arkananta

[Claude @claudeai]

We’re renaming our Max plans:

Max 5x → Max
Max 20x → Ultra

Max is still $100/month, and Ultra is still $200. If you’re a subscriber, there’s nothing you need to do.

We’re also removing the 5-hour limit for verified Ultra accounts, starting today with most existing subscribers. Newer accounts keep a temporary limit until they’re verified, which helps us prevent fraud and abuse. You'll get an email when it's removed.

Weekly limits remain unchanged. View our plans here: https://t.co/niRpyGF5Me

[lauren @poteto]

we will need to rebuild and rewrite much of software to adapt to a new, faster pace.

code used to arrive one drop at a time. soon, if not already, code will be written as if it were a continuous stream, like a violent river twisting and turning as it pleases.

this is not a new thing: big tech cos have had to deal with this with the enormous scale of their engineering teams. but now ai has brought an incredibly elastic and capable workforce wielded by every engineer. this is your problem now, and the only way to adapt is to evolve your systems so agents - even and especially the ones with little context about the right way of doing things - can thrive. make the easy thing the right thing.

your codebase is becoming organic architecture. agent contributions grow around the constraints and guardrails you’ve designed. good software engineering matters even more now! and no, the continuous stream of code is not something you have to watch helplessly. be more ambitious and design systems, frameworks, and languages to control the chaos.

the time for mourning coding is long over

[OpenAI @OpenAI]

Privacy should advance as fast as intelligence. OpenAI Private Intelligence gives businesses stronger controls over their data while using our most capable models.

We’re building these protections in close collaboration with some of our largest customers to help businesses apply frontier AI to their most sensitive work.
https://t.co/BiA4N8FQVH

[jeff.hl @chameleon_jeff]

Growing up in the United States, NYSE was synonymous with the story of American capitalism. I vividly remember learning about the Buttonwood agreement in 9th grade history class. 24 stockbrokers met under a tree on Wall Street and formed the beginning of what would become the world's financial center. From pits to computers to now onchain markets, America has always led the way in innovating markets to improve price discovery and capital formation. Today the next chapter begins with ICE, trade[XYZ], and Hyperliquid.

ICE started as an electricity-trading platform in 2000, growing to acquire NYSE itself in only 13 years. It is a key infrastructure provider of America’s energy, bond, and mortgage markets. ICE is a rare story of exponential growth of a financial giant over decades, continually embracing innovation and technology.

trade[XYZ] was the first HIP-3 deployer and responsible for spearheading the flourishing global RWA perpetual market today. Only a year ago, trade[XYZ] launched its first RWA perpetual markets. They took a bet on HIP-3, which had just launched after months of tireless development. Having followed their journey from day 1, I cannot overstate how much Shoku and the team have poured into growing these markets to a genuine source of price discovery for the most important assets in the world.

Over the past three years, Hyperliquid has pioneered onchain infrastructure to house all of finance. Hyperliquid is nothing without its world-class builders. I am honored that trade[XYZ] and ICE have chosen to build on Hyperliquid to bring perpetual contracts to America.

When I first spoke to Jeff Sprecher around a year ago, he asked what success looks like to me. I thought for some time and joked that it would be seeing ICE building on Hyperliquid's technology. I could never have predicted the progress that we've made as a community in a single year to make this come true. Excited to see what we can build together next.

[Thariq @trq212]

very weird thing happening rn

technical people are sad, they think their skills are now useless

non-technical people are desperately wishing they were more technical so they could use agents better

[Felix Rieseberg @felixrieseberg]

The coding interview is dead, at least for my team at Anthropic. I've seen enough to know that it no longer provides signal. I removed it from loops this month.

I have a spicy, optimistic take - I think there's an opportunity for junior engineers: https://t.co/PVvpQCbQtK

[Axiom @axiommathai]

The largest math proof in human history is now computer-verified.

Today, Axiom announces a complete Lean auto-formalization of the Classification of Finite Simple Groups, the "periodic table of symmetry."

About 15,000 pages, built by over 100 mathematicians across generations.

[arkananta @alistarkananta]

Idk after 6.1-terra pop up I think that the 6.1-sol usage has drown much faster than before. Like I was just on two prompts with 6.1-sol in extra high, previously it gotten me to 30% of usage remaining is actually limit after 6-8 prompt, but now only with two prompt it cost same

[OpenAI @OpenAI]

GPT-6.1 Terra: delivering fast and capable computer use at a lower price.

GPT-6.1 Terra understands what’s on screen, takes action across apps, writes naturally, and is a more capable model for your whole workday with the efficiency to take on more of it.

[levent @__alpoge__]

“The core algorithm was found on October 16 by an internal Claude research model with 14M output tokens and no human input. Anthropic researchers worked with Claude to improve the presentation, resulting in this paper.”

https://t.co/rZLajqbVH8

[ellington @not_ellington]

It is such a funny twist of fate that OpenAI, led by an ex-YC product guy, is putting out groundbreaking math/physics/cs research while Anthropic, led by a physics PhD, is primary putting out a coding product.

[Sachin Konan @SachinKonan]

Will your ICLR paper get accepted? 👀

Introducing PaperScorer, our NeurIPS '26 project that predicts acceptance from anonymized submissions.

It beats GPT, Gemini, and Jev, with well-calibrated probabilities.

Try it on your paper today: https://t.co/27XsDaHZzF
Blog: https://t.co/QxJkwCGA9i

Details in thread 🧵

[Anthropic @AnthropicAI]

Anthropic has filed an S-1 registration statement with the SEC related to its proposed IPO.

Read more: https://t.co/ofhv0DK3Zp

Legal disclaimer: A registration statement relating to these securities has been filed with the SEC but has not yet become effective. These securities may not be sold, nor may offers to buy be accepted, prior to the time the registration statement becomes effective. This post does not constitute an offer to sell or the solicitation of an offer to buy these securities, nor shall there be any sale of these securities in any state or jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such state or jurisdiction.

[arkananta @alistarkananta]

@katiekschwartz @a16z @algravithm

[arkananta @alistarkananta]

netflix #zonauang

[kori rogers @korigero]

Scott Wu vs. the models

[Jon Barron @jon_barron]

Hi all, I have a new result I'm excited to share. It turns out that *all existing implementations* of softmax and cross-entropy (that's JAX, PyTorch, textbooks, etc) have a subtle bug --- two bugs, actually. A simple rewrite fixes both, and eliminates "slingshots" when grokking:

[SAIR @SAIRfoundation]

Open Math Harness is open source: the runtime of Open Math OS, infrastructure for Math 2.0.

Built for everyday math research: agents on open models with math and scientific computing tools, parallel exploration in Ultramath, autoformalization in Lean.

https://t.co/EripsqJuP8

[Brandon Zhao @joiedeposter]

Introducing beignet, a new neural field architecture!

beignet uses a multiresolution fourier frequency pyramid to achieve faster convergence and higher precision when solving PDEs and finding singularities.

Teaser: here is beignet at work fitting an image (super fast)!

[Elon Litman @elon_lit]

There is an (unpatchable?) supply-chain zero-day in PyTorch autograd that allows a regularization term to use the model's weights as RAM and SGD as its CPU clock to run any computation during training.

[Kieran Didi @DidiKieran]

Avengers assemble: 1 year BakerLab + NVIDIA GenAIR = 🔥 https://t.co/Cd2qiugCJo

Presenting RFD4-Proteina, our latest protein design model, significantly better and faster than everything we compared against, both in silico and in the lab! 1/30