So, in general, I think it's not good in icons to show pictures of a particular product design because like the 3 and 1/2 in floppy for save. Um even though some there's still a few of those kicking around, but obviously it it didn't age well. Better to use a metaphor.
I think the case of TLA+ and most, not all, but most formal methods, they shine the most in highly computational domains, where most of the problems are highly technical and not like business embedded.
I genuinely believe that if you took an open weights model from 2025 and built a pentest harness for it, it could do this kind of sandbox escape and scan/hack in most networks. This is only surprising because you assume OpenAI has sounder sandboxes.
In the face of weakened renewable roll-out in Australia, the most likely outcome is simply that coal and gas just generate more, and for many more years past their shut down date.
Many AI researchers are overly focused on risks from model misalignment, and will be in for a rough surprise when havoc arises from other layers of the stack.
The best book I read last year was Mark Lawrence's The Book That Wouldn't Burn, which much to my surprise did not make a single award list for its publication year of 2023. It was a tour de force of world-building that surprised me multiple times.
And the German war machine could only win in so-called speed wars, like lightning war. Only if they would do it very fast and surprise, because they were always weaker, basically.
That might surprise people. The bigger it is, the less noticeable it is that you’ve crossed the event horizon. One way to think about it is curvature is less noticeable the bigger it is.
In fact, there’s a handful of dates that tell us that the fourth creation does continue farther on, that that baktun place should have 20 baktuns in it, like their counting system would dictate, not 13.
is this idea that we form these internal models at particular points of high prediction error or points of, I believe also points of uncertainty, points of surprise or motivationally significant periods. And those points are when it’s maximally optimal to encode an episodic memory.
So part of the reason that we deploy the way we do, we call it iterative deployment, rather than go build in secret until we got all the way to GPT-5, we decided to talk about GPT-1, 2, 3, and 4. And part of the reason there is I think AI and surprise don’t go together. And also the world, people, institutions, whatever you want to call it, need time to adapt and think about these things.
To my surprise, I really enjoyed The Republic. It is both well-written and weird, which puts it above many other famous philosophical books that are too obscure to be easily read.
In fact, I would say it’s more surprising that the matter that we know about is constitutes as big a fraction of the universe as it does. We’re limited, we’re human. The fact that we see 5% of the energy density of the universe, about one sixth of the energy density in matter, that’s remarkable.
It is fair to say that, while economists expected the short end of the yield curve to reflect the higher rates needed to win the fight against inflation, the sharply steeper long end of the yield curve in the last few months has come as a surprise. I shall freely admit that I did not predict it.
Recently though, I went to The Drama Bookshop, which was a delightful surprise. It is the closest I have come to the experience of a Manhattan bookshop as a third place in the kind of Prairie Lights mode.
So, it wouldn’t surprise me any longer if we found life on Mars and it had a genetic code that was not very different to the genetic code that we have here without it just being transferred across, there’s some inevitability about the whole of the beginnings of life, in my view.
This one might come as a surprise to some, but the reality is that at Fitbit’s more reasonable pricing as of late, the Fitbit Sense is a pretty good option. And it’s a super well-rounded option
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