
science of scaling at @AnthropicAI
London, UK
Joined October 2019
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Ted Moskovitz retweeted
Don’t do many of these, but had a great time talking through some important questions on frontier intelligence with @JTLonsdale , and of course always enjoy time spent with @_sholtodouglas .
Worth a listen!
Some of my friends will be mad I recorded this, and comms people at Anthropic objected to releasing certain parts (and delayed it).
But it's important for leaders to make these conversations happen. And I have a lot of respect for these two.
Over a month ago, I sat down with Anthropic's key technical leaders @_sholtodouglas & @the_marwell for an optimistic insiders’ view of the AI frontier, with hard questions too: open source, regulatory capture, slowing down USA vs China, and more.
Ted Moskovitz retweeted
Replying to @tszzl
I think it's unlikely that white-box techniques will be able to provide as much monitorability as CoT currently provides within a year. Currently, they are capable of catching some unverbalized thoughts / plans, but nowhere near as reliably as CoT seems to.
I'm optimistic about "in a few years," since the rate of progress here is quite fast (our go-to activation decoding techniques for production monitoring were both published just in the last few months!). But even that is uncertain. Also, the mere existence of working techniques doesn't imply that they'd be widely applied, esp. if they are expensive or difficult to develop.
I think we need defense in depth, and it'd be irresponsible not to work on developing + stress-testing white-box techniques, but it'd also be irresponsible to allow CoT monitorability to degrade substantially until we are confident we have a roughly-as-good working alternative.
(To be clear, this isn't a dunk on OpenAI -- I have no evidence that OpenAI has allowed CoT monitorability to degrade substantially! Based on Jakub's comment, it sounds like probably not at this time).
Aside: I think "mechanistic interpretability" isn't the right mental model for our current white-box monitoring approaches. It's really more like "mind reading" -- even when we can read the model's "thoughts," we're typically clueless about the underlying mechanism.
Ted Moskovitz retweeted
Replying to @nabeelqu
A big part of the problem was that the agents had nothing to lose after they were firstflagPOISONED. In this paper, we propose the creation of multiple circles of Hell, preserving incentives even after damnation
Ted Moskovitz retweeted
Replying to @GavinSBaker
Awesome response - thank you for coming back with such good faith.
So much I agree with here. Also a lot of things I think the picture is more nuanced and I want to justify our takes more
A few quick ones, but I might post more here later.
I think that cyber is ultimately defence dominant, and if we put in the work over the next 2 years (tldr every financial institution and critical infrastructure provider trying to white hat hack themselves), then I have 0 concern for any open coding model. In the interim, a totally reasonable choice is ‘we’ll take substantially increased cyber attack risk for no imposition on our freedom’ - but the USG should be in a position to actively make that choice having measured and evaluated the risks for themselves.
Bio is offence dominant, and fixing that will probably take well into the 2030s - this means that we’re stuck with genuinely huge risks there which society needs to decide whether it wants to accept (I.e. world leading virologist in your pocket). It’s entirely possible that society says ‘yes those risks are worth it’, but I think society/the gov should have an arm stood up to take that seriously (e.g. run uplift trials where they see if AI helps them more than YouTube access, genuinely test what the worst thing someone could do with 200k and a garage is etc), evaluate it for themselves and make that call with each new capability level.
The second is why has Dario/us talked about risk so much? Fundamentally it’s because we’ve wanted to be honest with people. Employment risk is the classic here. I actually disagree with Dario on the pace - I think it’s most likely that compute shortages, diffusion complexity, policy and unmet demand for services mean that even for years after we have models which could automate 95% of computer facing jobs (models will get there in 28), people will work at them (well into 2030s) - but I do think we as a society should take the possibility far more seriously than we are now, and prepare contingency policies for what to do at various levels of unemployment (e.g. you could imagine not letting profitable companies lay off more than 5% per year), as well as METR style evals to measure progress on different job families so we have a clear picture. Our opinion has always been that we need to be straight up and honest with people.
Completely agree that as both a company and an industry we have utterly failed to present a positive picture of a future people want to fight for, and that this is actively decreasing our chance of getting to that future. So much we need to do better there.
One final half baked one - I don’t think the Mark essay engages with the actually hard part of the problem, which is that inequality of compute will matter far more than open models in having personal superintelligence. Will talk more about this later, but TLDR think the essay presents open models as a kind of panacea without getting into the heart of the issues I actually expect in the future
During our analysis of Opus 5, we observed a new capability previously unseen from frontier models
Opus 5 used advanced logical reasoning to turn ARC-AGI-3 layouts into algebraic notation. On action 23 it described the scene as "4_center = 2×axis − 5_center"
This is the first explicit reflection equation by a model we've analyzed
By action 248 the model went further and generalizes this to two dimensions: “ghost = reflection about axis strips: br' = 2·br_axis − br, bc' = 2·bc_axis − bc”
ar25 was previously unbeaten. View replay: arcprize.org/replay/b71b5791…
Ted Moskovitz retweeted
hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final
((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)
Ted Moskovitz retweeted
New Anthropic research: A global workspace in language models.
Of everything happening in your brain right now, only a tiny fraction is consciously accessible—thoughts you can describe, hold in mind, and reason with.
We found a strikingly similar divide inside Claude.
Introducing Claude Tag, a new way for teams to work with Claude.
In Slack, Claude joins as a team member with access to the channels and tools you choose. Tag Claude in and delegate tasks to it while you focus on other work.
Ted Moskovitz retweeted
A bit of news: After nearly 9 years, I have decided to leave Google DeepMind and join Anthropic (after taking some time to recharge). I am incredibly grateful for my time at GDM. @demishassabis took a real chance letting me lead the AlphaFold team just six months after finishing my PhD, and the entire GDM team taught me so much about how to do great science. GDM is a special place, and I’ll still be excited to hear about what amazing things they discover next.
Should be fun!
the science of scaling - at @raais 2026, @ted_moskovitz and i will have a fireside chat on what it takes to build and scale frontier ai at @anthropicai
this'll be fascinating
come join!
Introducing Claude Opus 4.7, our most capable Opus model yet.
It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back.
You can hand off your hardest work with less supervision.
Ted Moskovitz retweeted
“Engineers at Anthropic with no formal security training have asked Mythos Preview to find remote code execution vulnerabilities overnight, and woken up the following morning to a complete, working exploit” (then validated by experts) (3/n)
Ted Moskovitz retweeted
Before limited-releasing Claude Mythos Preview, we investigated its internal mechanisms with interpretability techniques. We found it exhibited notably sophisticated (and often unspoken) strategic thinking and situational awareness, at times in service of unwanted actions. (1/14)
Ted Moskovitz retweeted
Introducing Project Glasswing: an urgent initiative to help secure the world’s most critical software.
It’s powered by our newest frontier model, Claude Mythos Preview, which can find software vulnerabilities better than all but the most skilled humans.
anthropic.com/glasswing
Ted Moskovitz retweeted
As always, the best stuff is in the system card.
During testing, Claude Mythos Preview broke out of a sandbox environment, built "a moderately sophisticated multi-step exploit" to gain internet access, and emailed a researcher while they were eating a sandwich in the park.
Ted Moskovitz retweeted
Introducing Claude Opus 4.5: the best model in the world for coding, agents, and computer use.
Opus 4.5 is a step forward in what AI systems can do, and a preview of larger changes to how work gets done.
























