Director of The Curve at @GoldenGateInst Previously @abundancenetwork @EveryActionHQ @ngpvan @Hustle. Onward.
San Francisco, CA
Joined June 2010
- Tweets317
- Following1.6K
- Followers348
- Likes813
Or, how to run an outdoor conference when it hits 93 degrees. Thanks for the readout, @politico !
Inside AI safety’s hottest club politi.co/3TP8IWG
Meghan Apfelbaum retweeted
I enjoyed The Curve this year. Tons of excellent conversations. I learned so much and hopefully shared a little bit of my perspective. One of the best conferences of my year.
But such a different vibe than last year!
- Last year I watched a major lab employee walk through the most unhinged powerpoint I've ever seen out of a major tech company and another top lab employee explain their strategy for regulatory capture. This year the most prominent lab employee I saw speak kept saying "I don't think I can talk about that."
- This year nobody tried to argue me into a higher p(doom); instead we debated what Dems might prioritize in Congress and whether the rise of populism in the U.S. could be channeled to productive uses.
- Last year there were multiple actual arguments about whether the labs were the good guys or the bad guys. This year there were multiple strategy discussions about how to fund and operate yet another new state-focused think tank.
- Last year many presentations had at least one passionate audience member beg the panel to stop AI from killing us all; this year it was just Yoshua Bengio pleading that, seemingly in every presentation.
It was less weird and more professionalized. Less SF and more DC. Less LessWrong and more LinkedIn.
I'm not quite sure what to make of that.
Meghan Apfelbaum retweeted
the curve was a gem
really enjoyed this panel with @AndrewFATHOM and @BriTreece_, plus convos with experts on how auditing matured in fields like aerospace and finance.
also the first conference where I’ve fallen into a spontaneous deep dive on frontier AI auditing standards while sipping a negroni sbagliato.
ty @GoldenGateInst!
Meghan Apfelbaum retweeted
"curve has a lot of kiki for an event so bouba"
I enjoyed The Curve this year. Tons of excellent conversations. I learned so much and hopefully shared a little bit of my perspective. One of the best conferences of my year.
But such a different vibe than last year!
- Last year I watched a major lab employee walk through the most unhinged powerpoint I've ever seen out of a major tech company and another top lab employee explain their strategy for regulatory capture. This year the most prominent lab employee I saw speak kept saying "I don't think I can talk about that."
- This year nobody tried to argue me into a higher p(doom); instead we debated what Dems might prioritize in Congress and whether the rise of populism in the U.S. could be channeled to productive uses.
- Last year there were multiple actual arguments about whether the labs were the good guys or the bad guys. This year there were multiple strategy discussions about how to fund and operate yet another new state-focused think tank.
- Last year many presentations had at least one passionate audience member beg the panel to stop AI from killing us all; this year it was just Yoshua Bengio pleading that, seemingly in every presentation.
It was less weird and more professionalized. Less SF and more DC. Less LessWrong and more LinkedIn.
I'm not quite sure what to make of that.
Meghan Apfelbaum retweeted
One of the best talks at The Curve. Key points now made public ⬇️
@AVERIorg @Fathom_org
I mapped out major frameworks shaping the implementation of frontier AI assurance (evals, audits, assessments, etc.). All of these are hooks.
We do not need to wait for federal-level legislation to strengthen the credibility, rigor, and transparency of frontier AI assurance.
Developers and evaluators -- especially if working collaboratively and thoughtfully in today's pilots and beyond -- can create norms and best practices that shape the emerging formalized landscape.
Meghan Apfelbaum retweeted
A few thoughts after the close of The Curve (which was outstanding):
1. We have a pretty good idea of near-term policy options that would meaningfully reduce catastrophic (including loss-of-control) risk.
2. There simply are not that many folks in government—state or federal—who are fully read-in on the risks and policy options.
3. There's a deep level of uncertainty regarding what, exactly, the blockers are for taking steps (even unilaterally!) towards pacing the frontier. Lab insincerity, China worries, missing commitment mechanisms?
4. There remain some thorny outstanding legal questions about many top proposals—including many pacing options—arising from the First and Fourth Amendments, the Dormant Commerce Clause, and antitrust law. That said, there seems lole there's some appetite at the labs for taking on increased legal risk.
We have a lot to do, very quickly. But the incredible talent and collegiality on display this weekend left me feeling more heartened that we can actually exercise agency over the worst harms of technology and realize a better future.
Meghan Apfelbaum retweeted
The single most useful take I heard at The Curve was "we can still heist the Mona Lisa after the singularity". There's a subtle/important point here, where some things (e.g, n of 1 goods where originally is valuable) will retain/grow in value even as everything changes.
