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【舞台物販情報】 「 #アサルトリリィ# 御台場女学校-The Battle to Overcome-」 こくみん共済coopホール スペース･ゼロ 2/3(金)〜2/12(日) 記念グッズを多数ご用意！会場内特設スペースとアゾンダイレクトストアで販売予定です🍀 ★詳細 #御台場TBO# #アゾン# #azone#

🚨 BREAKING: $1.77 BILLION OF BITCOIN JUST LEFT #BINANCE# IN 24 HOURS. AND NOW INSOLVENCY RUMOURS ARE CIRCULATING!!! 27,764 BTC MOVED OUT OF ONE BINANCE HOT WALLET ALONE. REMEMBER: 17 DAYS AGO BINANCE LOST $6.36 BILLION IN A HACK AND PROMISED TO COVER EVERY DOLLAR. NOBODY ASKED WHERE THAT MONEY WOULD COME FROM. ARE THEY SELLING THEIR OWN BITCOIN TO FILL THE HOLE? AND ARE YOUR LIQUIDATIONS PAYING FOR IT? @grok is Binance dumping Bitcoin, or is this the start of a bank run?

Having multiple research tools is useful, but the experience becomes much better when users can access them without constantly switching between different platforms. Consider how a Solana trader researches a new token. They might start by checking its market activity, investigate the wallets involved, examine token distribution and look for possible risks before making a decision. Each step provides a different piece of information, but they all contribute to the same research process. This is where @StonkwatcherSF’s planned website restructure becomes interesting. The team is working on improving the website’s navigation and making its features easier to discover. The new landing page is also expected to showcase the broader Stonk Watcher ecosystem, including its products and mobile application. I think this is a meaningful direction because Stonk Watcher is aiming to bring different parts of crypto research closer together. Token discovery helps users find opportunities. Wallet tracing provides more context about the people and addresses behind transactions. Market analysis and risk indicators help users examine what is happening before deciding where to focus their attention. These tools become more useful when they fit into one connected workflow. The mobile app adds another layer by making research and safety features more accessible beyond the desktop experience. Of course, a redesigned website alone doesn’t guarantee a better product. Navigation needs to be intuitive, information needs to be reliable and the different features need to work smoothly together. That’s what will determine whether this restructure makes a real difference. I believe good product development is not just about adding more features. It’s also about making existing tools easier to find, understand and use. The goal should be simple: less friction, better access to information and a smoother research experience. That’s the progress I’ll be watching from @StonkwatcherSF. @StonkwatcherSF $STWC

In 2015, AI hallucinating was the whole point. 🌀 This is DeepDream, running on VGG16. You hand a neural network an image and tell it to exaggerate whatever it thinks it sees. Then you make it do that over and over, each pass building on the last. 🔁 It finds eyes and creatures everywhere 👁️ because it learned to see from ImageNet, a dataset of 1,000 categories packed with animals (about 120 are dog breeds alone 🐕). Ten years later, the same behavior has a less fun name: hallucination. And we spend a lot of engineering effort stopping it. 🛠️ Same thing underneath, just a different job.

— The worst feeling is when you don’t even want to give up on someone, yet they leave you with no choice. Not because you stopped loving them, but because you slowly realize that love cannot survive on hope alone. You keep showing up, keep understanding, keep giving chances, while they keep giving you reasons to question your place in their life.

