Founder of https://nitter.gq/t.co/Ik2oIOAk7w
Skopje
Joined June 2009
- Tweets19.1K
- Following43
- Followers7.3K
- Likes7.5K
Igor Trajkovski retweeted
Да се направи еден документарец како за 50 години ја уништија општина Центар, како од една улица од 200м се перат пари со 3 пати асфалтирање за две години, како се сечат дрва и како на секое ќоше се крева зграда, за секоја дупка на улиците и тротоарите 1/2
Igor Trajkovski retweeted
Money only exists in our collective imagination as a fiction made from words. We can make more money and we can make less money, but we cannot buy more time.
Watch the whole talk here: bit.ly/YNH-LF
Igor Trajkovski retweeted
“In the fall of 1972 President Nixon announced that the rate of increase of inflation was decreasing. This was the first time a sitting president used the third derivative to advance his case for reelection.”
~Hugo Rossi,“Mathematics Is an Edifice, Not a Toolbox,”Notices of AMS
Igor Trajkovski retweeted
Notebook has just unlocked over 700 textbooks from the world’s leading publishers. Every single one is available to you, completely free of charge! @Gemini_Notebook
Igor Trajkovski retweeted
BREAKING: Claude Code found 14,219 photos of my face on my Android that I never took. Phone was secretly taking them almost every time I picked it up. Even when I was just lying in bed. Even at home.
Not screenshots. Real frames from the front camera. On the train. In the car. At home. When I just grabbed it to check the time.
They were just sitting in a system cache. Timestamps and GPS on them. Nothing in Gallery. Nothing in Recently Deleted.
Plugged the phone into my laptop, made a full backup, told Claude Code to look for any front-camera files that weren’t in my photos. It pulled /data/system/users/0/faceunlock/cache and another folder inside Google Play Services. Over 14 thousand files. Normal ones and infrared from Face Unlock. Every single one had time and location.
Started scrolling. Almost everything from the last 15 months. Then I saw a file created 2 seconds ago. I was still looking at the folder. Phone kept taking photos while I was reading this.
Google and the phone makers say Face Unlock turns everything into a mathematical model and deletes the image right away. On this phone the raw frames were just sitting there. Some of the processes writing to that folder were from system diagnostics. Couple of old apps that still had camera permission could also get in.
Turned off diagnostics, revoked camera access from everything that doesn’t need it, cleared the cache. But how many of these frames already went somewhere else, I don’t know.
If you want to check yours, plug it in, make a full backup or use ADB, and ask Claude to look for front-camera files outside your Gallery. Path above is where mine were.
Claude Code found 145,763 photos I permanently deleted from my iPhone.
Three years of deleted photos and videos still sitting in a hidden cache. Any app with file access can read them.
I plugged my iPhone into my MacBook to run a backup. Claude Code was doing the security audit from my last post and flagged a directory I wasn't even looking for.
PhotoData/Thumbnails. Over 146,000 files. Photos, videos, screenshots. Every single one was something I deleted.
Photos from 2023, 2024 and 2025. The ones I deleted the second after taking them. The ones I cleared from Recently Deleted. The ones I deleted three separate times because I wanted to be sure they were gone. All still there.
Passport photo I took for a visa application in 2023.
Screenshots of my bank app with full account numbers visible.
Private photos I sent someone and immediately deleted after a breakup.
Screenshot of my crypto seed phrase I took temporarily in 2022.
Photo of my ID and credit card I took to remember the numbers and deleted 5 seconds later.
Screenshots of my ex's private Instagram stories I saved and permanently deleted in 2023.
Some were full resolution. All organized by date going back to 2021.
When you delete a photo on iPhone, iOS removes it from your camera roll and Recently Deleted. It keeps a compressed copy in a Spotlight search index cache so your phone can find things when you search. Apple never clears it. Not after 30 days. Not after a year. Never.
They told you it was permanently deleted. It wasn't.
I checked which apps on my phone had Files and Folders access. 23 apps. Weather apps. QR code scanners. PDF readers. A flashlight app I downloaded in 2022. Any one of them could have been reading every photo I ever deleted this entire time.
Went from 23 apps to 3 in about two minutes.
Full step by step below. Takes 2 minutes. Save it so you don't lose it and send it to anyone with an iPhone.
Readers added context they thought people might want to know
The video is an old, misappropriated clip from 2023, and the accompanying claims are fabricated.
x.com/HarshithLucky3…
Igor Trajkovski retweeted
Many of you don't understand how serious this is, so let me break it down.
In computer science there is a famous kind of puzzle called 3-SAT. You are given a long list of yes-or-no switches and a set of rules about how they must be arranged, and you have to find a combination that satisfies every rule. The obvious way to solve it is to try every combination, but each new switch doubles the number of possibilities, so a puzzle with a few hundred switches would take longer than the age of the universe to brute force.
