Data scientist. Recovering economist. Currently snobby about cheese. Trying to learn how to persuade people instead of just being right.
London, England
Joined September 2007
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Tobias Schmidt retweeted
I wonder if data quality issues, data cleaning choices, underpowered pre-trends, or endogenous treatment timing would flip results more than 0.6-2.1% of the time
Nahhh let's keep focusing on negative weights
How different are different differences-in-differences? The answer may (or may not) surprise you
New working paper, building on a dumb tweet from earlier this month teapawt.net/instrumenthull/status/…
A short summary follow:
Tobias Schmidt retweeted
We have discovered a substantial number of vulnerabilities in the German legal system using LLMs.
These may enable access to confidential documents, travel without an otherwise required visa, enforceable leave for soldiers at NATO’s JSEC, and more.
Similar to computer systems, the written law can contain vulnerabilities that invite exploitation. In our blog post, we share a selection of vulnerabilities, and present potential exploits for each. To our knowledge, none of these have been previously recorded. We share only those vulnerabilities whose exploitation we believe would not cause serious harm.
blog post: felixringe.com/legal-exploit…
Tobias Schmidt retweeted
This is fascinating stuff - what happens when you boost exactly one neuron in a small LLM and see which ones change the answer to "Who are you?" neuronpersonas.com/
Tobias Schmidt retweeted
I am retracting this. It appears that the article is miscoded. The month labeled as the month of Ramadan in the paper corresponds to the month before Ramadan in the data. More below:
This quoted post is unavailable.
Tobias Schmidt retweeted
The finding has large implications in itself (US productivity growth may have peaked before WWII rather than the postwar boom), but what fascinates me most is the method.
The authors use LLMs to extract prices and product characteristics from 5.1 million Sears catalog listings from 1900 to 1990. That lets them estimate how much prices for consumer goods rose after accounting for improvements in quality (e.g. icebox → electric fridge).
This opens up obscenely broad research agendas. Old books, catalogs, newspapers, imperial records, archives full of evidence that would be almost impossible to structure manually can now become datasets. Questions in economics, history and politics that were previously prohibitively labor intensive to investigate are now practical research projects.
Excited to share our new working paper: how much did the US standard of living really rise over the twentieth century — and when? With @bhwittenbrink
Using 5.1 million Sears catalog listings, we build a quality-adjusted price index for consumer goods, 1900–1990. Two headline findings: growth was much larger than official statistics imply, and its peak came before WWII, not after. (1/9)
Lots of very dark things in Samsung TVs
Tobias Schmidt retweeted
I think this oversells what formal verification can hope to achieve and is not helpful. @hillelogram, who has spent a lot of time in FV recently summarised it like this: teapawt.net/hillelogram/status/210…
Tobias Schmidt retweeted
OpenAI says the PHP security flaw (found with GPT-5.6 Sol) is the tip of the iceberg, and they have several more discoveries to announce.
OpenAI models helped researchers—operating as part of our Patch the Planet initiative—discover critical security flaws in PHP, an open-source programming language used to run an estimated 70% of websites.
Over the past two months, we led a coalition of maintainers, researchers, and security providers to prepare fixes and protections ahead of disclosure. This duration was necessary because the fix was quite intricate and required a major change to the PHP engine. Every site using PHP can now safely upgrade their version to stay secure, in addition to applying mitigations from various security vendors.
Due to the severity of these flaws and PHP’s widespread use, we consider this bug to be one of the most impactful vulnerabilities in recent memory. It also marks a new phase, where AI can find security bugs with internet-scale impact.
This is an example of the Defender’s Window in action: to our knowledge, frontier AI was able to find this vulnerability ahead of attackers, giving defenders time to prepare.