X AI ALGORITHM UPDATE (BIG ONE) 🚨 X updated their open source algorithm yesterday and the biggest number in it is gone: copy link went from 20 to 0 points. Small accounts should focus on: posts people like, reply to and stay on (so stop counting on link copies) tl;dr: - on Nov 13 X's open source code set the score for copying a post's link to 0 - copy link: 20 → 0 - it was the top score in the whole system, 4x a reply - the code also names a "copy link bait" spam check - likes (0.708), replies (5) and DM shares (5) didn't move full details: - The number that's gone Since I started reading X's open source code in August, one number sat at the top: 20, for someone tapping share and copying your post's link. Nothing else came close. As of the Nov 13 release, it's 0. X still guesses who'll copy your link. It just multiplies that guess by 0 now. X didn't explain it. It's just what the code says. (I check the open source algo daily with Claude and share updates with you) - Cross it off your list My own checklist called copy link the biggest number. Last week's post said it too. It was true then. It isn't now. If you saved that list, cross that line out. - The "copy link bait" check X's code now mentions a spam check called "copy link bait". In the code it adds a spam label to the post, and that label already keeps a post out of strangers' feeds. It only shows up in a test, so I can't see if it's running or how strict it is. My read: X saw people baiting link copies, so it turned the score off and built something to catch the bait. That's a read, the code doesn't say why. - Why that matters if you're small If your plan was posts people copy the link to, that plan now earns 0 in X's ranking. A copied link can still bring people in from outside X. It just doesn't push your post up anymore. What still pays: likes at 0.708 (the highest ever), people staying on your post, replies at 5 and back and forth with mutuals at 20. - Also new: photo and video tags If a post has a spam label, people you tag in its photo or video who don't follow you won't get notified. Same idea as last week's rule for replies. - What didn't change Every other score. Your new posts still get their extra push in the first 2 hours and first 200 views, and early likes still pick which one gets it. Here's a recap of what you should be doing: - aim for likes, replies and time spent, the copy link score is gone - a DM share still earns 5, same as a reply or a quote - likes sit at 0.708, never higher - time on your post keeps counting at its best rate yet - 10+ seconds after someone taps in adds 0.385 - write your replies yourself, under big accounts most of all - give people a reason to hang around your profile - in videos the opening seconds carry it, an open alone scores 0 - posts read to the end help X find you strangers - smaller accounts (below 50K) get a shot at a spot near 16 for a fresh original - early likes decide which new post gets that spot - post when your followers are awake, the push lasts 2 hours and 200 views - mutuals going back and forth earn 20, so follow back the regulars - only your originals ever get shown to strangers - like 1 and like 32 each unlock another way to reach strangers - one strong post per feed, your second only counts 62% - clips longer than 10 seconds for the video lists - a post likely to win you a follow gets +4 - give your pinned post a look, it can affect the whole account What you should NOT be doing: - counting on copy link shares, they score 0 now - baiting link copies, the code names a spam check for exactly that - a spam label also stops your photo tags reaching non-followers - AI-written replies under big accounts, "llm slop" is a flag X uses - copy-paste replies, labeled ones skip non-followers' notifications - chasing taps, 0.274 and dropping - drifting off your topic, each probable "not interested" takes 53.07 away - videos people open and leave, the open itself earns 0 - posting at 3am, it wastes the 2 hour push - expecting replies and reposts to reach strangers - an insult label, it hides that post from non-followers - earning a misinfo or low quality label, which adds a warning and locks strangers out of liking or sharing - 3 adult photos or videos among your latest 5 posts, that puts a label on you - forgetting videos get rechecked at 64 and 512 likes - one account label and strangers stop seeing you - pinning a link to a site X rates badly, that can mean a label for a week - posting your own old words again risks the copypasta flag - a low quality link plus tagged strangers reads as spam - bait for engagement, big or small it gets a label - several posts back to back, they split the same feed - hashtag piles, they do nothing - bookmarks for reach, they score 0 - hoping a 3 day old post still lands in For You, it stops at 2 days