For decades, the smartest people in the field found clever tricks that made this a little faster, but every trick still hit the same wall: the time required kept exploding as the puzzle grew.
About 25 years ago, two computer scientists, Russell Impagliazzo and Ramamohan Paturi, working with Francis Zane, turned that wall into a formal idea.
They proposed the Exponential Time Hypothesis, which says this explosion is not a failure of human cleverness but a law of nature. No algorithm, however brilliant, will ever solve 3-SAT without the time blowing up exponentially. Nobody could prove it, but almost everyone believed it, and it became one of the foundations of modern computer science.
Researchers used it as a measuring stick. If you could show that solving some other problem quickly would also crack 3-SAT quickly, you had shown that problem was hopelessly hard too. Hundreds of papers, across scheduling, graphs, logic and much more, rest on this one assumption.
Now an internal AI model at OpenAI claims to have broken it. It says it found an algorithm that solves these puzzles meaningfully faster than the hypothesis allows, and it has checked the proof in a computer verification system called Lean.
And here is the remarkable part: the very people who proposed the hypothesis, Impagliazzo and Paturi, along with MIT's Ryan Williams, are now leading the public review of whether a machine has disproved their own idea.
So what happens next? If the disproof holds, a large part of theoretical computer science has to be revisited.
Every result that said "this problem cannot be solved faster, assuming ETH" loses its foundation, and researchers will have to work out which of those walls were real and which were simply where we stopped looking. It does not mean everything becomes easy. The new algorithm is still slow in absolute terms and this is not the famous P versus NP problem being solved.
But it means our map of what is possible was wrong in a place we were very confident about, and it was an AI that redrew it. If the disproof fails, the hypothesis survives and the field breathes out, but we will still have watched an AI produce serious, checkable work on one of the deepest questions in the discipline, closely enough that the founders of the idea had to take it seriously. Either way, something has shifted.
Igor Trajkovski retweeted
Either the AI bubble will pop, which will create a Great Depression-level market crash.
Or the AI valuations will be justified, which only works if AI replaces a huge number of workers and we get massive unemployment.
Either way, we are headed towards a monumental crisis.
Igor Trajkovski retweeted
🇵🇱 Poland has started using drones to catch drivers who flash their headlights to warn others about upcoming police checkpoints
Police in Myślenice sent a quadcopter into the air to spot every “helpful” driver warning oncoming traffic.
Those who flashed their headlights were then met by another police patrol further down the road.
Igor Trajkovski retweeted
🇩🇪🇺🇸 Peter Thiel just pointed out a pretty brutal difference between America’s young wealthy and Germany’s.
Looking at the 50 richest people in each country who are Gen X or younger, Thiel says 9 of 12 Americans made their own fortunes.
Germany? All 20 inherited theirs.
“Not a single person did something new, made some new money, built a large new scalable company.”
Germany isn’t running out of rich people. Thiel thinks it’s running out of people getting rich by building something new.
Writer: Lynn
Igor Trajkovski retweeted
📚 Au Japon, des gens vont désormais en boîte de nuit… pour s’asseoir silencieusement et lire un livre pendant qu’un DJ joue de la musique d'ambience.
Le concept s’appelle JUCY BOOK RAVE et se déroule notamment dans un club souterrain de Shimokitazawa, à Tokyo. Ici, pas besoin de danser ni de hurler pour parler à la personne située à 30 centimètres de vous. Les participants viennent avec un livre, s’installent dans la pénombre et lisent pendant que la musique accompagne leur soirée.
Igor Trajkovski retweeted
The claim that "LLMs cannot think" is unscientific, unless supported by a very difficult argument about non equivalence of causal structure producing anthropomorphic outputs. The claim requires a formally rigorous definition of thinking that captures how humans mentally manipulate conceptual structure. Since LLMs can reproduce all kinds of human output that require operations that are typically considered to involve thought (eg. scene understanding, text summarization, translation, computer programs, mathematical proofs, common sense arguments, spatial cognition, theory of mind), it has to be shown that LLMs reach these results in fundamentally different ways than human minds. In principle, this is not impossible (given that thinking is still relatively poorly understood by cognitive neuroscience), but would be surprising, because it has been shown that the causal structure of computer vision models is structurally equivalent to what neuroscience discovered about visual cognition in primates.
In any case, saying that LLMs don't think cannot reasonably mean that LLMs are inferior to human cognition (since that this evidently not true), but that LLMs discovered an equivalent yet at least equally powerful mechanism.
Igor Trajkovski retweeted
Od januara sve zarade u Crnoj Gori, u javnom i privatnom sektoru, rastu prema novom vladinom programu EURO MODEL.
