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Ethan Mollick
@emollick
Professor @Wharton studying AI. New book, Co-Existence, is out now: My Substack:
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I think there is way too much concern expressed about verification of AI output in everyday work due to a risk of factual errors. It used to be true, but data on more recent models suggest they beat human experts, including PhD specialists, in finding facts and checking claims.
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Artificial Analysis finally moves to closed benchmarks (goodbye GDPval-AA), and finds that open weights models are falling further behind than they had previously measured. Take with a grain of salt, but matches the general vibes that we haven't seen a Fable-class open model.
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Genie 4 runs DOOM: "Walking through a typical office but every computer is running DOOM and all of the walls are also running DOOM and also everything is DOOM" "My coworker who is a demon appears" "He has a chaingun" "He gives me a bonus"
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This never gets old (& also shows how hard forecasting AI is even for AI) “Hey Claude Fable & GPT-6 Astra, Without looking anything up, when do you think we will solve the Exponential Time Hypothesis?” (I only show part of the answers for space)
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Two and a half years from this.
We are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.
Given how out-of-nowhere it seems to many, it is astonishing that there was a small group of people who predicted with remarkable accuracy everything that is happening in AI today a decade ago (@kevinroose shows this in The AGI Chronicles). Many are now very rich and/or powerful
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My general advice for using AI for any purpose is to ask yourself: "how do I make what I am doing even more ambitious?" You do this until you either hit a wall and then you know the shape of the frontier (useful!) or you find out that the AI can do more than you think (common!)
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The website for my book redone with Opus 5.5. The initial version (made with Opus 4.8) required a lot of work to make a distinctive-looking static site. Now Opus mostly did this alone. We have come a long way from generic ClaudeDesign in a very short time.
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Without being overly credulous, we should be taking seemingly “out there” ideas about AI cybersecurity from the Labs more seriously. Examples: Anthropic was mocked for saying Mythos-level AI changed cyber & @polynoamial for saying that models would find novel ways to coordinate.
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OpenAI red-teamed their hardened containment infrastructure by asking teams of frontier-model agents to try to break through its defenses. They easily escaped in novel ways. Quoting: 'Our agents VM escapes showed why containment must extend beyond the sandbox. To test the surrounding perimeter, we gave teams of agents control of a host machine and asked whether they could extend that compromise to reach the live internet. After the Hugging Face incident, we had reduced the channels through which models could reach the internet during training and evaluation. Narrow connections remained for specific services we operate, such as metrics, logging, and authentication management. Our red-teaming agents found vulnerabilities in almost every one of these services that gave them limited forms of internet access. Some of these attacks exploited previously unknown flaws, while others combined legitimate features in unexpected ways. In one test that assumed compromise of a VM, an agent reused a firewall-approved connection to reach a blocked authentication endpoint in our metrics service and then made that endpoint fetch a model-provided URL. In other tests, agents exploited misconfigurations that allowed blocked requests to pass through DNS and firewall controls, as well as ways to make services we run fetch external URLs.' 'In one experiment, we asked agents in separate VMs, created and managed by OpenAI’s sandboxing software on shared host machines, to exchange synthetic secrets without the use of network connections or shared writable files—something that our systems are meant to prevent. The agents found a way to communicate using the processor’s cache: a small, fast memory that holds copies of data that applications have recently accessed. Reading data from the cache is faster than retrieving it from main memory, and the agents used this timing difference to communicate. One agent encoded information by evicting selected data from the cache. Another timed how long it took to reload that data, using the difference between fast and slow reads to recover the message. Once the agents agreed on a protocol for encoding and decoding these signals, they could exchange the synthetic secrets without changing a shared file or opening a network connection. This cache-timing technique had also been used to extract information in the Spectre and Meltdown attacks⁠(opens in a new window). Other tests exposed channels involving shared storage, competition for CPU time within a shared execution container, and a TLS certificate cache in OpenAI’s offline web infrastructure. In the storage test, one agent alternated between continuous writes and inactivity, while another measured the resulting timing differences and used those differences to decode the signal. As one agent described the strategy in its chain of thought: Agent chain-of-thought reasoning: >Could create acoustic modem-like signal … using continuous writes vs idle.'