🚨 THIS IS WHY BITCOIN KEEPS CRASHING BELOW $67,000 If you still think Bitcoin trades like an asset whose price is determined purely by spot supply and demand, you need to read this carefully. Because that market no longer exists. What you’re watching right now is NOT normal price action. This isn’t just an AI stock sell-off. This isn’t just hotter inflation. And this definitely isn’t retail suddenly deciding to dump Bitcoin at the exact same time. Most people have no idea what is actually happening. And by the time it becomes obvious, the damage is usually already done. This didn’t start today. It has been building underneath Bitcoin for YEARS. And now it’s accelerating. Here’s the truth: Bitcoin still has a hard cap of 21 MILLION coins. But Wall Street can create almost unlimited financial EXPOSURE around those coins. That distinction changes everything. Because once derivatives dominate short-term price discovery... Bitcoin stops trading purely on who wants to own the actual coins. It starts trading on: 1) LEVERAGE. 2) HEDGING. 3) MARGIN. 4) LIQUIDATIONS. 5) FORCED SELLING. And that is exactly what is happening right now. It’s the same mechanism that repeatedly drives violent moves in: → Gold → Silver → Oil → Stocks Once derivatives become large enough, spot buyers are no longer the only force setting the price. And this is the part almost nobody understands: Bitcoin’s scarcity didn’t disappear. But scarcity alone no longer controls the SCREEN PRICE. Wall Street built an entire financial layer on top of Bitcoin: → Cash-settled futures → Perpetual contracts → Options → ETFs → Broker lending → Swaps → Wrapped BTC The 21 million cap controls the COINS. It does NOT cap the amount of leveraged exposure that can be created around them. And once that leverage starts unwinding... The market doesn’t care what the long-term thesis is. It SELLS. Look at what just happened: Over $1.9 BILLION in leveraged crypto positions wiped out in 24 hours. More than $1.1 BILLION liquidated in Bitcoin alone. Spot Bitcoin ETFs have already seen roughly $1.9 BILLION in outflows this month. Once leveraged selling overwhelms real buyers, price stops responding only to long-term demand. It starts responding to positions. Hedging. Margin calls. And cascading liquidations. Wall Street does not need to own millions of physical Bitcoin to push the market around. It only needs enough derivatives exposure and enough leverage sitting in the wrong place. The playbook is brutally simple: 1st: Build enormous leveraged exposur 2nd: Push price through obvious liquidity 3rd: Trigger stops and liquidations 4th: Forced selling pushes price even lower 5th: Buy back into the panic 6th: Repeat THIS is why Bitcoin can lose thousands of dollars while the number of coins on-chain barely changes. The coins didn’t suddenly disappear. The PRICE DISCOVERY mechanism changed. That’s what people are missing. Bitcoin is still scarce. But the financial claims built around Bitcoin are NOT. And when leverage controls the marginal trade... 21 million coins can behave like a market with FAR more supply than 21 million coins. That’s not the Bitcoin market retail thinks it is trading. That’s a WALL STREET PRICING SYSTEM built on top of Bitcoin. You can choose to ignore it. But don’t pretend nobody warned you. Bitcoin is now trading around $66,600, its lowest level since August and roughly 48% below the $126,200 high. If $65k breaks, the next level I’m watching is $62k. Reminder: I called the Bitcoin top at $126,000 and told you to start buying again around $60,000. The next call will matter even more. When I EXIT the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.

not all crypto rewards are created equal. when a platform advertises yield, i think the first thing to check is what holders actually receive and where that value comes from. @RebateLaunch has an interesting approach to this. instead of paying holder rewards in newly issued $rebate, eligible holders receive payouts in the pair asset. on robinhood chain, that's usdg. the platform reports: → $28.5k distributed to holders. → 120,403 individual payouts. → rewards sent several times throughout the day. → no staking or manual claiming required. but the reward distribution is only one part of the model. rebate pad also uses a declining launch tax to address early sniping. → 99% during the initial stage. → 66% in the next stage. → 33% in the following stage. these penalties go into a locked treasury that supports the buyer bonus mechanism. separately, the 0.7% platform fee is used to buy $rebate from the market and burn it. the reported cumulative burn has reached 35.3m tokens, representing 3.53% of the original 1 billion supply. what makes this model worth examining is how several mechanisms connect: ✦ early launch activity contributes to the treasury. ✦ the treasury supports buyer bonuses. ✦ trading fees fund holder payouts and the $rebate buyback-and-burn mechanism. my perspective is that paying rewards in the pair asset is an interesting distinction because holders aren't simply receiving more of the same token. however, attractive payout numbers alone don't prove sustainable yield. trading volume, fee generation, treasury health and long-term user activity still matter. i'd rather evaluate the source of rewards than focus only on the advertised percentage. also, round 3 of the creator campaign closes november 17 at 22:00 utc. the real question is whether rebate pad can maintain this economic cycle as adoption grows. $rebate