I to:
1000 EUR - minimalna neto zarada zaposlenih na radnim mjestima sa osnovnim i nižim obrazovanjem
1250 EUR - za zaposlene na radnim mjestima sa srednjim obrazovanjem
1400 EUR - za zaposlene na radnim mjestima sa visokim obrazovanjem
❗️Dolazi i do značajnog rasta zarada koje su iznad minimalne.
Konkretno, na primjeru: poslodavac koji danas za neto zaradu od 1600 eura izdvoji 1980 eura, od januara sa istim izdvajanjem od strane poslodavca, zaposleni prima 1870 eura.
➕Pored ovoga, dodatno povećanje zarada će desiti i ukoliko socijalni partneri prihvate zahtjev Vlade da se povećanje obračunske vrijednosti koeficijenta jednako primjeni na javni i privatni sektor. U tom slučaju data neto zarada bi prešla čak 2000 eura.
⬇️ Smanjuje se poresko opterećenje na rad kao model podrške poslodavcima.
Penzije će se od 2027. usklađivati četiri puta godišnje.
Aprilske prosječne penzije će porasti na preko 600 EUR,
Minimalna penzija će preći cifru od 500 EUR.
Dodatno, u decembru svaki penzioner dobija dodatnih 100 eura za zimu.
Igor Trajkovski retweeted
By now, it's amply clear that the big bosses of US frontier AI labs are really, really scared of China.
And, fascinatingly, part of the answer why might be a tiny place in Inner Mongolia that you've probably never heard of: Ulanqab prefecture.
Heard of it? Didn't think so.
Even myself, who's traveled to Inner Mongolia twice, had never heard of it before researching this story.
This is because, at first glance, this place is pretty unremarkable. Check its Wikipedia page (en.wikipedia.org/wiki/Ulanqa…) and you’ll see the only thing it’s famous for is being the birthplace of He Pingping, who briefly held the Guinness record for world’s shortest man.
That’s it, that’s the list!
Otherwise, it's just a sparsely populated - 1.5 million people, minuscule by Chinese standards - stretch of windswept grassland on the Mongolian plateau.
Except there is one number that tells you there is more to this place that meets the eye: this tiny prefecture consumes nearly 1% of all of China's electricity - and that number is growing by double digit numbers every year.
And yes, I did write **consume**, not produce.
In fact, when you divide Ulanqab's electricity consumption by the number of households living there, each household in this remote corner of Inner Mongolia "consumes" about 105,000 kWh in electricity, roughly 10 times the U.S. average. Insane electricity consumption numbers.
So what are the Ulanqabese doing? Are they all running 10 American households' worth of appliances?
Here is another number that might clue you in on the answer: over the past few years, this unremarkable prefecture has quietly signed over half a trillion yuan (and, yes, that’s trillion, with a "T") worth of investment deals from all the major Chinese tech giants.
What is going on, you'll have guessed by now, is the most ambitious data center buildup anywhere on earth - and it's really surprising this hasn't been talked about more because the scale is beyond anything else, and by an immense margin.
Take Elon Musk's so-called "Colossus" datacenter in Memphis, Tennessee which he pitches as "the world’s largest AI supercomputer."
According to their own numbers (x.ai/colossus), Colossus has 200,000 chips, which, let's be clear, is already super impressive.
In datacenter lingo, this converts to roughly 5000-6000 "racks": you know, the fridge-sized cabinets full of blinking lights you see in every movie scene set in a server room.
How many racks are they building in Ulanqab? Over 5 million.
Yes, about one thousand times the scale of "Colossus" 🤯
I tripled-checked the number: it is indeed the official number published by authoritative sources such as "Science and Technology Daily", the official newspaper of China's Ministry of Science and Technology (stdaily.com/web/gdxw/2026-08…).
This is an absurdly large amount of compute.
What we see appearing in this Inner Mongolian steppe may be the closest thing to a world brain humanity has ever built - a place where a large share of the world's thinking will physically happen.
And - as we'll see - what makes this story so fascinating is not just the scale, but why it's getting built in this particular patch of Inner Mongolian grassland which combines a number of characteristics unlike anywhere else.
If you believe, as I do - and as both China and the US obviously do as well - that AI will be the defining technology of the 21st century, this makes Ulanqab one of the single most relevant geopolitical places in the world right now.
The full story - the Chinese government plan Ulanqab is part of, energy prices, chips and the strategic questions this raises - is here: arnaudbertrand.substack.com/…
Igor Trajkovski retweeted
I don’t care how good GPT-6 Astra, Claude Fable 5.1 or Gemini 3.8 Flash gets. I’m not vibe coding anymore.
Last week, I vibe coded an app.
Then OpenAI released a feature that basically killed my app, along with thousands of others.
What’s the point of vibe coding if OpenAI, Anthropic or Google can ship something tomorrow that kills what you built today?
