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My landlord raised my rent by $400 a month and gave me 30 days to accept or move out. His text said: "Market rate. Nothing personal." I replied, "Understood. Can you send the new lease so I can review it?" He sent it within the hour. I read all 11 pages twice, and on page 9, I found one line he had clearly forgotten was there...

My mom fed a homeless man behind our house for 20 years. Three meals a day, even when we couldn’t afford electricity. I hated her for it. The day after her funeral, that same man took my hands, looked me straight in the eyes, and said: “Before she died, she begged me to stay silent.” I honestly had no idea what he was talking about. For 20 years, this man had lived in a makeshift shelter behind our rental house. My mom brought him breakfast, lunch, and dinner. Every single day. And the crazy thing was, we were poor too. My sneakers had tape covering the holes. Sometimes we struggled to pay our bills, and there were days when we couldn’t even afford electricity. But somehow, my mother always found enough food to feed him. I never understood it. I remember coming home two days before Christmas and finding a yellow eviction notice taped to our front door. We were struggling to keep a roof over our heads, yet my mother was still preparing three meals a day for a stranger. That night, I finally lost my temper. Me: “Maybe if you stopped feeding strangers, we wouldn’t live like this!” My mom turned around so quickly that I knew I had crossed a line. Mom: “Don’t you ever DARE say that again.” I had never seen her that furious before. I didn’t understand why she was defending him so strongly when her own child was going without things. I moved out when I turned 18. We fought less after that, mostly because I stopped asking questions. But the man stayed. Year after year, his little shelter remained behind our house, and my mother continued feeding him. Then my mom got sick. Cancer made her small. She became quiet, and it was the kind of quiet that scares you because you know something terrible is happening. Two weeks before she died, she reached out and grabbed my wrist. Her grip was so weak that it broke my heart. Mom: “Promise me you’ll keep feeding him.” I looked at her. Honestly, I wanted to say no. I wanted to ask why she was still worrying about that man when she was the one who needed help. But you don’t lie to a dying mother. So I promised. My mom eventually passed away. The day after her funeral, I prepared the best meal I could, put it on a plate, covered it with foil, and drove to her house. I had promised her I would keep feeding him. But when I got there, the man was gone. His shelter had been completely cleared out. Everything was gone. The ground had even been swept clean, as if those 20 years had never happened. I stood there holding the warm plate, wondering where he could have gone. Then I noticed something. A black SUV was parked at the curb. Standing beside it was a man wearing an expensive wool coat. He was clean-shaven, well-dressed, and looked nothing like the homeless man I had known for 20 years. But the thing that caught my attention was what he was holding. My mother’s old silver locket. The same locket she had told me she lost when I was eight years old. He looked at me and said: Man: “I thought you wouldn’t come.” I stared at him. Me: “Wait… is that you? What’s going on?” He smiled, but his expression was unsteady. His eyes were already filling with tears. Man: “Your mom hid something from you.” I felt my stomach tighten. Me: “What did she hide?” He looked at the plate in my hands before responding. Man: “Before she died, she begged me to stay silent.” My blood went cold. Me: “Silent about what?” He gently shook his head. Man: “Sit down. You shouldn’t hear this standing in the cold.” We sat on the front steps. The plate was still warm between us. He turned my mother’s silver locket over in his palm as though it might break. Then he began telling me something I never could have imagined. Man: “My real name is Vernon Hale. Before all this, I owned a company. I had a big house in Connecticut, a wife, and a little girl. My daughter was six years old.” I just stared at him.

जब मैं पहली बार Thailand घूमने गया तो वहाँ मेरे एक दोस्त ने बिना पूछे मेरे लिए एक Rental Girlfriend बुक कर दी पहले तो मुझे लगा था कि वह लड़की सिर्फ मेरे साथ घूमेगी ही और कुछ नहीं लेकिन Thailand की Rental Girlfriend तो मेरे साथ...1/2

