Cheng Wang (ℵ)

Founder & core dev @Alephium / VM, consensus, contract language / proposed the first linear-time async Byzantine consensus algorithm

[Cheng Wang (ℵ) @wachmc]

Scaling PoW was just the beginning. Now we build the flywheel. Alignment begins. 🌀

[Cheng Wang (ℵ) @wachmc]

Crazy 🤯

[Greg Brockman @gdb]

we've found, validated, and prepared patches for almost 1,000 linux local privilege escalations using our cyber vulnerability pipeline, at the cost about $1,000 per vulnerability.

an emerging scalable approach to significantly hardening both open source and proprietary projects

[Cheng Wang (ℵ) @wachmc]

@ggwp21581779 As far as I see, the bug is XRP-specific, not something generic

[Cheng Wang (ℵ) @wachmc]

The only AI-proof problem seems to be P/NP

[OpenAI @OpenAI]

We’re releasing a broad range of new mathematical results produced by an internal frontier model.

We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.

https://t.co/7N6TPlft1P

[Alephium @alephium]

10,000,000 💥

We launched. You staked.

An important Powfi milestone, and almost halfway to the 20.5m ALPH campaign target.

You can do it 🫵

[Cheng Wang (ℵ) @wachmc]

@runchao_han @NeurIPSConf 牛逼

[Cheng Wang (ℵ) @wachmc]

He’s not done coding or math for 1+ year at least

[ShreeChaithanya @heyim_shree]

Yann LeCun: We’re not going to reach human-level intelligence or AGI simply by scaling LLMs.

“There’s absolutely no way in hell.”

“The idea that we’re going to have a data center full of geniuses is complete BS.”

“It might feel like you have a PhD sitting right beside you.”

“But that’s not what it is.”

“It’s a system with enormous memory and retrieval capabilities not a system that can genuinely come up with solutions to problems it has never seen before.”

[Cheng Wang (ℵ) @wachmc]

Right, if the proof is correct, why slow it down

[Paata Ivanisvili @PI010101]

About a year ago, Talagrand’s convolution conjecture was announced with a 40+ page proof, and later simplified by Shaposhnikov, with the help of AI, to 7 pages: https://t.co/INoxgBatiy

Since then AI has improved so much that, after playing with it a little, it rewrote the full proof in 1.5 pages and in my style (I told AI what tools I’m familiar with and asked it to stay within those limits and kept just asking "simplify proof").

As long as a valid proof exists, AI seems increasingly able to simplify it (or even find a simpler alternative proof) and rewrite it much shorter and more cleanly in your style. So I think I agree with @ChrSzegedy that human “desloping” may be a temporary issue and eventually won’t really be needed:
https://t.co/nj24wP9053

Looks like we are converging back to Perelman’s statement: if the proof is correct, no other recognition is needed.

[Cheng Wang (ℵ) @wachmc]

@ittaia Do you think the same would happen to TCS? Will frontier labs be interested in throwing decent amount of resources into TCS?

[Cheng Wang (ℵ) @wachmc]

Make DeFi great on PoW

[Alephium @alephium]

Powfi is now LIVE! 💥

The first two foundational layers of $ALPH DeFi are now available:
▪️ Concentrated liquidity
▪️ ALPH liquid staking

That also means:
▪️ ALPH x USDT liquidity can now be provided through the CLMM.
▪️ ALPH can now be staked for xALPH.
▪️ Other markets can also be added to the CLMM.

More details below 🧵

[Cheng Wang (ℵ) @wachmc]

🔥🔥🔥

[Alephium @alephium]

🚨 Powfi will launch on Tuesday!

This platform introduces two foundational layers to $ALPH DeFi:

▪️ A CLMM DEX
▪️ A liquid staking layer for ALPH

Together, they create new primitives for liquidity, staking, and capital efficiency on Alephium.