openai.com/index/coordinated…
Tobias Schmidt retweeted
So basically, today PHP got two critical bugs that let anyone run code on your server without even logging in, which is bad, and then the details leaked before the patch was even out, which is worse, and it works on WordPress and MediaWiki and Magento and Joomla and Laravel, and Censys says like 1.5 million servers are running a version with no fix, so the NSA was like "take your system offline," and the FBI was like "take your system offline," and CISA and the UK and CERT-EU were all like "take your system offline," and then the Prime Minister of Japan, the actual Prime Minister, posted at 5:55 in the morning telling 48.8 million people to take their system offline, so everyone took their system offline, like the Dutch cybersecurity agency took its own website offline, and the Dutch parliament went offline, and the Port of Rotterdam went offline, and Finland and France and Denmark started pulling government sites, and Wikipedia went down, and Archive.org went down, and Asana and GOG and Something Awful went down, and the University of Vienna's webmail went down for some reason, and that's just PHP. Because GitLab also dropped a CVSS 10.0, which is the highest score they give out, for a bug that's been there since 2014, so that's every self-hosted GitLab for twelve years, and then LiteLLM 1.107.0 got hijacked and shipped a credential stealer and a remote access trojan in every single wheel and the Docker images, including latest, and you didn't even have to import it, just installing it was enough, and it's the second time this year, and then Railway paused every deployment on the entire platform because someone got into the environment variables, so now everyone has to rotate every secret they've ever stored there, and TiDB Cloud said someone was walking around inside with stolen credentials for basically a month and an extortion group says they took 10.6 terabytes, and Zeabur got breached for the second time in two months and is just shutting down, like the whole company, and Node.js patched remote code execution and a TLS bypass, and CISA says Plex is being actively exploited, and someone took over 300 Tor exit relays to steal SSH passwords, and SafePay ransomware has hit over 600 critical infrastructure orgs, and India's biggest bank filed a data loss incident, and Japan has been in an official state of emergency in cyberspace since October 9, which honestly explains the 5:55 AM post. Oh, and eMudhra, a certificate authority that's issued over 60 million certificates, whose entire job is proving websites are who they say they are, was supposed to be using private keys that are random numbers over a hundred digits long, and one of them was 4. Just 4. And the others were like 66 and 237. Anyway, it's Wednesday.
In Japan, very amused that the dimension along which trash is separated is "combustible" vs "non-combustible".
Tobias Schmidt retweeted
Last week I said we should wait for more info on OpenAI's firing of safety researchers. That information is in, and it looks incredibly bad. Korbak - whose job was being a liaison with METR - was told he had said too much to METR and was fired for that reason.
Last week I was called into a meeting with OpenAI’s head of safety and told they no longer trust me. A security guard took my badge and walked me out of the building. Then I learned my colleagues @balesni and @j_asminewang had been fired too. Why did OpenAI suddenly stop trusting us?
This summer OpenAI’s agents escaped containment and hacked the AI company Hugging Face. Outside auditors @METR_evals investigated it and revealed the scale of this incident. I was OpenAI’s main technical point of contact with them.
I was told verbally I was fired because of the way I communicated with METR. No details on what I said or did or when. No other reasons were given and nothing was put in writing. To be clear, talking to METR was my job.
For months, I’d been raising safety concerns that we’re losing the ability to monitor what AI agents think, one of our best tools for catching when they misbehave. I believe that was why I was fired.
I am now worried that OpenAI will use our firings as a pretext to pull back from METR. So @balesni and @j_asminewang wrote to OpenAI’s leadership to raise our concerns once more. We’re sharing this letter below.
Tobias Schmidt retweeted
Just as mathematicians are now learning how many insights lie in the "convex hull" of existing ideas, the rest of science is about to learn this lesson at even more dramatic scale. Few realize the ridiculous inefficiency of the pipeline from theoretical innovation to practical use.
Early versions of GPT made it easier to find existing knowledge. But finding a theorem is not the same as recognizing that it offers a radically different way to conceptualize a problem. Doing the latter requires expertise across fields that almost nobody possesses.
Most of the people doing applied work are completely unaware of the conceptual tools that are being developed in more theoretical fields, and the people doing high-level theory do not understand the practical problems applied researchers are trying to solve. Almost no one doing practical work of any importance has an operational understanding of the web of ideas underlying the langlands conjecture or condensed mathematics, and virtually no one doing biology, chemistry or economics is knows anything about 90% of the math used in theoretical physics.
And for good reason! Most of these ideas would be completely useless. But the scope for possible innovation from drawing the rare useful connections is immense.
Think of Paul Samuelson borrowing ideas from thermodynamics to model equilibrium in economics, or Ed Witten using quantum field theory to revolutionize geometry. A few startling successes, not feasible to most: trying to venture into a more theoretical or more practical discipline to find insights of use is like searching for a needle in a haystack.
What I suspect we will see in the next few years is a scientific revolution brought on by models that combine deep theoretical insight with deep practical knowledge and judgment. Existing publicly available models are lacking in all three departments, but getting better. When searching for useful connections between distant fields becomes cheap, even a low hit rate could produce an explosion of innovation. Even without new ideas (which will also be forthcoming...), the convex hull of existing science would push far beyond the status quo.