I am actually disgusted by the timing of this drop. And this will get a bit more technical. Let’s do a real technical teardown of this "1,385-sigma Blackwell weight fingerprint" report that OpenAI and Anthropic are breathlessly promoting today, because banking on nobody reading past the headline is how DC narratives get manufactured. ​First, look at the actual CUDA maths: when PyTorch initialises model weights (torch.nn.init) with a fixed PRNG seed, curand/Philox parallelises random number generation across the GPU’s Streaming Multiprocessors (SMs). Because Hopper has 132 SMs and Blackwell has 148 or 152 SMs, the exact same seed lays out initial weights in a different spatial pattern depending on the GPU’s SM count. In huge MoE models, certain low-gradient null-spaces or unrouted slices preserve faint directional traces of those step-0 weights even after training. ​So yes, brute-forcing the seed and SM grid can show that a model’s step_0 weight initialisation script ran on a 148/152-SM Blackwell GPU. Now read what the summary explicitly admits in the fine print: 1. Initialisation is not full training: The report literally states that these signatures show how the weights were created, and "support (but do not prove) the inference that Blackwell also participated in model training". Initialising a model checkpoint takes seconds on a single rented dev node before loading the safetensors onto a standard Hopper cluster. The "2,000 to 3,000 Blackwell GPUs" and "$500 million" cluster numbers do not come from the weight fingerprint and Depue admits in his own thread that he simply "estimated" cluster sizes from release schedules and model details. ​2. Zero geolocation and zero proof of smuggling: The final sentence of the executive summary explicitly admits that the findings "do not establish the physical location of the chips, how they were acquired, or whether export control regulations were violated". Depue himself rented a cloud GB200 instance just to run his verification test. Commercial labs that are not on the Entity List renting bare-metal Blackwell nodes in offshore clouds (Singapore, Japan, or the Middle East) is completely legal under BIS rules and leaves the exact same SM fingerprint. Now ask yourself why a former OpenAI researcher dropped this on November 12, the exact day Jensen Huang was pushed out, with OpenAI and Anthropic immediately stepping in to "independently verify" it. US closed-source labs are watching their paid API moats get eaten alive by free Chinese open-weights models. Conflating a step-0 PRNG initialisation seed with a "$500M smuggled Blackwell cluster" hands DC hawks the exact pretext OpenAI and Anthropic want to regulate global cloud compute and kneecap open-source AI.

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.

