The Man Who Told People to Buy $1 worth of Bitcoin 12 Years Ago😱😱
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. Follow for more information🙂 #bitcoin☀️
I recently spent an afternoon trying to get an AI to help me draft a sensitive legal document, and it was a total disaster. It kept making up case law that did not exist and looking me straight in the digital eye while doing it. That is the moment I realized that while these models are brilliant at talking, they are terrible at being right. We are all living in this weird era where we have the world's most powerful library at our fingertips, but half the books are filled with lies. This is why I started looking into Mira. From a user's perspective, it feels like a much-needed reality check for the internet. Instead of just taking a chatbot's word for it, the system breaks down complex writing into tiny, individual claims. It is like taking a suspicious car to five different mechanics at once to see if they all find the same engine leak. If they do not agree, the claim gets flagged. It stops being about one "god-like" model and starts being about a community of different AI perspectives checking each other's work. It is a bit like a jury for information. We have to face the fact that "blindly trusting a single neural network is a recipe for digital disaster". Mira changes the dynamic by making sure no single entity can steer the truth. It gives me a way to actually verify the math or the facts before I hit send on something important. It is less about fancy tech and more about making sure the tools we use every day do not let us down when it matters. It makes me feel like I finally have a safety net.
Shipping the Truth: Mira and the Containerization of AI Logic
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
Many people have Ramadan Game of Chance spins 🎯 But not everyone can use them 😕 because only a limited number of people can spin at the same time. and spins finish in just 1-2 seconds ⚡
The time resets at 12 PM UTC 🕛 so you have to be ready exactly at that time.
But Dont worry
I know the trick 😉. I didn't record screen today but Tomorrow I’ll upload a full video tutorial with screen recording 🎥 so you can also do your spin easily.
I have been spending a lot of time lately thinking about how much we actually trust the answers we get from artificial intelligence. It is a strange situation where we use these tools for almost everything, yet we always have this lingering doubt in the back of our minds. I often find myself double checking facts or worrying if a chatbot is just making things up to sound smart. This is where I started looking into a project called Mira. From a user perspective, it feels like a necessary safety net for the digital age. We are currently living in a world where "AI is great at sounding right even when it is completely wrong" and that is a hard truth we have to deal with every day. Mira works by taking the output from an AI and breaking it down into small, individual claims. Instead of just hoping the one model got it right, a whole network of different models looks at those claims to reach a consensus. It is like having a jury of experts double check a homework assignment before you hand it in. As a consumer, I do not have to understand the complex math or the blockchain mechanics behind it to see the value. I just want to know that the medical advice or the legal summary I am reading is actually accurate. The network uses economic incentives to make sure the verification is honest, which gives me more confidence than a single company promising their model is perfect. This project matters to me because it turns AI from a creative toy into a reliable tool that I can finally use without constant fear of errors.