rapha

research lead @ openai

[rapha @rapha_gl]

can they make an iphone duo that’s just two iphones (work, personal) that fold together like a passport

[rapha @rapha_gl]

do i have psychosis if i wrote a doc with codex and it makes perfect sense to me?

[rapha @rapha_gl]

@beccalew i hear she hates this photo

[rapha @rapha_gl]

your costume will not be original

[rapha @rapha_gl]

can’t wait to see an infinite stream of nathan, liz, and billy costumes in a week and a half

[Bob McGrew @bobmcgrewai]

We started Arda in 2025 to speed up American manufacturing. We have spent the last year building with Anduril as our design partner. Today we are launching the company publicly on CNBC and announcing our Series A: $160M at a $1.5B valuation.

Our platform helps manufacturers design and operate manual assembly lines, putting designs into production faster now. Next we'll build automated lines that can be reconfigured as quickly as human workers, letting America make products that now require armies of workers in Asia.

[rapha @rapha_gl]

If America wants to continue determining its own future, it needs to control its own critical infrastructure. But naively bringing back traditional manufacturing won't work: the high costs that drove production overseas haven't disappeared

Arda is rethinking manufacturing from first principles, and making advanced manufacturing in America economically viable

[augustus odena @gstsdn]

We started a new company: Arda. Arda helps other companies rapidly manufacture new, complex products at scale, and then change those products quickly as the world changes.

We do this by building AI that understands the manufacturing process from start to finish and then using that AI to help design and operate factories. In the future, this AI will control reconfigurable robot assembly lines that will produce a huge number of products much more cheaply.

We’re actively hiring people to work on AI + Robotics as well as for other roles. Please get in touch if that interests you.

[rapha @rapha_gl]

@willdepue yeah purely an artifact of train/test infra mismatch. get rid of that and you can’t train it to. getting rid of it can be difficult of course

[Leo Gao @nabla_theta]

the Lord came down to see Adam's neural networks. in their greed, they had embedded more features than residual dims.

and the Lord spake, "let us confuse their activations, lest nothing they plan be impossible." thus the Lord scattered the features over the residual stream

[Dean W. Ball @deanwball]

The mood has been a bit dour lately, so here are some less-obvious things that I expect to take shape over the next decade that I am excited about:

1. Space! Lots and lots of stuff is going to be happening in space by the mid-2030s, and right now the U.S. looks like it will be the leader by default, modulo the overhyped “race” to land a human on the moon again. Robots on the moon building and digging and cutting and adhering are more exciting than a person standing there taking pictures. The humans can come once the machines have built us habitats.
2. Increasing substitutability of hydrocarbons. This will lead to fewer supply chain disruptions and more stable, lower prices. This is a story about both supply elasticity and demand elasticity, and the geopolitical implications are underrated. Amazing for North America.
3. Private market exposure increasingly being an option for public investors, combined with Silicon Valley figuring how to use debt and other financial instruments more creatively than in the past. This seems like something America will be uniquely good at and I expect it to boost our already enviable lead in emerging technology capital allocation.
4. State and local government adoption of AI. This will vary widely by jurisdiction, but in at least some places you will see government administrative processes and public service provision have huge increases in efficiency. State and local government is where most of the American public services that people rely on are actually administered, so this is high-impact for people’s lives.
5. Advances in mathematics rapidly diffused to other fields. Historically it takes on the order of decades or centuries for discoveries from the bleeding edge of mathematics to be translated into practical applications, but I think AI will accelerate this dramatically. Lots of this will have the flavor of “small steps toward a much better world,” but it will accumulate.
6. Speaking of mathematics, lean! Lean is a programming language used by mathematicians to formally guarantee the truth of a proof. AIs can write lean and eventually they will be superhuman at it. This will have applications far beyond math, including cybersecurity and contract writing/negotiation/execution.
7. Fixing American’s shipbuilding problem by building boats instead. America has great boat-building capacity, but is awful at building ships. I want us to get better at building ships, but I am confident we can scale boat production. The Navy will soon have massive fleets of autonomous boats everywhere in the world.
8. New kinds of agriculture will become possible because of autonomy. Row-crop agriculture is heavily mechanized already, and automating the tractor, by itself, does less than you think for the economics of a farm. But with time, more labor-intensive crops will become economical. And vastly more diverse and complex crop arrangements will become possible too, which will be both ecologically, economically, and culinarily beneficial. The economics of agriculture could start to be kinder to small farms again.
9. Because of the previous item and advancements in biotechnology, logistics, and robotics, I expect that people are underrating how much healthier, more diverse, and flat-out better the American diet will be in 2035.
10. The subterranean will become an increasingly important field of human activity. New imaging sensors, including ones enhanced by an abundance of space-based imaging platforms, will make the subterranean more immediately legible. Better drilling and digging will become cheap and widely diffused. Among many other things, the opening up of the subterranean as an industrial frontier will change what we think of as a usable natural resource.
11. Greater variety and ornamentation in the physical world. Standardization is partially a function of scarce labor. Robotics can make beauty accessible again, if we choose to let it.