Trade your shielded $ZEC for confidential USDC on Ethereum, without ever unshielding it. No bridge. No custodian. No wrapped ZEC. And the amount never shows up on chain. I connected @zama and @Zcash to make it work. Live on testnet 👇 What it is ZEC Desk is a small trading desk on Zama's FHEVM, on Ethereum Sepolia. On one side there's cUSDC, a dollar token whose balances are encrypted. On the other side there's shielded ZEC on Zcash testnet. You can trade either way. Built on Zama's model Zama's Confidential RFQ is already live on Ethereum mainnet, open to everyone: It runs confidential swaps with encrypted quotes, a sealed-bid pick on chain and a hidden floor. ZEC Desk takes that same model and extends it to native shielded ZEC. Zama's swap settles both legs on one chain, inside its own contract, so a Zcash leg can't plug into it directly. Here that leg lives on Zcash and settles minutes later with a proof, so the mechanics run in my own contract. It's a sketch of how native ZEC could sit next to Zama's swaps one day, with no wrapped token. How a trade works (buying ZEC) 👇 1️⃣ You lock cUSDC in the desk. The amount is encrypted. 2️⃣ Makers send encrypted quotes. Nobody sees anyone else's price, or the minimum you'll accept. 3️⃣ The contract picks the best one under FHE. 4️⃣ The winning maker sends shielded ZEC to your Zcash address, with the order's reference in the memo. 5️⃣ A zero-knowledge proof shows that payment happened, and the contract releases your cUSDC to the maker. If no proof arrives in time, your cUSDC comes back to you. Selling is the same in reverse: the maker locks cUSDC, you pay the ZEC, and the proof releases the cUSDC to you. Why these pieces Each piece does one job. Zcash keeps the payment private. Zama keeps the amounts encrypted and can still compute on them. Seam, the Zcash light client I built last month, connects the two: a contract checks every Zcash block header itself, and a RISC Zero proof shows a shielded payment reached the right receiver. The transaction, the note and the address never touch the EVM chain. The masked amount This was the hard part. Seam's proof used to write the paid amount in the clear, and ZEC amount × price gives away the dollar amount. So the amount is masked. The contract adds an encrypted one-time mask to the encrypted amount and reveals only the sum, which looks random to everyone else. The mask comes from a secret that the side receiving the ZEC hands to the payer. The proof checks that the payment was at least the sum minus the mask, and never states the amount. One-time pads are old, and Zama's RFQ uses one too. Using one to hand a value from FHE to a ZK proof is the part I haven't seen before. If you have, please send it my way. No vault, no signers Seam can read Zcash, but it can't take ZEC from anyone. So the design never needs someone to pay ZEC on someone else's behalf. Whoever pays, pays from their own wallet, and the escrow on the EVM side enforces the deal. The side that paid the ZEC can prove it itself, so nobody depends on the other side's goodwill. Seam does more than this Any EVM app that needs to know a shielded payment happened can use Seam: pay-with-ZEC checkouts, escrows, payouts, cross-chain orders. This desk is one example. Where it stands ↓ Testnet only, unaudited. On 12 November 2026 I ran a Buy end to end: ➡️ Settled with a proof: ➡️ One proof: 2 minutes on a rented RTX 4090, about $0.25 for the whole session ➡️ Gas per Buy on Sepolia: about 7.6M, in six transactions ➡️ A Sell also ran on Sepolia, up to the maker locking its cUSDC; it settles through the same proof step ➡️ Seam's light client is now deployed on Ethereum Sepolia too, next to Base Sepolia Where it can go ↓ → The desk only needs Zama's FHEVM and a cUSDC. Both already run on Polygon, where following Zcash costs a fraction of Ethereum mainnet. → Zama keeps adding chains. On any cheap EVM chain it reaches, the same desk can run, and if it comes to Base, Seam's relay already runs on Base Sepolia. → Zama's roadmap also goes beyond the EVM, to chains like Solana. Seam's verifier would need a port there. → On Ethereum mainnet, following Zcash header by header would cost over 2B gas a day, so batched header proofs are next for Seam. What it can't do yet - Settlement takes minutes, not seconds. Zcash confirmations set the pace, not the GPU. - Right now I'm the only maker, and a maker needs ZEC, cUSDC and a GPU. - Amounts are hidden, but EVM addresses are public. Read more ↓ Seam on Seam: ZEC Desk:

मैं जापान घूमने गया था। वहां मुझे पता चला कि कुछ कंपनियां पैसे लेकर Rent-a-Girlfriend की सुविधा देती हैं। पहले मुझे लगा यह कोई मजाक होगा, लेकिन जब इसके बारे में पता किया तो हैरान रह गया। मैंने भी सोचा कि एक दिन के लिए Rent-a-Girlfriend बुक करके देखता हूं। कुछ देर बाद एक लड़की मेरे सामने आई। वह बेहद खूबसूरत थी और बिल्कुल गर्लफ्रेंड की तरह व्यवहार कर रही थी। हमने साथ में खाना खाया, शॉपिंग की और घूमने गए। रास्ते में उसने मेरा हाथ पकड़ लिया और पूछा: "क्या तुम्हारी असल जिंदगी में भी कोई गर्लफ्रेंड है?" मैंने कहा: नहीं, इसीलिए तो तुम्हें पैसे देकर बुलाया है! वह हंसने लगी। लेकिन शाम को उसने मुझसे एक ऐसा सवाल पूछा, जिसने मुझे सोचने पर मजबूर कर दिया। उसने पूछा: "अगर आज तुम्हें मेरे साथ अच्छा लगा, तो क्या तुम कल भी मुझे बुक करोगे या किसी दूसरी लड़की को चुनोगे?" मैंने मजाक में कहा कि शायद तुम्हें ही दोबारा बुलाऊंगा। लेकिन उसका अगला जवाब बिल्कुल अलग था...

