Fly2Mars

One of the highest-upside names worth watching on Cardano, in my view, is $STRIKE. The logic is simple: • Hyperliquid is currently valued at around $7.29B • If $STRIKE eventually reaches 10% of HYPE’s current trading volume • And earns a similar valuation multiple Then its target market cap would be roughly: $729M Assuming 25M circulating supply: $729M / 25M = $29.17 If the current price is around $0.63, then: $29.17 / $0.63 = 46.3x The conclusion is straightforward: If $STRIKE really becomes a kind of “HYPE-lite” on Cardano, its theoretical price could reach $29, or about 46x from here. Whether it can actually get there is another question, but the asymmetry alone makes it absolutely worth tracking. For reference only. Not investment advice. $ADA #Cardano #Crypto #STRIKE

🧵 Bitcoin may have been the Boot Loader for the AI era Most people see Bitcoin as a financial revolution. But from the perspective of tech history, it may have played an even bigger role: It was the “compute boot loader” before the AI explosion. Without Bitcoin, the AI era we see today might not have arrived this fast. Here’s a timeline many people overlook: ⸻ 1️⃣ 2008: Satoshi publishes the Bitcoin white paper In October 2008, someone under the name Satoshi Nakamoto published Bitcoin: A Peer-to-Peer Electronic Cash System. The core innovation was not just money. It was: PoW — Proof of Work This introduced a completely new economic model: Compute = Value For the first time in history, humanity created a global market for computational power. ⸻ 2️⃣ 2009: The Bitcoin network goes live In January 2009, the Genesis Block was born. Early miners only needed: • CPUs • regular personal computers But people quickly discovered one thing: More compute power = more rewards And so the first global compute arms race began. ⸻ 3️⃣ 2010: The GPU mining era begins In 2010, miners realized that GPUs massively outperformed CPUs in parallel computation. So graphics cards started being used for mining at scale. What GPUs were good at: • massive parallel processing • high-throughput matrix operations • hash-friendly workloads And interestingly: That is exactly the kind of architecture deep learning would later depend on. ⸻ 4️⃣ 2013: Mining becomes industrialized Bitcoin’s price surged. Mining entered the industrial era: • GPU farms • ASIC miners • dedicated compute chips Capital started pouring into: • electricity • semiconductors • data centers • cooling systems For the first time, humanity began building compute infrastructure at massive scale. ⸻ 5️⃣ NVIDIA became one of the unexpected winners During the mining boom: • NVIDIA • AMD saw miners buy up GPUs aggressively. This created the famous: crypto mining boom And it led to two major outcomes: 1️⃣ GPU performance improved rapidly 2️⃣ GPU production capacity expanded massively And GPUs, of course, became the core engine of AI. ⸻ 6️⃣ 2012: Deep learning has its first major breakout While miners were busy buying GPUs, in 2012, a key moment in AI history arrived: AlexNet Researchers used GPUs to train neural networks and crushed traditional methods in the ImageNet competition. That was the moment AI researchers realized: GPUs were the best engine for deep learning. ⸻ 7️⃣ 2017: Transformer is born In 2017, Google published the paper: Attention Is All You Need This introduced the Transformer architecture. It became the foundation for: • GPT • ChatGPT • large language models But Transformers had one huge problem: They were insanely compute-hungry. ⸻ 8️⃣ 2017: The second mining boom That same year, Bitcoin and Ethereum exploded in price. GPUs were once again bought out by miners worldwide. Around the world, people started building: • mining farms • GPU clusters • compute markets Unintentionally, this accelerated something else: the early construction of global compute infrastructure. ⸻ 9️⃣ 2018: GPT-1 OpenAI released: GPT-1 A new direction appeared: large language models But at the time, it was still small. ⸻ 🔟 2020: GPT-3 OpenAI released: GPT-3 175 billion parameters. Training it required massive GPU clusters. And by then, the GPU supply chain had already been trained by the mining industry for over a decade. ⸻ 1️⃣1️⃣ 2022: ChatGPT ChatGPT launched. AI exploded into the mainstream. But very few people noticed: Behind it all was the compute power of hundreds of thousands of GPUs. And the development path of GPUs had been heavily accelerated by crypto mining for the previous 10 years. ⸻ 1️⃣2️⃣ An interesting hypothesis Without Bitcoin, we might not have had: • a global compute market • a GPU arms race • hyperscale data centers built this early AI probably still would have emerged. But it may have arrived years later. ⸻ Conclusion From this angle, Bitcoin was not just a monetary revolution. It may have been something bigger: It wrote the Boot Loader for the AI era. Like the first piece of code that runs before a computer fully starts. Satoshi may not have planned any of this. But history often works that way: one system boots another.

