dims

there isn’t actually a correct answer re: how to do this, the correctness is something that emerges // systematic tradoor wannabe // devrel @devweb3jogja

[Gogo | Dota for Toxicity @lwastuargo]

Unironically, this is not true anymore

I have written, rewritten, resumed someone else's work, and migrated several production apps and enterprise systems post-AI

And I can confidently say: we can actually fix it later

You can't fix shitty human and shitty process tho

[dims @0xDimss]

@yonathandinata can be both at the same time 🤣

[Agstrooo @xchamberzz]

my very first demonstration

[james hawkins @james406]

parents: "move out"

girlfriend: “quit being such a loser”

boss: "work harder"

claude: "uber for dogs (the dogs are the drivers) is a great idea, you should absolutely pursue it"

[dims @0xDimss]

future of finance

[tempo.co @tempodotco]

JUST IN: Gubernur Bank Indonesia Minta Bank Tahan Suku Bunga Kredit Meski BI-Rate Naik

[dims @0xDimss]

> capcut mcp

u mean claude code + ffmpeg?

[corsaren @corsaren]

Claude (tokens): “You’re absolutely right!”
Claude (activations): “holy shit this guy is retarded…”

[Leptokinetic @leptokinesis]

"what are your hobbies:

-UNGODLY PATTERN RECOGNITION
-AGGRESSIVE ACTIVE QUESTIONING
-SILENT OBSERVATION
-REAL TIME THEORY BUILDING
-BEHAVORIAL ANALYSIS
-MICRO EXPRESSION DECODING
-POST CONVERSATION AUTOPSY"

[dims @0xDimss]

@ecommurz @fajarr0x 99 panggilan tak terjawab dari Antrophic

[Jonathan Filbert @jonathanfilbert]

🇸🇬 Singapore vs 🇮🇩 Indonesia on Claude AI usage — straight from Anthropic’s Economic Index (March 2026).

Singapore ranks #1 out of 116 countries with a 5.53x usage index. Indonesia sits at #95 with just 0.30x.

That’s a massive 18x gap.

In SG 🇸🇬, people use Claude for building/debugging AI systems, advanced scientific research, and professional business analysis.

In ID 🇮🇩, the top uses are academic assignments, creative fiction, religious/spiritual content, and data extraction.

Every day my colleagues here in Indo rave about how Claude has changed their lives. I’m glued to podcasts like Dwarkesh and TBPN, thinking that ID is on the same AI wave as the rest of the world.

Turns out… the rest of the country isn't.

It’s just today that I realized — I’ve been living in a complete bubble.

[Overfit Quantitative Strategies @OverfitQuantit1]

In compute we trust

[knv @knveth]

One of the biggest reasons why the affluent “made it” crowd and the brokies keep hanging out on ct is because there’s never really a dull day on here. The entertainment factor of this real life mmorpg beats the rest by miles.

Where else do you see
- a serial cokehead deploying billions into buying bitcoin every week
- a mid 9 figure exploit by North Korea
- one of the richest Australian Jews strangling his cute Asian influencer gf because some crypto people bullied him

All of the above in the same week

[dims @0xDimss]

"the tree that would grow to heaven must send its root to hell"

idk what that means but it’s hard

[dims @0xDimss]

if you’re healthy, mobile, mentally curious, & have real friends or a community...

congrats! you’ve already won a pretty huge lottery

[Patrick McCorry 🐋 @stonecoldpat0]

Most people forget that cryptocurrency is the field of Trust engineering:

- Identify Trust
- Measure Trust
- Minimise Trust

Trust exists everywhere: in cryptographic assumptions, software implementations, social coordination, and every point of human intervention.

It is impossible to build a Trustless system.

Trust-minimisation is a spectrum and it always comes with trade-offs.

For example, one may wish to 'turn off governance and upgradeability of a system', but this does not remove Trust. It transfers it to the assumption that the current implementation is bug-free and capable of surviving the test of time.

An engineer's goal is to manipulate and shape Trust. To design and build a system that Trusts software and cryptography 99.9% of the time, and human intervention less than 0.1% of the time.

That is what all thrive to build. It is significantly better than the legacy financial system. That is why they are now moving onto our rails and will continue to do so at size and speed.

[Vlad Tenev @vladtenev]

Math appealed to me early because it rewarded clear thinking.

Code did too. You could sit with a hard problem, strip away the noise, and work toward something real. That habit carried into business.

Building a company is messier than math, obviously.

People are more complicated than equations. Markets are stranger than they look. Still, the instinct is similar: start from first principles. Test your assumptions. Keep going when the first answer falls apart.

Looking back, a lot of my path has been an attempt to bring that kind of rigor into parts of life that are usually dominated by tradition, gatekeeping, or inertia.

[Nik Algo @nik_algo]

When I was younger, my parents always nudged me to spend less time on the screen and go outside more often.

Back when the internet was still wired.

I didn’t understand them.

To me, the internet felt like an entire world. Bigger than the one outside and much more interesting.

I thought they just didn’t get it.

Now I don’t think that way anymore.

The internet back then was a much friendlier place. People were the same, but incentives were different.

It was mostly forums and small communities.
Corners of the web you had to find.
You weren’t being pulled in… you had to choose to go there.

Modern internet is a different kind of beast.

It’s been engineered. Weaponized.
Built to drain your attention.

Attention is the only thing they want.
As much of it as possible.
All of it, if they can.