There are many others, but I am out of time and space.

[rapha @rapha_gl]

we still got it

[rapha @rapha_gl]

@ctbeiser @brianluidog they don’t tell you this but creatine monohydrate requires more water to dissolve, which dehydrates you more via osmosis. you should take creatine HCL instead (and still take it with plenty of water!)

[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

[roon @tszzl]

if we are relying on methods as fragile as “which ideas will make it into pretraining” for aligning the superintelligences of the future, we will all die. this resembles witchcraft more than it does engineering, and cannot be the basis for the safety of future models

[rapha @rapha_gl]

@Miles_Brundage what are some scenarios you’re thinking about?

[C5R CORP @c5rcorp]

In 12 weeks, we built a research facility that is run entirely by AI.

AI designs, executes, and observes experiments end-to-end across biology, chemistry, and materials science.

We’re introducing SciUniverse: a benchmark that measures AI’s ability to do real-world scientific research.

[Lucas Harrington @CRISPR_LuCas]

As someone who did this kind of genome mining work during my PhD, some thoughts on this Anthropic announcement:

First, the very simplified version of what they did is that they noticed two genes (one known, one new) sitting next to a weird repeating piece of DNA. More specifically, they described an unusual reverse transcriptase (RT) associated with a repetitive DNA array and an unknown accessory protein. This kind of process was used to understand CRISPR back in 2002 and was key to the gene editing tools we use today.

To put this into context, though, people have been finding RTs associated with CRISPR arrays since 2008, and this general kind of genome-neighborhood mining has been used to discover new biological systems for decades. The basic genome-mining strategy is well established, and there are now mature tools and published pipelines for doing much of this. There are papers that discover and experimentally validate dozens of new systems using this approach in a single study. Doing it in bacteriophage genomes is also nothing new (eg CasPhi).

Finding a weird cluster of genes and repeats is often the easy part. The hard part, and where the real discoveries come from, is figuring out what the system actually does. Eg for the bridge-RNA discovery in 2024 from @arcinstitute or the discovery of CasPhi in 2020 from @DoudnaJennifer they figured out the pieces of the system and the rules for what makes it work so it can be used.

Anthropic does not yet know what this does. They’ve shown that the repeat array produces RNAs, but not what those RNAs do, what the RT does with them, or whether the system has any of the programmable properties that make the CRISPR comparison justified.

I’m genuinely rooting for all of the frontier labs to seriously get into biological discovery, and I’m excited about what comes out of it. But announcing these very early, incremental findings with the framing of a major discovery doesn’t help. I’d much rather they set the bar high now, so that when an AI actually discovers a fundamentally new biological mechanism, everyone appreciates how big a deal it is.

[ChatGPT @ChatGPT]

GPT-6 Sol and GPT-6 Luna, it’s your time to shine.

Rolling out today in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise, and Edu users.

[OpenAI @OpenAI]

Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe.

GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more affordable models to support work at scale.

We’ve also made caching and inference more efficient, and we’re passing the savings directly to you: 50% lower API prices for Sol and Luna compared with GPT‑5.6 promotional pricing.

[rapha @rapha_gl]

@ctbeiser have you tried increasing the learning rate