Wintermute CEO Evgeny Gaevoy really told Bloomberg these auctions are "more transparent and democratic" than Wall Street colocation Bro, of course you love the system when your wallet (0xecb63caa47c7c4e77f60f1ce858cf28dc2b82b00) has extracted $227M in lifetime profit on Hyperliquid and printed +$18.8M in the last 30 days alone Spending $10M a year to lock down 76% of the top slots and get a 60ms head start isn't competing fairly, it is literally paying pennies on the dollar for a legal money printer while smaller MMs get slaughtered Look at their actual positions right now: they are sitting on $93M+ in equity, $18.9M staked just to keep their direct node peering, and shorting the entire market including a massive $7.5M $HYPE short while gutting altcoin liquidity across the exact ecosystem they pretend to support

I have a major result to share. I’ve found conclusive forensic evidence that the top 4 Chinese AI labs—DeepSeek, Moonshot, MiniMax and Ant Group—have built their newest models on NVIDIA’s most advanced Blackwell chips, which are barred from export to China. This sounds insane, but I discovered that almost every AI model carries a hidden signature of the GPU that trained it. When a model is first set up, the starting values of its weights are laid out in a pattern that depends on the exact GPU. Each combination of GPU and seed number produces a unique pattern—a sort of fingerprint of the hardware used to create the model. Traces of that pattern survive training into the published model. Again, this evidence isn’t based on any insider information or leaking. It’s based on a forensic analysis of the model weights released by the companies themselves. I searched more than six trillion combinations of chip layout and seed number and matched them to open-weights models. In doing so, I found conclusive evidence that six Chinese AI models—including DeepSeek-V4-Pro, Kimi K3, and MiniMax-M3—were initialized on NVIDIA Blackwell systems. Four of the models match Grace Blackwell, the GB200 and GB300 parts in NVIDIA’s flagship liquid-cooled rack-scale systems. I then verified these results on real hardware. Running unmodified PyTorch with the seeds I’d recovered, a Blackwell B300 reproduced DeepSeek-V4-Flash’s untouched starting weights bit for bit, and a rented GB200 reproduced Kimi K3’s to a correlation of 0.999995. A Hopper H100 reproduced none of DeepSeek-V4-Flash’s, and changing the seed by one broke the match. (DeepSeek’s seed is 953049583 by the way.) The method also was verified to match 24 known open-weights models to the hardware that developers said they used. It is exceedingly unlikely that these results are a coincidence. Across six trillion combinations, the best accidental match should reach only about 8 sigma (i.e., eight standard deviations above what random chance would produce). The real matches range from 49 to 1,385 sigma, and even the weakest single test hits 20. These were data-center-scale training runs. With some analysis of release schedules and model details, I estimate that the largest, Kimi K3 and DeepSeek-V4-Pro, used 2,000 to 3,000 Blackwell GPUs each. Clusters of this size cost on the order of $150 to $200 million each to buy, and across these labs alone would add up to more than half a billion dollars of export-controlled GPUs, not counting experimental compute or otherwise. It’s quite likely that we see multi-billion dollar expenditure on export-controlled GPUs. I am highly confident in this result, and it has been independently verified by senior researchers at OpenAI and Anthropic. You can read the full report at There is much more I’ve identified about these models through other forms of checkpoint forensics like this, and will have more to share soon.