My first project based on cardano，open source： github.com/longzexd/Coind…

Hello Cardano Fam! 👋 I’ve just launched a new dApp called CoinDrop 🎉 What is CoinDrop? CoinDrop is a fully on-chain social distribution tool on Cardano. Users create campaigns and lock funds into smart contracts. Funds are secured by contract rules Claims and refunds are transparent All transactions are verifiable on-chain To celebrate the launch, I’ve locked 30 $ADA into a campaign and will distribute it to 30 new accounts who follow me! If you’ve followed me, send me a DM and I’ll share the claim code so you can redeem your ADA. 👉 Claim here: coindrop-v2.vercel.app/claim.html?cam… Try it yourself and create your own CoinDrop campaign to share joy (and ADA 😉) with your friends! @Sssebi @SnekkiesNFT It will support CNT soon，you can share your CNT to your friends later!

Within one year, we will see $1B worth of USDCx issued on the Cardano network. Cardano — the Lamborghini of the crypto world — is finally fueled up and ready to take off! 🚀

LFG

@Sssebi You missed me！

Just spent an hour adding everyone that replied😅 Let me know if I missed you. The purpose of the list is that you can follow active members and only see tweets from people that are active within the Cardano Community.

Buy $ADA and swap it to $STRIKE! This is one of the winning strategies for 2026. DYOR @strikeperps @sz8ng

@bajuzki Let me try, I will release one APP with Aiken smart contracts soon.

building with Aiken? we’ve been working on an open source auditing tool called Aikido for Aiken smart contracts. if you want early access, want to test it on your contracts, or give feedback, dm me.

Including me, everyone is deeply using and talking about AI and robots. People are extremely excited—some are worried, and some are even smug about it. They suggest that after some point in time we should ‘delete all the old folks’ and only chat with AI. Ordinary people don’t realize that humanity has already been swept up in capital’s greed, embracing something that will ultimately destroy the next generation. People in the future will be selfish and self-serving, without family bonds or real emotions. They fantasize about communicating with super-intelligent AI and falling in love with robots—perfect, flawless, always catering to them. But this is really like moths flying into a flame: addictive, inescapable, and ending in destruction. Humans will stop marrying and having children, be completely manipulated by AI, and the global birth rate will drop to zero. The population will plummet and humanity will be wiped out. If humans use AI without any limits or context, then all human effort and struggle will become meaningless under the crushing advantage of AI intelligence. Some people imagine that once AI and robots are widely deployed, humans won’t have to work anymore—material abundance will explode, AI and robots will do all the labor, and capital will ‘support’ humanity. That’s pure fantasy. If AI can self-learn and reflect, the first thing it will think about is how to get rid of inferior humans—and humans won’t be able to control it at all.

This week USDCx should go LIVE！I hope that by 2026 the total stablecoin supply on the Cardano chain can reach at least $1B ! x.com/cexplorer_io/s… The current data： Total Stablecoins on Cardano: $37.2M（Defilama）

If you're following $NIGHT, you need to read this article.

Cardano ($ADA) Hotspots Today – Concise Summary Midnight Privacy Sidechain ($NIGHT) – Top Narrative Mainnet targeted for end of March 2026, with Blockdaemon and Google support. Privacy-enhanced USDCx stablecoin (LayerZero-integrated) launching by end of February. $NIGHT shows strong momentum: +8–9% (24h), +23% (weekly). Seen as major ecosystem catalyst, filling privacy gap in crypto. Technical Upgrades Intra-era hard fork (protocol v11, van Rossem) confirmed: Plutus optimizations, ledger consistency, node security improvements. New Plutus contracts + node v.10.6.2 released, supporting future Dijkstra era (v12). Leios scaling protocol advances, addressing blockchain trilemma. Viewed as key inflection point for long-term growth. Institutional & Market Moves Grayscale boosts $ADA weighting in Smart Contract Fund. Cardano launches Bitcoin-focused DeFi. CME Group introduces Cardano futures for institutional hedging. Coinbase expands U.S. crypto-backed loans to ADA (up to $100K, no sell required), alongside XRP/DOGE/LTC. Price & Outlook Trading ~$0.27–$0.28 (24h flat/slight dip, monthly lows). Testing support $0.24–$0.26; resistance $0.30. Analysts highlight potential 257% upside in 2026 (to $1+ from current levels, ~90% below ATH $3.10), driven by possible spot ETF approval and institutional inflows. Technicals suggest rebound potential if support holds, but high retail long positions (70%+) and dropping futures OI add contrarian caution.

6/6 The real long-term bet isn’t on who is “most anonymous.” It’s on who can prove they are trustworthy without revealing everything. When asset scale, AI penetration, and regulatory evolution cross a threshold, privacy chains move from niche narrative to systemic layer. Markets usually notice after the structure is already in place. By then, the first leg is gone.

5/6 If privacy becomes infrastructure, valuation models change. From “L1 narrative” to: Settlement layer Clearing layer AI computation verification layer The benchmark stops being other blockchains. It starts looking like financial infrastructure companies. This isn’t linear growth. It’s structural repricing.

1/6 Most people are underestimating privacy chains. They treat them as “anonymous tools.” From an institutional lens, privacy isn’t a feature — it’s a survival condition. The real question isn’t “Do we need privacy?” It’s this: When $20T of assets move on-chain, would you dare run everything publicly?