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⚓️ Ethra Ship Notes｜Vol.050 Today, I came across a number that made me stop. Nearly 1,900 vessels are now considered part of the maritime "dark fleet" according to Windward, roughly tripling since the Russia-Ukraine invasion. The interesting part isn't just the number. It's what the number tells us about visibility. A ship can disappear from AIS. That doesn't mean the ship disappears from the ocean. It just disappears from one information layer. And that's a very different thing. This is where I think Sea Verity's approach gets interesting. Instead of asking a single system to tell us the truth, it combines different sources. Reporters on the ground. AI analysis. Controller nodes. Each piece adds another layer of evidence. And rather than forcing every observation into a simple "true" or "false", the system is designed around confidence scores. I like that approach. Because the physical world rarely gives us perfect information. A satellite image can be obscured. A reporter can only see part of a vessel. AIS can disagree with visual evidence. Weather can make everything harder. The honest answer isn't always certainty. Sometimes it's: We're 90% confident this is what happened, and here's why. That's much more useful than pretending the other 10% doesn't exist. For insurers, traders, logistics companies and regulators, knowing the confidence behind a piece of maritime intelligence could be just as important as the information itself. The ocean is enormous. Maybe the answer isn't one perfect signal. Maybe it's many imperfect signals learning how to verify each other. @EthraShip #EthraShip# #EthraShipProtocol#

the reason i'm so chronically online on X is that i owe my entire career to it. every job i've had has been through relationships i've made here, and as i hit 50k - a number i never thought i'd see on my profile - i can't help but feel a little emotional. you see, i started building up my profile when @wifelette and @tomdale took a chance on me many years ago - a nobody in melbourne who was still learning how to code in js - and invited me to speak at @EmberConf. i had never been to a conference at that point in my life, let alone speak at one. they found me through my tweets sharing my blogposts about learning the framework. i'm not exaggerating when i say that my life changed after doing that talk. public speaking was my greatest fear and i was visibly shaking for the first 5 minutes of my talk, but somehow i managed to remember everything i had practiced. that talk was how i got my first real job (and moved to the US) at @DockYard, thanks to @bcardarella also taking a chance on me. throughout this time i continued posting on twitter and building up my profile little by little. after you've done one talk, the next one is a little easier and so i kept doing more of it - seeing the world i had never been exposed to before. i got my job @netflix the same way, through doing a talk, and people taking a chance on me. some of you may be surprised to know that i never majored in CS and that i'm a self taught programmer. so going through a FAANG interview was inconceivable to me at that point in my life. i actually tried to back out of the interview, but they convinced me to do it anyway, and im glad that i did. i then got my job at facebook through Dan Abramov (i miss him here!!), who i met at a conference talk i did in London. we stayed in touch on twitter for a while before he reached out to me asking if i would be interested in working on the react team (uh, hell yes?! but wait, me??). massive imposter syndrome has followed me everywhere. now at @cursor_ai and @SpaceXAI, i feel so lucky that i get to work alongside such crazy talented, driven, and ambitious people who want to build beautiful products for everyone. and i'm also still in disbelief that this many people care about what i have to say here. thank you everyone for taking a chance on me, and thanks @X for being there for me this whole time 🤍

Robot shook a man's hand at Haneda Airport this spring. Not a metaphor. Not a demo reel. Japan Airlines put a Unitree humanoid on the tarmac, and after it slid a bag onto the belt, it turned and shook hands with the coworker standing next to it. I keep coming back to that handshake. Not because it's impressive engineering – it is, but that's not the point. It's because somewhere in my head I still filed "robots at work" under someday. And someday just quietly became this spring. The G1 costs around $13,500. Less than six months of minimum wage in most US states. That number is the part nobody's mind adjusts to fast enough. Here's the thing I actually sit with: fear usually runs on the speed of change we've already seen, not the speed of change actually happening. Which means most people will notice this shift about two years after it stopped being news. The ones who don't wait – the ones who start asking "where else does this math already work" – are quietly building the next decade's businesses right now. Automation audits for small operators who can't afford a robotics team. Leasing models for companies that don't want to buy outright. Someone managing a small fleet of these things is a real job now, not a concept. I don't know exactly where I land on this yet. Some of it excites me, some of it unsettles me, and I think both reactions are honest. What would you automate first if the robot only cost $13K?