More below 🧵👇

[Cheng Wang (ℵ) @wachmc]

Mathematicians need to learn how to live with shit code

[The Economist @TheEconomist]

24 Fields Medal winners have written a letter of objection https://t.co/uY2OSfyRnI

[Cheng Wang (ℵ) @wachmc]

First principle: if you can solve math, you can solve others.

[Cheng Wang (ℵ) @wachmc]

AGI is here

[Cheng Wang (ℵ) @wachmc]

This aligns with my personal experience. I did not use any skill except for a simplification skill I made by myself.

[Dan Robinson @danrobinson]

Increasingly evident that for intelligence-bound tasks like research, the model is far, far more important than the harness/skill/prompt

[Cheng Wang (ℵ) @wachmc]

Math drama, best drama

[Emad @EMostaque]

Wow, Navier-Stokes drama

This statement is worth reading in full from Tristan Buckmaster discussing his work with @__alpoge__ and OpenAI’s upcoming Condition C/D result (!)

Crazy

https://t.co/EnCVLyjgEZ

https://t.co/ZLqBagNNcX

[Cheng Wang (ℵ) @wachmc]

13+M LoC formalizing FLT, 21 hours work, AGImath

[Leonardo de Moura @Leonard41111588]

I did not expect this. Anthropic just published a Lean proof of Fermat's Last Theorem.
The proof is +13M LoC, more than 5 times the size of Mathlib.

Kevin Buzzard's post: https://t.co/yVJ46QzsZn
The proof: https://t.co/PqAq7qc375
Anthropic's post: https://t.co/d4e1eNqlwQ

[Cheng Wang (ℵ) @wachmc]

AI slop vs human slop: pick yours

[International Cyber Digest @IntCyberDigest]

Linus Torvalds says tracking down a bug in Linux's Intel GFX Driver was a "debug session from hell." The AI helping him repeatedly called it "impossible and unsolvable" and suggested they just write a report instead.

He kept pushing. 24 debug patches and 18 kernel boots later he found the bug: one round_up() that should have been round_down().

He then let the AI write the commit message.

https://t.co/9qcHPvThzP

[Cheng Wang (ℵ) @wachmc]

Chatting with stoa AI models feels like this most of the time

[Math Files @Math_files]

Richard Feynman said that one of the joys of working with all the really smart people on the Manhattan Project was:

“You never had to explain anything twice. Everyone was paying attention. Everyone understood the first time you said it.”

[Cheng Wang (ℵ) @wachmc]

Alephium’s sUTxO already does this in production: UTXO for assets + dynamic state for contracts + composability. Best of both worlds, live today.

[vitalik.eth @VitalikButerin]

Bitcoiners deserve a lot of credit for pioneering many of these ideas (see Utreexo).

But yes, this is what the current proposed Ethereum scaling strategy looks like in action.

We want Ethereum to have the best of UTXO-style state, dynamic state, and everything in between, allowing the great majority of Ethereum's activity to be hyperscaled without sacrifice to decentralization, ease of node running and censorship resistance.
https://t.co/rVylwVtgP5

[Cheng Wang (ℵ) @wachmc]

The only explanation: this was made by Google's Gemini.

[Google Design @GoogleDesign]

Celebrating small wins is hardwired into "Achieve," our goal-tracking sample app.

We wanted the simple act of checking off a task to feel like a celebration. Instead of the standard #Material ripple, we used Styles to drop in a custom, high-contrast completion animation—specifically, a brand-colored ring that expands and fades on tap, paired with a subtle pressed-state gradient.

It lets us focus entirely on polishing those custom, rewarding micro-interactions while Material handles the foundation.

#GoogleDesign #MaterialDesign #JetpackCompose #AndroidDev #UXDesign #InteractionDesign

[Anthropic @AnthropicAI]

We asked an unreleased research version of Claude to take a stab at the Riemann hypothesis.

It didn’t solve it, but it did make strides on a related problem: it increased the lower bound for the fraction of zeros of the Riemann zeta function that satisfy the hypothesis from 41.6% to 67.2%.

https://t.co/aZDvqqhHRi