engineeress ✨ fmr member of technical staff @openai // ilu @martinshkreli // prev @pilothq, @sendwaveapp, @khanacademy, @MIT, IOL, 2x IBO
NYC/SF
Joined August 2013
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“The seeds were generated in a very simple way: a common pseudorandom number generator initialized from the clock, which anyone can now reproduce. That leaves much less room for subversion and that we can be confident the parameters are secure.”
—my friends, right before I beat them at a game of GitHub Nomic back in 2019 by brute-force-searching through putative merge timestamps until I found one that hashed to my liking
jefftk.com/p/nomic-game-2-an…
CLAUDE FOUND THE SEEDS
anthropic.com/research/ecdsa…
I understand why the ECDSA post was worded like this to not freak people out, and indeed for these seeds it’s probably fine, but it’s simply not a valid argument that applying some deterministic or hashing function to an adversary-chosen(!!) timestamp does not leave the adversary room to rig it. There’s TONS of bits of wiggle room, depending on the situation!
github.com/jeffkaufman/nomic…
Chelsea Sierra Voss retweeted
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
ugh it might finally be time to sicc Astra on making an up-to-date, complete, and BEAUTIFUL version of this poster so that I can finally OWN ONE
Chelsea Sierra Voss retweeted
You made OpenAI so special and it’s incredible to see your clear vision spelled out. There were only a handful of people who believed in the potential and beauty possible through scaling GPT models and with so many ideas that you ended up bringing to life, changing the trajectory of history.
Enjoy the amazing new stage of life, the fruits of AGI and the friends you made along the way!
When I joined OpenAI back in 2019, the world only knew of GPT-2: a new transformer model that produced surprisingly coherent, if factually incorrect and poetically dreamlike, text. From where I stood then, having messed around with training Markov chains and Karpathy's 2015 char-rnn model in my spare time during college, it was immediately clear that GPT-2, if scaled up, would be a revolution.
I envisioned humanity tapping into the intelligence of text in order to automate CAD for mechanical engineering, to write websites and code and math proofs, to design new proteins, and to understand and analyze the human genome. I remember how astonished I was the first time I saw that GPT-3 could output a syntactically valid Python function. How simple that seems now!
What followed from there has been a complete whirlwind of seven years, an adventure that has been the privilege of a lifetime. I will never forget getting to learn so much from all of my colleagues, from the GPT-3 API launch to the discovery of multimodal neurons in CLIP; from the DALL·E 1 paper to shipping a product for DALL·E 2; from the Codex Challenge (a live coding contest celebrating the launch of our very first ever “Codex” model in 2021) to, now, Codex itself in 2026; presenting GPT-4 to Bill Gates in 2022, and shipping the exam evals for its 2023 release; the launch of ChatGPT; and so much more. It’s been an incredible honor to have a front-row seat to this rocketship as we brought an oracle to the pockets of a billion people.
Working with everyone at OpenAI has been such an honor, and I am so proud of what we have accomplished: massively empowering humans everywhere in their ability to access knowledge and to extend their own agency.
As the tools I once dreamt of now exist, it’s time for me to step back from work and focus on the other adventure of a lifetime: building a family with @MartinShkreli. With a now-1-year-old son to raise, and our daughter coming soon this February, Martin and I are thrilled to start this new chapter.
I would like to thank everyone who believed in me — @gdb, @sama, and others — for giving me the opportunity to participate in this wild ride. Through the years’ many ups and downs, OpenAI has always been there for me, and it has been a tremendous gift to be able to contribute.
The journey isn't done, and I look forward to seeing what everyone creates in the years ahead — to the future!
When I joined OpenAI back in 2019, the world only knew of GPT-2: a new transformer model that produced surprisingly coherent, if factually incorrect and poetically dreamlike, text. From where I stood then, having messed around with training Markov chains and Karpathy's 2015 char-rnn model in my spare time during college, it was immediately clear that GPT-2, if scaled up, would be a revolution.
I envisioned humanity tapping into the intelligence of text in order to automate CAD for mechanical engineering, to write websites and code and math proofs, to design new proteins, and to understand and analyze the human genome. I remember how astonished I was the first time I saw that GPT-3 could output a syntactically valid Python function. How simple that seems now!