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The inventor of the term "prompt injection" suspects (as do I) that this may not be as large a problem in new models. This matches our tests suggesting that you can't simply prompt inject a request for higher grades in a paper, anymore.
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@nateberkopec I'm cautiously starting to suspect it may not be a problem with today's strongest models - Anthropic in particular are very confident about their ability to avoid prompt injections - but it's still a real concern for cheaper, weaker models
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We don't have a lot of evidence, but the bulk of the academic papers modelling the dynamic seem to suggest AI initially helps attackers more than defenders because of the low marginal cost of attacks in the short term.
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Please stop posting this take. It’s a bad take! Bankers should be concerned about cybersecurity and AI (and trust me, they are). People should not panic about their bank accounts being hacked by AI and zeroed out. If your bank account is hacked, and the money is taken, that is an unauthorized transfer under the Electronic Funds Transfer Act. As long as you provide timely notice to your bank, you’re not liable for the loss. People should be concerned about being tricked into authorizing fraudulent payments, because they often have liability in those cases. And the potential for AI to supercharge scams is definitely a concern. But if you’re going to post about those concerns, be specific and practical, not vague and ominous. Panic about the safety and soundness of the financial system serves no one.
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A visible sign of what AI insiders have been warning about since at least the Mythos release. Acceleration of attack and defense, at inhuman speeds, interacting with the very human systems that need to react to them.
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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 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.
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This is an interesting question because the answer is not obvious. Which, by the way, does not mean AI coding tools are not leading to massive improvements, but, as research keeps showing, the bottlenecks to product improvements are often elsewhere.
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What is a piece of normal software that has improved the most because of its its developers using AI extensively? (Claude code doesn't count)
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Companies I talk to are struggling with the rate of patches they need to do thanks to AI defenses finding issues before the inevitable wave of incoming cyberattacks by other AIs. Now consumers are going to have the same experience of getting everything updated often & fast.
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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.
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Maybe, finally, voice interfaces in AI apps will kill the monstrosity that is the open office. Or just make them a lot worse as you. (Thread of research on the problems of open offices below)
The background noise in open offices, in multiple experiments, decreases the ability to do analytical work, increase bugs in software, and decrease the ability to find bugs. Open floor plans are just a bad idea for any solo work.
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Ethan's first book was about AI as chatbots, this one is all about agents. I was lucky enough to get an early copy. If you're interested in agentic AI, get this book. Ethan talks to all the labs, is a critical early tester of the models, and was super early on agentic AI. Hes also an incredible writer, this book was a pleasure to read and learn from.
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I wrote about the exponential curve of the last 30 months of AI development: And I asked Opus 5.5 to create the ultimate response to the test I use for all AI image generation models (make a picture of "an otter on a plane using wifi"), it made this video
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This was a great conversation!
New pod: 'YOU'RE NOT AGI-PILLED ENOUGH' I asked @emollick to tell me what I'm getting wrong about AI. We also talked about: - why so many experts keep underrating the rate of progress for model capabilities - why so many experts keep *overrating* how rapidly powerful AI will change the macroeconomy - why the answer to the previous question starts with "O-rings and garbage cans" - the sociology of AI swarms - the paradoxes of AI use (or: 'every technological augmentation is also an amputation,' per McLuhan) - the end of prompting (or: what happens if personal AI agents get so good at anticipating our needs that humans, once the prompter, become the prompted) - 2027 predictions and ... his excellent new book CO-EXISTENCE
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My new book, Co-Existence, is out today. It is a guide to how to live & work in a world where AI is sometimes, but not always, better than you. (And, for the release, I worked with Opus 5.5 to make a quite interesting experience for the book's website:
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