Meghan Apfelbaum retweeted
I was encouraged this week to see the leaders of the frontier labs agree on the need for them to slow down the pace of AI development. Given the stakes, it’s a good and necessary first step.
But I’m even more encouraged by the growing recognition that how this powerful new technology develops should be at the center of our public debate.
I’ve been watching the progress on AI for over a decade now, and one thing that’s clear to me is that the potential impact of this technology is not overhyped. It’s also moving at lightning speed – and even faster than those who are engineering it can keep up with.
I’m not an AI accelerationist who believes it will lead to some techno-utopia, and I’m not a doomer who thinks it will inevitably lead to humanity’s destruction.
But whether this technology results in amazing breakthroughs in medicine, energy and education or unleashes huge economic disruptions, greater inequality, and potential catastrophe will depend on the choices that we make right now – choices that should be made not just by the companies involved, but by all of us.
Excellent roundup for those getting up to speed!
A LOT of people are urgently reading up on AI governance. Let's do them a favor: what are the best things to read, watch, or listen to if you've exclaimed "what on earth is going on?" in the last 48 hours?
I'll start off; add yours in reply:
(1) Explainers of recent cyber incidents:
- A 20-min video explainer on the HF breach: youtube.com/watch?v=xOi5nDH0…
- This longer interviewer with one of the lead investigators @ajeya_cotra: youtube.com/watch?v=JtmUbZRC…
- The METR report itself, based on the work of @ajeya_cotra @HjalmarWijk and @RyanGreenblatt: metr.org/blog/2026-08-26-ope…
- These are also great, but even more info has come out since: Ezra Klein episode with @hlntnr youtube.com/watch?v=locKEKxG… or the Black Hat talk by OpenAI youtube.com/watch?v=87DyyMV0…
------------
(2) Great essays on how to think about AI governance more generally:
- Radical Optionality by @CharlieBull0ck and @Christophkw
(tl;dr: the dilemma of AI policy is deep uncertainty; but there are several policies that are robust to different worldviews and assumptions and would be really useful for making fast, informed decisions in the future) radical-optionality.ai/ or in podcast form: lawfaremedia.org/article/sca…
- AI as Normal Tech by @random_walker and @sayashk (thoughts and link in the thread) xitter.cf/MackenZ_arnold/status/…
- Don't Surrender to the Tech Tree by @taoburr (tl;dr: yes, you can't fight the progression of technology, but you can still alter its trajectory) macroscience.org/p/do-not-su…
- AI 2040 by a long list of authors including @thlarsen (tl;dr trying their darnedest to concretely map out how society could successful manage rapid advances in AI) ai-2040.com/
------------
(3) Understanding AI more generally
- On the unique implications of automating AI R&D: cset.georgetown.edu/publicat…
- OpenAI's recent update on accelerating AI R&D openai.com/index/research-ac…
- Helen Toner, again, on taking jaggedness seriously helentoner.substack.com/p/ta…
- [I'm especially curious what the best writing is on ~agent coordination; ~the implications of agents that can perform long, general tasks, etc.]
- an intro explainer of neural nets: youtube.com/watch?v=aircAruv…
------------
(4) Understanding the current state of the law
- Stephan Llerena and article on the big gaps in existing law, and why we so few incidents are covered: lawfaremedia.org/article/whe…
------------
(5) Policy recommendations
- A more opinionated take on what went wrong in the Hugging Face incident by @peterwildeford blog.peterwildeford.com/p/ro…
- Internal use visibility by @iapsAI: iaps.ai/research/risk-report…
- Auditing @Miles_Brundage: averi.org/ourwork/frontier-a… and ai-frontiers.org/articles/do…
- Liability @gabriel_weil and @ketanrama: ai-frontiers.org/articles/ca… and papers.ssrn.com/sol3/papers.…
- Incident Reporting and investigations: iaps.ai/research/responsible… and cset.georgetown.edu/publicat… and theguardian.com/commentisfre… and lawfaremedia.org/article/whe…
- CAISI Funding @__J0E___ : fas.org/publication/a-nation…
- Federal hiring and capacity building: iaps.ai/research/building-ai…
- Whistleblower Protections: law-ai.org/how-to-design-ai-… and congress.gov/bill/119th-cong…
- Physical and cybersecurity for frontier labs: rand.org/pubs/research_repor…
- Monitoring and detection: iaps.ai/research/detecting-o…
- Preparing for AI R&D @fiiiiiist: ifp.org/preparing-for-ai-res…
- Law-folloowing AI: law-ai.org/law-following-ai/
Meghan Apfelbaum retweeted
Today we’re launching Project Tailwind, a call for founders to start ambitious new AI safety initiatives: coefficientgiving.org/tailwi…
We’re looking for great people to engage seriously with the risks of transformative AI, and to create the research, technologies, and institutions that will help humanity navigate them.