And that’s where it starts getting really uncomfortable.

I can almost see a world where we become the resource.
Entire economies built on extracting human attention… the kind of greed people used to warn about in the Bible.

Humans reduced to organisms feeding the system, trading attention for credits,
then spending those credits on things they don’t need… over and over again.

A closed loop.

Maybe it won’t be as bad as my mind sometimes imagines.

But I’m not willing to find out passively.

I’m lowering the stimulation baseline.
I’m cutting down my online presence.
I don’t want to go back.

[Justin Drake @drakefjustin]

Today is a monumentous day for quantum computing and cryptography. Two breakthrough papers just landed (links in next tweet). Both papers improve Shor's algorithm, infamous for cracking RSA and elliptic curve cryptography. The two results compound, optimising separate layers of the quantum stack. The results are shocking. I expect a narrative shift and a further R&D boost toward post-quantum cryptography.

The first paper is by Google Quantum AI. They tackle the (logical) Shor algorithm, tailoring it to crack Bitcoin and Ethereum signatures. The algorithm runs on ~1K logical qubits for the 256-bit elliptic curve secp256k1. Due to the low circuit depth, a fast superconducting computer would recover private keys in minutes. I'm grateful to have joined as a late paper co-author, in large part for the chance to interact with experts and the alpha gleaned from internal discussions.

The second paper is by a stealthy startup called Oratomic, with ex-Google and prominent Caltech faculty. Their starting point is Google's improvements to the logical quantum circuit. They then apply improvements at the physical layer, with tricks specific to neutral atom quantum computers. The result estimates that 26,000 atomic qubits are sufficient to break 256-bit elliptic curve signatures. This would be roughly a 40x improvement in physical qubit count over previous state-of-the-art. On the flip side, a single Shor run would take ~10 days due to the relatively slow speed of neutral atoms.

Below are my key takeaways. As a disclaimer, I am not a quantum expert. Time is needed for the results to be properly vetted. Based on my interactions with the team, I have faith the Google Quantum AI results are conservative. The Oratomic paper is much harder for me to assess, especially because of the use of more exotic qLDPC codes. I will take it with a grain of salt until the dust settles.

→ q-day: My confidence in q-day by 2032 has shot up significantly. IMO there's at least a 10% chance that by 2032 a quantum computer recovers a secp256k1 ECDSA private key from an exposed public key. While a cryptographically-relevant quantum computer (CRQC) before 2030 still feels unlikely, now is undoubtedly the time to start preparing.
→ censorship: The Google paper uses a zero-knowledge (ZK) proof to demonstrate the algorithm's existence without leaking actual optimisations. From now on, assume state-of-the-art algorithms will be censored. There may be self-censorship for moral or commercial reasons, or because of government pressure. A blackout in academic publications would be a tell-tale sign.
→ cracking time: A superconducting quantum computer, the type Google is building, could crack keys in minutes. This is because the optimised quantum circuit is just 100M Toffoli gates, which is surprisingly shallow. (Toffoli gates are hard because they require production of so-called "magic states".) Toffoli gates would consume ~10 microseconds on a superconducting platform, totalling ~1,000 sec of Shor runtime.
→ latency optimisations: Two latency optimisations bring key cracking time to single-digit minutes. The first parallelises computation across quantum devices. The second involves feeding the pubkey to the quantum computer mid-flight, after a generic setup phase.
→ fast- and slow-clock: At first approximation there are two families of quantum computers. The fast-clock flavour, which includes superconducting and photonic architectures, runs at roughly 100 kHz. The slow-clock flavour, which includes trapped ion and neutral atom architectures, runs roughly 1,000x slower (~100 Hz, or ~1 week to crack a single key).
→ qubit count: The size-optimised variant of the algorithm runs on 1,200 logical qubits. On a superconducting computer with surface code error correction that's roughly 500K physical qubits, a 400:1 physical-to-logical ratio. The surface code is conservative, assuming only four-way nearest-neighbour grid connectivity. It was demonstrated last year by Google on a real quantum computer.
→ future gains: Low-hanging fruit is still being picked, with at least one of the Google optimisations resulting from a surprisingly simple observation. Interestingly, AI was not (yet!) tasked to find optimisations. This was also the first time authors such as Craig Gidney attacked elliptic curves (as opposed to RSA). Shor logical qubit count could plausibly go under 1K soonish.
→ error correction: The physical-to-logical ratio for superconducting computers could go under 100:1. For superconducting computers that would be mean ~100K physical qubits for a CRQC, two orders of magnitude away from state of the art. Neutral atoms quantum computers are amenable to error correcting codes other than the surface code. While much slower to run, they can bring down the physical to logical qubit ratio closer to 10:1.
→ Bitcoin PoW: Commercially-viable Bitcoin PoW via Grover's algorithm is not happening any time soon. We're talking decades, possibly centuries away. This observation should help focus the discussion on ECDSA and Schnorr. (Side note: as unofficial Bitcoin security researcher, I still believe Bitcoin PoW is cooked due to the dwindling security budget.)
→ team quality: The folks at Google Quantum AI are the real deal. Craig Gidney (@CraigGidney) is arguably the world's top quantum circuit optimisooor. Just last year he squeezed 10x out of Shor for RSA, bringing the physical qubit count down from 10M to 1M. Special thanks to the Google team for patiently answering all my newb questions with detailed, fact-based answers. I was expecting some hype, but found none.