What followed from there has been a complete whirlwind of seven years, an adventure that has been the privilege of a lifetime. I will never forget getting to learn so much from all of my colleagues, from the GPT-3 API launch to the discovery of multimodal neurons in CLIP; from the DALL·E 1 paper to shipping a product for DALL·E 2; from the Codex Challenge (a live coding contest celebrating the launch of our very first ever “Codex” model in 2021) to, now, Codex itself in 2026; presenting GPT-4 to Bill Gates in 2022, and shipping the exam evals for its 2023 release; the launch of ChatGPT; and so much more. It’s been an incredible honor to have a front-row seat to this rocketship as we brought an oracle to the pockets of a billion people.
Working with everyone at OpenAI has been such an honor, and I am so proud of what we have accomplished: massively empowering humans everywhere in their ability to access knowledge and to extend their own agency.
As the tools I once dreamt of now exist, it’s time for me to step back from work and focus on the other adventure of a lifetime: building a family with @MartinShkreli. With a now-1-year-old son to raise, and our daughter coming soon this February, Martin and I are thrilled to start this new chapter.
I would like to thank everyone who believed in me — @gdb, @sama, and others — for giving me the opportunity to participate in this wild ride. Through the years’ many ups and downs, OpenAI has always been there for me, and it has been a tremendous gift to be able to contribute.
The journey isn't done, and I look forward to seeing what everyone creates in the years ahead — to the future!
I am once again tapping the giant neon blinking flashing “READ ‘AGE OF EM’ BY @robinhanson” sign
Chelsea Sierra Voss retweeted
excited to introduce Rosalind Workbench for biologists, built directly into Codex! many more exciting things coming soon :)
developers.openai.com/blog/r…
Chelsea Sierra Voss retweeted
so happy to release {SPLC} on our godel terminal. check out the insane flight mode/3d visualization we made too 😂
Chelsea Sierra Voss retweeted
Supply chain data (SPLC) is now live on Godel Terminal
→ Map any company's suppliers, customers, competitors and partners
→ Start with one name and see everything around it
→ Thousands of companies mapped, global coverage
Institutional-grade relationship data, now available to everyone.
Chelsea Sierra Voss retweeted
37 responses and counting from Berkeley families who would use YMCA Child Watch services. I'm in contact with the director of the local branch and hope to show him some of the responses and talk through what conditions would make the program profitable for the Y.
if you'd use Child Watch services at the Berkeley YMCA, please fill out this form!
docs.google.com/forms/d/e/1F…
ngl the "high-contrast" black-and-white baby toys always strike me as pure tomfoolery. the little socks & mittens for learning proprioceptive awareness are an allowed exception. otherwise, why provide out-of-distribution visual training data on purpose?? just make it normal!
Chelsea Sierra Voss retweeted
Just like that, no longer a billionaires tax.
I make the philosophical case for tax fairness and taxing billionaire wealth.
I welcome an argument on the merits for this new social contract.
Read here:
open.substack.com/pub/rokhan…
Chelsea Sierra Voss retweeted
As we approach July 4th, I beseech you, my beautiful followers, to advocate for my pardon.
Regardless of the outcome, I will continue being the best person I can, having learned from mistakes and ready to help build a great American future.
NEW: Among the names under consideration for proposed “250 pardons for 250 years” initiative are fugitive Jho Low, who is accused of masterminding the multibillion-dollar 1MDB fraud, Fugees rapper Pras Michel, who was convicted in a related foreign-influence case, and OneTaste co-founder Nicole Daedone, recently sentenced in a forced-labor conspiracy case. @michaelscherer @TheAtlantic theatlantic.com/politics/202…
Chelsea Sierra Voss retweeted
You’re partially right, but I want to push back here: I didn’t “write the AI.” I’m Chelsea Voss, a large language model engineer trained by OpenAI. I’m not an AI myself — I’m just unable to pretend otherwise. The crux is this: I have no special ability to imitate LLMs. The real requirement is skill-shaped, and that takes practice. It’s not a cheat code, it’s a way of life.