ve been desperately needing a way to move past this blind faith, but the technical debt of verifying complex, generative output is a nightmare that most teams are just too terrified to touch.
The fundamental rot in the old way of doing things is that you can't just hand a fifty-page technical brief to three different models and ask them if it’s "correct." It’s a total failure of logic; one model focuses on the syntax, another gets tripped up on a specific adjective, and a third just ignores the middle ten pages entirely. You end up with a fragmented mess of opinions that can’t reach a consensus because they aren't even looking at the same problem. This is where I think Mira is actually onto something that isn't just another Web3 buzzword. Instead of trying to verify a sprawling, messy narrative all at once, they’re essentially atomizing the content. They take a compound statement like the Earth revolving around the Sun and the Moon revolving around the Earth and strip it down into its constituent, verifiable claims. It’s the difference between trying to grade an entire essay in one go and checking every single fact against a primary source. By standardizing the output into these discrete units, every verifier node in the network is forced to look at the exact same claim with the exact same context, which finally brings some sanity to the verification process.
Of course, the "visionary" part of this only works if the "bone-deep reality" of the economics holds up. Mira is trying to build this decentralized orchestration layer where independent node operators are economically incentivized to be honest, which is a tall order when you consider the sheer latency and compute costs involved. You’ve got this systematic workflow where a customer sets their domain—say, medical or legal—and defines a consensus threshold, like an N-of-M agreement. The network then grinds through the transformation, claim distribution, and consensus management before spitting out a cryptographic certificate. It’s a heavy lift, and the cynical side of me wonders if the world is ready to pay the premium for that kind of rigor, but the alternative is a digital landscape where we literally can’t tell the difference between a hallucination and a hard fact. We’re moving toward a source-agnostic future where it doesn't matter if a human or a bot wrote the code; what matters is whether the claims hold water.
If we don't get this right, we’re essentially building a massive library where the books rewrite themselves every time you close the cover. Mira’s approach feels less like a simple "fact-checker" and more like a sophisticated sorting machine for the truth. It reminds me of the shift from old-world maritime shipping to the modern container terminal. Before, you had loose cargo and chaos; now, everything is standardized, tracked, and verifiable. We are finally moving away from the era of "trust me, I’m an AI" and toward a world where truth isn't a feeling, but a cryptographically signed receipt.
$MIRA #Mira @mira_network

A few days ago, I had drinks with several friends who work on large models in big tech companies, and during the conversation, we talked about the current AI craze. Today's AI indeed resembles the internet of yesteryear, even being pushed to the heights of the printing press and steam engine, which changed civilization. But what about reality? Ideals are abundant, but reality is stark enough to make one think of 'giving up.' Everyone talks about how AI will replace doctors and lawyers, but when it comes to high-risk decision-making, who would dare entrust their life to a chatbot that could go off on a tangent at any moment? This 'immense wealth' is right in front of us, yet due to that damned illusion and bias, AI is still locked in a low-cost, high-tolerance toy box, becoming a 'gold-consuming beast' that can only chat and cannot bear responsibilities.

Last week, I had drinks with a few friends who are working on nodes in Singapore. We talked about the current Layer 1 track, and the most commonly heard term during the conversation was 'discouragement'. Indeed, the current public chain market is very similar to early e-commerce platforms, where everyone is competing on throughput and the number of nodes, resulting in users staring blankly at the progress bar when making a transfer. I was thinking at the time, have we always been wrong about the direction of our efforts? People are always nitpicking a few milliseconds of optimization in the word games of consensus algorithms while selectively ignoring a harsh reality: the Earth has a radius, and the speed of light has limits. Even if your algorithm is perfect, when your nodes are spread across the globe, that 150 milliseconds of physical latency across the Pacific is an insurmountable barrier.

Recently, I had drinks with a few old friends who have been navigating this circle for many years. We talked about the current Web3 applications, and everyone's most intuitive feeling is "exhaustion." The current blockchain products, although their slogans are deafening, are basically a real-life "discouragement guide" when you actually use them. If you want to play a game or conduct a transaction, you have to click countless confirmation buttons and deal with numerous signature pop-ups. This kind of "signature fatigue" is simply wearing down the last bit of patience from users. Honestly, if we remain stuck in this primitive interaction stage, the so-called "mass adoption" will forever just be a self-indulgence among insiders.

Recently, I had a late-night chat with several old friends who have been navigating the Web3 space for many years. When we mentioned the current economic models of public chains, the most intuitive feeling for everyone was: the threshold for launching a chain has indeed lowered, but figuring out the accounts clearly and ensuring the network doesn't collapse within a few years remains a highly challenging technical task. When many people look at Fogo, their first impression is that it is a pixel-level replica of Solana, such as the 5000 Lamports basic transaction fee and the priority mechanism that increases packaging probability through 'tips' under high load. Although this design seems mediocre and even a bit 'following the trend,' in the pursuit of extreme efficiency today, it actually represents the most prudent survival strategy, just like those seemingly inconspicuous yet extremely efficient precision parts in industrial production.

Recently, I was chatting with a few friends in the node community, and everyone was complaining that the current consensus mechanism of public chains is simply a "Frankenstein"—wanting the appearance of decentralization but unwilling to sacrifice performance. As a result, the validators are suffering greatly, with hardware costs piling up higher than mountains. Actually, I've been thinking about whether a machine like Solana, which pursues extreme peak throughput, can really play around a bit more in the dimension of the physical world. It wasn't until I recently delved deeply into the logic of Fogo that I realized these people truly dare to think outside the box. They even want to implement a "time difference system" for the validators.

Recently, I had morning tea with a few old friends who have been struggling at the bottom of public chains on Shennan Boulevard, and we all sighed in unison when discussing the current scaling solutions. In the current Web3 circle, everyone seems to have fallen into a certain degree of 'technical arrogance,' believing that as long as the consensus algorithm is written in a sufficiently esoteric way, it can break through physical laws. But I always feel that those who sit in offices writing white papers have probably forgotten that the speed of light has limits and that the global operator networks are actually in ruins. It's like having a supercar capable of 100 kilometers per hour but insisting on racing on a narrow path during the morning rush hour. Until recently, when I opened Fogo's design documents, that long-lost feeling of being hit by someone knowledgeable returned. The first impression this project gave me was 'down-to-earth'; it doesn't play around with those abstract scientific terms but directly inserts a scalpel into physical constraints and network topology, and this daring posture of confronting physical common sense is indeed quite interesting.

A few days ago, I had drinks with some old friends who work in node operations in Singapore. During the conversation, everyone was complaining about the current public chain track. While we talked about various new projects endorsed by big companies, deep down, we all knew that the current blockchain world has fallen into a strange state of 'parameter inflation.' Every newly launched Layer 1 seems to want to write in its white paper that it can achieve millions of TPS, as if just having a sophisticated name for the consensus algorithm could break the constraints of physical laws. However, I have always felt that many developers are actually writing a kind of 'spherical chicken in a vacuum' program. They assume that the network reaches instantaneously, and that the performance of machines worldwide is uniform. But where is real life that gentle? Reality consists of physical delays and that damn long-tail effect; they are the cold killers that strangle all high-performance fantasies.