beeneir

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beeneir

@beeneir

Father, Husband, Cosmic Dancer, Brother, Son // Web Dev 🌈💀🏀

Templin Beigetreten Haziran 2015
209 Folgt40 Follower
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Zeneca🔮
Zeneca🔮@Zeneca·
Taxing unrealized gains is one of the dumbest things I have ever heard of and I’ll never understand how the idea is getting as much traction as it is
Bitcoin News@BitcoinNewsCom

NEW: Dutch Parliament Member Michel Hoogeveen explains how the 36% unrealized capital gains tax, just passed by the House of Representatives, will work. Here is a more detailed example: Step 1. Starting position You own 500 shares. Value on Jan 1, 2028: €50,000 Value on Jan 1, 2029: €100,000 So the paper gain is: €100,000 − €50,000 = €50,000 unrealized profit You did not sell. But for tax purposes, that €50,000 is treated as income. Step 2. Apply exemption You are married, so you get a €3,600 exemption. €50,000 − €3,600 = €46,400 taxable amount Tax rate: 36% €46,400 × 36% = €16,704 tax bill That bill is due in May, even though you never sold anything. Step 3. Market falls before you pay Now suppose by May the shares drop in value. New total value: €60,000 So your portfolio is no longer worth €100,000. It’s worth €60,000. But the tax bill is still €16,704, because it was calculated based on the January 1 valuation. Step 4. You must sell shares to pay tax To raise €16,704, you sell part of your shares. After paying the tax, you’re left with: €60,000 − €16,704 = €43,296 Originally you had 500 shares. Now you have 360 shares left. You were forced to sell 140 shares. 140 ÷ 500 = 28% of your shares gone. Step 5. What happened economically? Before the correction: Paper gain was €50,000. After the correction: Portfolio is worth €60,000. Original cost basis was €50,000. Real gain is only €10,000. But you paid €16,704 in tax. So instead of being up €10,000, you are now: €43,296 − €50,000 = €6,704 below your original starting value. You turned a €10,000 real gain into a €6,704 net loss. And you lost 28% of your shares permanently.

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Aakash Gupta
Aakash Gupta@aakashgupta·
The scariest number here: 3.61% of CPUs in one large-scale study were found to cause silent data corruptions. Not “a few bad chips.” Nearly 4 out of every 100 processors doing math wrong, silently, with no error log. Google coined the term “mercurial cores” in 2021 after their production teams kept blaming software for data corruption. They’d debug for weeks, find nothing wrong with the code, swap the machine, problem gone. The actual cause: manufacturing defects at sub-7nm that pass every factory test, then degrade unpredictably months or years after deployment. Facebook confirmed the same thing independently. Hundreds of affected CPUs across hundreds of thousands of machines. The defect doesn’t crash your system. It just gives you 5 instead of 6 when you multiply 2x3, under specific microarchitectural conditions, with zero indication anything went wrong. Now think about what this means for AI training. A single corrupted GPU or CPU in a distributed training cluster doesn’t just produce one bad output. It feeds corrupted gradients into a synchronization step that gets averaged across every accelerator in the cluster. One bad chip can silently poison an entire training run. NVIDIA published a whitepaper on exactly this problem. Loss spikes during LLM training that nobody could explain traced back to silent hardware corruption. The part that keeps infrastructure engineers up at night: traditional defenses don’t work. ECC memory can’t catch this because the corruption happens during computation, not storage. Checksums like CRC heavily use vector operations, which are themselves one of the most vulnerable instruction types. The tools designed to detect corruption are running on the same flawed silicon. Google’s current detection method? Roughly half human-driven, half automated. And of the machines humans flag as suspicious, only about 50% are actually confirmed mercurial on deeper investigation. We’re debugging trillion-parameter models on hardware where we can’t reliably tell which chips are lying to us. Moore’s Law gave us more transistors. It also gave us transistors we can’t fully verify.
LaurieWired@lauriewired

CPUs are getting worse. We’ve pushed the silicon so hard that silent data corruptions (SDCs) are no longer a theoretical problem. Mercurial Cores are terrifying because they don’t hard-fail; they produce rare, but *incorrect* computations!

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Topo
Topo@Topo_G·
Thanks a lot @hubermanlab I was rock hard for my physical
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Val
Val@valerioshi·
RIP again, I guess
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Viktor Bunin 🛡️🇺🇸
Viktor Bunin 🛡️🇺🇸@ViktorBunin·
OH in SF: "I'm not a lawyer but I get down. I fuck with LLMs."
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The Bitcoin Historian
The Bitcoin Historian@pete_rizzo_·
KAZAKHSTAN'S CENTRAL BANK IS NOW ALLOCATING $350 MILLION FROM ITS GOLD RESERVES TO BUY #BITCOIN AND CRYPTO NATIONS ARE BUYING THE DIP 🚀
The Bitcoin Historian tweet mediaThe Bitcoin Historian tweet media
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M.AUD
M.AUD@MatthewXBT·
Who is still bullish on @idOS_network and what they have coming in the future?! never fading gQuack
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Cryptofic
Cryptofic@MyCryptofic·
When the crypto market gives you 💩, $GIKO neko gives you 🌹 ./\___/\ ( ^ Д ^ ) |>🌹^| v——v\
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Jonny 👾
Jonny 👾@Hustlepedia·
Is Pump Fun streaming still the future of content creation? 😅
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Viktor 🧡
Viktor 🧡@s0meone_u_know·
You are not SELLING your Bitcoin… but donating it to the ppl with unlimited fiat money.
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Digi (Delusional)
Digi (Delusional)@digiii·
is this guy going to Dubai or siberia????
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RG
RG@TheRGMedia·
Montreal’s blue line puzzle is getting crowded. The Canadiens’ ensuing trade strategy could get interesting, but sources are indicating that any potential move is not expected to include Kaiden Guhle. More from @mndamico: rg.org/news/hockey/ca…
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DeeZe ⛳🏌️‍♂️
personally I cannot believe the coins are bouncing a day after everyone including myself was crashing out and ready to apply to a prediction market
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Kenn
Kenn@DegenKenn·
🔥 $4,500 giveaway to 3 people - $1,500 each 🔥 Time to give back in this brutal market Rules: Must follow @DegenKenn & @CryptoNoach Like & RT Tag 3 friends Winners drawn 11/29
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