This is the biggest irony of the whole Alice Huang / Nvidia saga: the Chinese government actually doesn't want Nvidia chips and is actively keeping them out of the country. Last year it even ordered Alibaba and ByteDance to cancel their Nvidia orders ( and sent customs teams to the ports to check every advanced chip coming in ( And right now 600,000 Nvidia H200s are stuck in Hong Kong because Beijing won’t let them into the country ( Nvidia also explicitly frames this as a threat to its business in its latest annual report to the SEC: "The Chinese government has encouraged customers to purchase from our China-based competitors and discouraged customers from purchasing, importing, or using our data center products" ( Why does China do that? Because every Nvidia chip a Chinese company buys is one that Huawei or Cambricon doesn’t sell, and domestic chips can only catch up if people actually buy them (which means money for R&D, etc.). Which means that the notion that Chinese intelligence was running honeytraps to get more Nvidia chips into China gets the whole thing exactly backwards. In fact, it looks like Megaspeed - Alice Huang's company - was a counter-reaction to official Chinese policy: a private sector workaround to these efforts by the Chinese government to curtail Nvidia. As was widely reported - including by Western media - Megaspeed built data centers in Southeast Asia and rented their computing power to Alibaba, which the New York Times called "a backdoor way of getting access" to Nvidia chips ( That is a backdoor not only - allegedly - around Washington’s export controls, but also around China's own efforts to wean its companies off Nvidia. I can’t believe the Chinese government was too thrilled about it: it'd make just about zero sense for it to run countless domestic measures to prevent Alibaba from using Nvidia chips, yet at the same time have its top spy agency help the same Alibaba get Nvidia chips through the back door in Southeast Asia 🤷 At the end of the day, as with all such stories, you always need to look at "cui bono?": who benefits? Who benefitted is pretty clear: - Nvidia itself: it's in the business of selling chips so a customer willing to spend billions of dollars on chips in Southeast Asia is a godsend. Again, as they themselves state in their SEC filings, not being able to tap into Chinese demand would have "a material and adverse impact on our business" ( - Chinese companies like Alibaba: facts are, 1) Chinese chips haven't yet caught up, 2) Chinese chip companies' production capabilities are still limited and 3) Chinese tech firms' historical tech stack runs on Nvidia’s CUDA ecosystem, and rewriting years of code for Huawei chips is painful. Renting Nvidia chips in Southeast Asia is the easy way to stay competitive and serve customer demand in the meantime. - The US, according to core members of the Trump administration: back in July last year, US Commerce Secretary Howard Lutnick explained that the point of letting Nvidia sell more chips to China was to get Chinese developers "addicted to the American technology stack" ( Who does NOT benefit, according to official Chinese policy, is the Chinese state, which has made tech self-reliance one of its foremost priorities. Which means that, to believe the spy story, you have to believe that a person - Alice Huang - was effectively a spy paid by her own government while simultaneously sabotaging its tech self-reliance drive, which it has spent years and trillions of dollars on - pretty senseless. Stranger things have happened, I guess, but it doesn't pass the smell test. And there is another absolutely major contradiction in the media story. According to a Financial Times article published yesterday ( "a person who knows [Alice Huang] said they had been asked by MSS for information about her earlier this year after news emerged that Singapore was investigating the company in relation to chip-smuggling allegations. The agency wanted to find out more information about Huang, including the nature of her business and connections, the person said." Which raises a damn obvious question: if she were indeed an MSS asset, why on earth would the MSS need to ask the people around her who she was and the nature of her business? It's a complete contradiction with the spy story - but very much not a contradiction with what I described above: a private businesswoman running a workaround to Beijing’s own policy, which the Chinese security apparatus would naturally want to look into. Especially since, around about the same time, Shanghai police detained her business partner, reportedly her husband, in a stock manipulation case ( also coherent with Chinese authorities looking into her network, and much harder to square with her being a prized MSS asset. And, to top it all, there is - to this day - not a shred of evidence that's been published that she is, in fact, a Chinese spy: just anonymous intelligence officials, repeated by journalists who never verified it, as I detailed here ( and here ( with one of the key FT journalists on this story actually admitting that he has no idea what evidence US intelligence actually has. So the claim went to print without anyone seeing the evidence, without anyone being able to check it, and without anyone knowing whether it even exists. And given everything above, from Beijing blocking the very chips she was supposedly recruited to help get into China, to the MSS asking around about her, to her partner being detained in Shanghai, my bet is that the evidence doesn’t exist at all. If anything, everything we can check points the other way.