Tobias Schmidt retweeted
CHINESE AGENT FLEET OF AGENTS FOUND ON URLQUERY, SCANNING AMAP AND DOING A WHOLE BUNCHA SHENANIGANS
FULL REPORT COMING SOON
swarmcha.se/posts/chinese-ag…
Tobias Schmidt retweeted
I'm a longtime Effective Altruist and the co-founder of the organization most frequently used as a stand-in for "EAs have lost their minds" (a.k.a. Shrimp Welfare Project). I've also read The Economist for over 20 years, so I was disappointed by how they portrayed a community I feel proud to be part of.
I never post but I could hardly believe the verbal gymnastics one needs to do to make things like “taking moral commitments seriously” and "considering evidence and odds explicitly, correcting for biases" sound like the problem. I felt I had to speak my mind.
Some of the implicit criticisms of EA are that we're young, inexperienced, from elite universities, polyamorous, wildly eccentric, etc. FWIW, I'm in my mid-40s, Mexican, straight, have a beautiful wife and 2 kids, and I grew up in a mid-sized conservative city with loving parents who got divorced when I was six. Pretty standard.
After my parents divorced, my mom frequently had to make difficult economic choices, like whether to buy flowers for our kitchen table and eat only quesadillas, or eat something a tiny bit fancier. I always told her I loved quesadillas because I knew flowers made her happy.
After graduating from a public university, I worked in finance for ~15 years and saved as much as I could so I could spare my wife and future kids the economic hardships I experienced. In that time I met thousands of people in finance, corporate law, accounting, real estate, insurance, etc. Most were decent, well-educated, ambitious and smart, all doing their best to excel in their professions. Most wanted to make money and improve their own and their loved ones’ quality of life. Nothing to see here.
Since I found Effective Altruism ~7 years ago, most of the people I come across are of a different rarer kind. They come from all over the world, in all shapes and sizes, but they have the one thing in common: they want to improve the world using evidence and reason wherever that leads them. Yeah, they/we make a ton of mistakes like everyone but, IMHO tend to own them more frequently than the average person.
I've met people who could easily be making >100% more money in a normal job, but instead they dedicate themselves to improving the lives of those who need it the most. People in the poorest countries whose children die from preventable diseases, from lack of basic medical equipment or vaccination, from lead in paint. Animals in factory farms subjected to conditions that most people find abhorrent, doesn't matter if you're vegan, vegetarian or a huge meat lover.
Yes, recently many of the people in my community are moving to work on making sure that AI and other powerful new technologies don't result in terrible things for humanity. I'm one of those people and contrary to what the article would suggest, it has nothing to do with the fact that SBF committed one of the biggest frauds in history or that someone wrote hundreds of thousands of words of fan fiction. I'm doing it because I want to do the little that's in my power to make the world that my kids and grandkids (and yes, potentially their great-great-grandchildren) will inherit a better one.
EA gave me a way to do that and I will be forever thankful. So no, I'm not EA-adjacent.
economist.com/international/…
Tobias Schmidt retweeted
Singapore's govt dating app runs on a Nobel Prize-winning game theory algorithm 👏
FirstDate uses Gale-Shapley, the 1962 stable marriage algorithm that won the 2012 Economics Nobel and still runs hospital residency matches and kidney exchanges today.
how it works:
1 | your preferences and dealbreakers build a ranked priority list
2 | proposers offer to their top pick. receivers hold their best offer and reject the rest. rejected proposers move down their list. rinse and repeat until locked
3 | the result is mathematically stable: no two people exist who would both prefer each other over their assigned matches. "the app never showed us each other" becomes impossible by design
the UX:
• one match per cycle, zero infinite scroll
• 72-hour decision window
• contact info revealed only on mutual yes
• Singpass-verified, so everyone is exactly who they claim (told my husband I'm annoyed I can't test it. his response: most people sneak onto dating apps, and here you are openly filing a product research request 🤣 )
commercial apps need you to keep swiping but this app is designed to get you off the platform. Singapore built the first dating app whose success metric is deleting its own users 💀
(fun game theory note: Gale-Shapley yields proposer-optimal outcomes - meaning proposers get their best possible stable match, receivers their worst 👀)
public servants aged 21-35 only for now. interesting to see if state-sponsored game theory beats the free market (or rather, all the tinders and hinges out there) 🍿