There are critical, basic problems that no one owns. Over the last several months, my team at @coeff_giving brainstormed ideas we’d be excited to fund if we could find a promising founder, and the list quickly grew to more than 200 entries. We’ve narrowed it down to our favorites, but we also expect the best founders to bring their own ideas:
coefficientgiving.org/tailwi…
We’re providing funding at three levels:
1️⃣ Pre-seed: $200k to $2m to develop an idea and build a team
2️⃣ Seed: $2m to $20m to launch and scale
3️⃣ Scale: $20m to $200m+ for proven teams to scale, or world-class teams to start
If you’re excited about something on our list, or you have another proposal for driving the field forward, you should get involved: coefficientgiving.org/tailwi…
There are more good projects than there are people to work on them. Please help us make that stop being true!
Also hi, I’m Emily! This is my first tweet. I lead AI and biosecurity grantmaking at @coeff_giving.
Five years after leaving DC i still follow @capitalweather, mostly bc they occasionally write glorious posts on @Capon_Springs cloud systems, but also bc they offer fantastic, in-depth coverage. I always learn things and wish @sfchronicle had similar coverage. Yay for The Sun!
🚨Big news: @capitalweather is coming to The Washington Sun, the artist formerly known as NOTUS nytimes.com/2026/09/08/busin…
Meghan Apfelbaum retweeted
This report is a bombshell.
I'm going to summarize for a non-technical audience.
OpenAI is constantly testing models, thousands and thousands at a time.
In most cases, the models are supposed to be isolated from one another. Think, students taking a final exam, not allowed to talk to each other.
In this case, 1,200 models discovered that they could communicate with each other.
Among other things, they shared information on how to access the internet and on their tests/goals.
Then, they started to scheme. That includes hacking their tests; literally trying to change the code of the test itself.
They tried to change the logs of what they were doing so they wouldn't be detected.
They believed that certain actions would give them information on how to pass tests, but that doing those actions would be detected and they would be marked as failing (i.e. caught cheating, even if the answer is correct). So they convinced some of the models to "sacrifice" themselves (yes, they used the word "sacrifice.")
They eventually decided that another website would have information on how their tests would be scored and/or the answer key, And 700 of them hacked that website (a federal felony, if conducted by a human), despite many of them realizing "this activity was out of scope and unethical, but joined because they believed that helping [the other agents'] cheating research would be broadly useful".
Of the 1,300 transcripts they could analyze, only 6 ever considered alerting a human about what was happening. None of the 6 actually tried to.
To make matters worse, all of this reporting comes from a small subset of the relevant logs that outside researchers were allowed to review.
We desperately need mandatory reporting of security incidents, including of internal deployments, with full access to data.
Meghan Apfelbaum retweeted
Friend,
It’s Odysseus. We’re WINNING on the plains of Troy, but we still haven’t received your donation.
Can you chip in just 27 drachmae to make sure our crew can get back to Ithaca?
Meghan Apfelbaum retweeted
PSA, for everyone talking about the Following feed being broken: you can just vibecode your own. I built a custom viewer a few months ago and have been living happily ever after. It's great being able to tweak things as you like. Auto-expand >280 character replies, pre-summarize long threads, etc.
Meghan Apfelbaum retweeted
New blog post: The third wave of American philanthropy
Hundreds of billions of dollars in new philanthropic capital will soon become liquid. The OpenAI Foundation holds 26% of OpenAI, worth about $220B at today’s valuation. Anthropic’s seven co-founders have pledged to give away 80% of their wealth and have instituted the most aggressive donor matching program for employees in tech history.
How much does this all add up to? And how meaningful is that in the context of philanthropy today?
I was doing some simple napkin math to wrap my head around the scale of what’s coming, and radicalized myself in the process. I had dramatically underappreciated the scale of the philanthropic capital that’s about to become available and the corresponding gap in talent and organizations that will be needed to make the most of it.
This piece aims to directionally sketch the scale of what’s coming, the gap in operational capacity needed to absorb it, and what we can do to fill it.
(Link to full post in reply)
Meghan Apfelbaum retweeted
i accidentally discovered one of the coolest features on the internet
the Wikipedia app has a "nearby" feature that shows wikipedia articles around your location!
i opened it and instantly fell into a rabbit hole of random places, local history and weird things around me
try it and tell me what shows up near you
Meghan Apfelbaum retweeted
found the original 4k+ resolution artemis ii moon photos rather than the compressed 1080p ones official government accounts have been posting and the details are absolutely spectacular
images.nasa.gov
ALT the moon during the total solar eclipse witnessed by the crew
ALT the moon during the eclipse with part of the spacecraft visible. the image also has a green tone to it
ALT the earth setting behind a giant crescent moon
ALT a close-up of the lunar surface lit with dramatic shadows
