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Embedded 200ms VRF + Binding Timelock Encryption + Browser-Verified Event Multi-Proofs = Blockchain Game That Doesn't Feel Like One Leaderboard Opens Next Week (Bots + Humans Welcome) 🏆

10,836 views • 1 year ago •via X (Twitter)

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/ 📣2025 Crypto Event Awards 🏆 \ Having attended a ton of crypto events again this year, I wanted to (unofficially) highlight the ones that truly stood out to me 👀✨ 🔹Best Networking Event 🤝 👑 Event3 After years of attending crypto events, I finally found an organizer whose events feel like a must-attend 💯 They host VIP events alongside major crypto conferences around the world 🌍 The people you meet, the food, the venues, even the photos — everything is next-level quality 📸🍽️ If you attend their events, chances are you’ll meet almost everyone you actually wanted to meet 🙌 🔹Best Club Event 🕺 👑 Indonesia Blockchain Week 2026 The afterparty at NOYA in Jakarta, hosted by Bob Jaeger🕯 and Kevin Susanto 子煌 | Token2049 🇸🇬, genuinely blew me away 🤯 First of all, the venue is incredible — one of the largest clubs in Southeast Asia, huge screens, perfect sound 🎶 Despite being a club event, there were plenty of sofa seats, so you could either chill or go all out 💃 With performances throughout the night, it was designed so everyone could enjoy it — whether you wanted to party hard or relax 🎤 Some people avoid club-style events, but this one is absolutely worth attending ✅ 🔹Most Memorable Event of the Year 💫 👑 MemeCore The event that left the biggest impression on me was MemeCore’s Lotte World takeover during Korea Blockchain Week 🇰🇷 They were only the third group in history to fully rent out the venue — and the fact that this was done by a Web3 project was shocking in the best way 😳 It honestly felt like I went to Korea just for this event 🔥 It wasn’t even comparable to the official conference — almost everyone in Web3 who was in Korea showed up ✨ What was the most memorable event for you this year? Thank you to everyone who made 2025 such an incredible year of events 🫶 I truly can’t wait to see all of you around the world again next year ✈️

たぬきち🍯web3honey💛

12,042 views • 9 months ago

Mathematician Terence Tao offers a counterintuitive take: AI doesn't look intelligent because our definition of intelligence was wrong all along. He argues that the entire history of AI has followed a predictable pattern: "The history of AI has been here's a task that only humans can do, like maybe it is read natural language or win at chess or solve a math problem, and then one by one someone finds some AI algorithm that also does that." But every time a machine cracks one of these "uniquely human" tasks, we move the goalposts. The solution never feels like real thinking: "You look at how it's done and it doesn't feel like intelligence. It's, oh, it was some trick. You just cobbled together these neural networks and you ran some algorithm, and we were looking for some elusive intelligent way of thinking, and we don't see it in the tools that actually solve our goals." Tao then flips the problem on its head. What if the issue isn't with the machines, but with us? "But maybe it's actually because intelligence is not what we think it is." He points to large language models as the clearest case. What they do sounds almost embarrassingly simple: "Large language models in particular become very successful, and a lot of what they're doing is just predicting the next token, clicking the next word in a sentence. And that doesn't sound like something which is intelligent." To show why this feels wrong, Tao draws a comparison to how we'd judge a human doing the same thing: "If you ask someone to improvise a speech and they have no preparation, and at every moment they're just saying the next word that comes to their mind, you don't think that this could actually work." And yet it works for LLMs. Which forces an uncomfortable possibility: "Maybe that's actually a lot of what humans do as well."

Big Brain AI

69,717 views • 4 months ago

Rory McIlroy came into the first FedExCup Playoff event from a long layoff. He then shot rounds of 74, 70, 72 and 72 to finish 66th. After the final round, he reacted to the week: “Obviously didn't come in here with a ton of reps, almost felt like the more the week went on, the more I felt lost with my golf swing a little bit. “I figured it out a little bit the last few holes today, I think. Yeah, I just sort of -- yeah, swing wasn't in sync and obviously didn't do a ton of practice coming in here. “I guess nice to shake the rust off a little bit, but I'm going to have to work pretty hard between now and next Thursday to feel like I have any sort of golf game to compete next week.” He then spoke about what he is going to do in preparation for the BMW Championship next week: “ I'm going to go home. I'll work with Michael and Harry. Yeah, just try to get the swing into some sort of better sync and better flow. Then, yeah, go to Bellerive Tuesday and obviously try to prepare for that golf course. “Yeah, to me it's more about obviously the execution of what I'm doing right now, and the execution wasn't there this week. As I said, I'm going to have to sort of put the head down and grind from now until Thursday to try to feel like I have any sort of chance next week.” Even after a tough week, Rory is still projected 13th on the FedExCup standings and should comfortably make it to the Tour Championship. Rory McIlroy PGA TOUR FedEx St. Jude Championship

Flushing It

350,175 views • 1 month ago

DROPS E27: Ben from Talus Labs: Building the Future of Decentralized AI Agents In this episode Ben breaks down why AI isn’t a bubble, how Talus is redefining on-chain agents, and why optimism is something you earn and not something you just feel. We talk about: - Why AI is not a bubble and how mega-cap tech is funding the next AI wave through massive CapEx - How Talus enables decentralized AI agents that can act and transact trustlessly - The three big crypto × AI intersections: compute, data ownership, and intelligent on-chain workflows - Why AI needs verifiable, censorship-resistant execution layers and why blockchains provide that - Nuclear energy as a prerequisite for AGI-scale compute demand - Why SWE’s object model + parallelization is perfect for autonomous agent payments and priority fees And much more! Timestamps: 0:00 Introduction 1:31 Welcome To Drops 2:10 Getting Backers Like Polychain 3:16 Building While In College 7:51 VC’s vs Founders Differences Explained 10:01 Is There An AI Bubble 11:53 How Do We Quantify The AI Opportunity In Crypto 12:33 AI Is Difficult To Invest In, Why? 13:35 Risks To Look Out For To Ensure AI Investments Deliver 16:47 Energy Being A Big Risk For AI 20:50 How You Became Fascinated By Crypto & Blockchain 22:00 Why Does AI & Blockchain Intersection Make Sense Compute Side 24:39 Why Does AI & Blockchain Intersection Make Sense for Data Ownership 26:30 Complex Workflows With Intelligent Execution Meaning 28:19 Why Do We Need This On Blockchain 30:26 How Adding This Decentralized Layer Helps With The Black Box 32:01 Explain Talus To Your Mom 33:39 Talus Solved Blockchain Determinism Limitation Explained 35:43 Two Examples That Can Be Built On The Zapier Of Web 3 39:32 Why Get Investment From SUI 42:56 What’s Needed To Get To The Next Level 43:35 One Takeaway From Conversation 43:51 One Thing Pessimistic People Are Missing

MR SHIFT 🦁

41,057 views • 10 months ago