8 MONTHS OLD AND ALREADY NUMBER 16 OUT OF 6,557 OBSIDIAN PLUGINS. EVERYTHING ABOVE IT HAS BEEN THERE SINCE 2022 YISHENTU/CLAUDIAN. 1,722,530 installs, 14,688 stars, MIT, 2.1.3 shipped yesterday. it isn't a chat panel. it drops Claude Code inside your vault with the folder as its working directory. read any file, search all of them, write back. so an agent is sitting in your whole archive with permission to edit it. every abandoned draft, every half thought you never finished, every promise you made in a note nobody else has read. 1.7 million people handed that over, and almost all of them use it to write more notes. nobody points it backwards. the feeds are full of graph screenshots. not one shows a contradiction. one prompt changes what it is: "read every note in this vault. find pairs that contradict each other. keep both, stamp the dates, never pick the newer one. show me the pairs, not a summary." no screenshots in the clip above either. every number in it was pulled live while it recorded. aimed forward it makes your archive bigger. aimed backward it makes it honest.

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SAMSUNG’S $200B BROADCOM DEAL IS BIGGER THAN A MEMORY SUPPLY CONTRACT. 📊 Samsung Electronics $005930 and Broadcom $AVGO have agreed to pursue more than $200B of semiconductor cooperation through 2030, covering HBM, advanced foundry manufacturing and packaging. Reuters separately confirmed the $200B Samsung–Broadcom portion of the wider Korea–US semiconductor agreements. The headline number is huge, but the strategic shift matters more. Samsung is trying to move from being viewed as a component supplier to becoming a full-stack AI semiconductor partner: Memory → Foundry → Advanced Packaging The reported scope includes HBM4 and HBM4E for Broadcom’s AI accelerators, sub-2nm foundry processes for key chip products, and integrated support from design optimization through packaging and mass production. That matters because Broadcom is one of the central players in custom AI accelerators and high-speed data-center networking. If this MOU converts into real production orders, Samsung would capture more value from each AI chip—not only memory revenue, but also manufacturing and packaging economics. For the Korean market, Samsung is the clearest direct beneficiary. Equipment, materials and packaging names may follow, but only after capacity expansion, supplier participation and actual purchase volumes are confirmed. I would not treat the entire $200B headline as booked revenue yet. This is still an MOU. The real revaluation depends on: → Final contract volumes → Product and process allocation → Production timing → Pricing and margins → Whether orders translate into utilization and earnings The headline creates expectations. Execution is what creates the rerating. $005930 $AVGO For reference only. This is not investment advice. Avoid excessive leverage, do not chase sharp moves and maintain strict risk management.

Hey @token_works, your packs have a 77.3% RTP and you don’t publish it anywhere. users deserve to see this before they buy You pay EV × 1.10. the exit pays you 85% of backing. 0.85 / 1.10 = 77.3%. you lose 23 cents of every dollar, every single pack The EV term cancels. it does not matter which pool you pick or how it’s built. the number is identical every time. no skill, no timing, no edge And it compounds. 5 packs leaves you 27%. 10 packs leaves you 7.6%. this is not variance you recover from, it is a straight line to zero Just for reference, blackjack returns 99.5% RTP. roulette 94.7% RTP. the worst slot machine on ANY casino returns 88% RTP. But $FWA packs return 77.3% RTP, before the nonrefundable VRF fee It’s all in your own docs at /docs/pricing-draw and /docs/winning. just never as one number. a buyer staring at a pack has no way to know they’re taking a worse deal than any casino on earth would legally be allowed to offer • users: 77.3% out. keeping the NFT only breaks even if the floor beats 1.10 × pool EV. know which bet you’re making • team: put the RTP on the pricing page. one line. UK operators are required to surface exactly this for slots You would literally have better odds gambling at a casino than aping $FWA packs