The James Webb Space Telescope has started capturing images of galaxies so far away that they are causally disconnected from the Earth — nothing done here or there could ever interact. 🧵 1/
The latest of these, JADES-GS-z14-0, was discovered at the end of May this year. It is located 34 billion light years away — almost three quarters of the way to the edge of the observable universe.
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The light we are capturing was released by the galaxy about 13.5 billion years ago — just 0.3 billion years after the Big Bang. So we are seeing a snapshot of how it looked in the early days of the universe.
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Because the space between us is stretching, the current distance to the galaxy is 15 times larger than it was when the light began its journey towards us. That's how it can be 34 billion light years away when the light has only travelled for 13.5 billion years.
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The expansion of space makes it hard for anything, even light, to cross the vast gulfs between distant galaxies, as the distance you need to cross keeps growing. Because the expansion is accelerating, eventually the remaining distance grows too fast to ever cross.
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If we shine a torch up at the night sky, some of the photons released will eventually leave our galaxy and travel for a vast distance. They will eventually be able to reach any galaxy that is currently within 16.5 billion light years of us.
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I call this region that we can affect 'The Affectable Universe', and in many ways it is the twin to the Observable Universe. Each year, more galaxies slip beyond our reach, as a photon released next year will no longer be ever able to reach them.
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JADES-GS-z14-0 is well beyond the edge of the affectable universe. Nothing we send out can ever reach it or affect it.
We've seen galaxies beyond this distance for a long time. Many of the smaller galaxies in the Hubble Deep Field below are forever beyond out reach. 8/
But events here and contemporaneous events in those small galaxies *can* interact — if being in both galaxies set off towards each other at near the speed of light, they could eventually meet in the middle.
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Or if we both sent signals, an alien civilisation in the middle could receive both and combine them. In other words, it is still possible to causally interact with each other.
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This is also what we saw with the star 'Earendel' — the first individual star to be identified that was beyond our affectable universe.
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But JADES-GS-z14-0 is slightly more than *twice* as far as the edge of the affectable universe. So the affectable universe around us and the affectable universe around them don't overlap at all. So there is no longer a way to interact at all.
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Of course, we can still see these baby photos of their galaxy, but no matter how long we wait, we'll never see them grow up to our current age. If we waited, we'd see the evolution of their galaxy slow down asymptotically and never get to be 13.8 billion years old.
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Of course, they'd keep getting older, but the 'postcards' (photons) they send us get delayed longer and longer by the expanding distance they have to cover, so come in less and less frequently, and recent postcards will never arrive.
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You can find out much more about this in my paper on The Edges of Our Universe, described here:
So far the JWST has identified 3 such galaxies that are twice as far as the edge of the affectable universe (i.e. more than 33.0 billion light years away). You can find them here: en.wikipedia.org/wiki/List_of_t…
I've drawn up a scale diagram to show what is happening. The blue lines are our past and future light cones, the purple lines are their's.
For the first 300 million years, they were in our past light cone, which is why we can see their early stages. Similarly, they (now) could see our spot in the universe at that time, but it was empty, and they can never see the Earth form.
And here is a version with a dashed line showing the last point in time at their location that we will ever see. We will only be able to see the first 5 billion years or so, and never be able to see what they are doing now.
If you were interested in this thread and want to hear more big picture thinking about humanity, its role in the cosmos, and why our own time is crucial in that story, you may be interested in my book, The Precipice. theprecipice.com
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New paper:
Inference Scaling Reshapes AI Governance
The shift from scaling up the pre-training compute of AI systems to scaling up their inference compute may have profound effects on AI governance.
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The nature of these effects depends crucially on whether this new inference compute will be used during external deployment or as part of a more complex training programme within the lab.
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Rapid scaling of inference-at-deployment would:
• lower the importance of open-weight models (and of securing the weights of closed models)
• reduce the impact of the first human-level models
• change the business model for frontier AI
…
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Inference Scaling and the Log-x Chart:
2024 saw a switch in focus from scaling up the compute used to train frontier AI models to scaling up the compute used to run them.
How well is this inference scaling going? 1/
You could think of it as a change in strategy from improving the quality of your employees’ work via giving them more years of training in which acquire skills, concepts and intuitions to improving their quality by giving them more time to complete each task.
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Or, using an analogy to human cognition, you could see more training as improving the model’s intuitive ‘System 1’ thinking and more inference as improving its methodical ‘System 2’ thinking.
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I've just published a paper positing a new kind of fundamental physical law bounding the rate at which any physical quantity can grow or converge.
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The idea is quite simple, drawing on a classic argument from computer science.
Almost all modern computers and programming languages can compute the same mathematical functions. These are called the Turing-computable functions.
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It is widely believed that these represent the limit of what is computable in our universe. I’m not sure if that is true, but it is the orthodox view — to think otherwise is generally considered eccentric.
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DISSECTING A BLACK HOLE
I’ve designed a new kind of diagram for understanding black holes — and made a beautiful poster to show it off.
The key idea is to show the many different layers of a black hole, each with their own unique properties.
Let's dive in!
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I call this a ‘record diagram’.
By slicing through all of these spheres, we see the black hole laid out like a record on a turntable, displaying all its different tracks — both the classic hits that may have blurred together in lower fidelity diagrams and some deep cuts.
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Distances near black holes are best measured in units of M — a key distance based on the black hole’s mass. For a black hole the mass of our sun, M = 1.5 km. For a mass of a million suns, M = 1.5 million km.
Most interesting things happen when you pass integer multiples of M. 3/
I’ve just released a new paper. The idea arose from a conversation with @DAcemogluMIT about the limitations of today’s generative AI systems.
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They are good at interpolating between different examples in their training data and perhaps even extrapolating further in a direction they’ve seen.
But they appear to be unable to head off in novel directions — to break free of the subspace where all their training data lies.
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The ability to find new locations in the space of paintings, poetry, music, or ideas that transcend what has come before is a key part of creativity.
Can we understand what is lacking in AI creativity today as an inability to move beyond the subspace of the training data?
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Since the launch of ChatGPT, there has been a lot of loose talk about AI having passed the Turing Test (or even 'blown past' it). But this was premature and probably incorrect.
A new paper tests whether GPT-4 passes the Turing test, with mixed results. Let's explore: 1/n
First, let's be clear on a few things about the Turing Test. 1) Pretty much everyone agrees it doesn't constitute a definition or a necessary or sufficient condition for intelligence.
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2) But that doesn't mean it isn't an interesting benchmark. e.g. it was very interesting to know when AI beat humans at Chess and at Go, even though no-one thinks they are definitive of intelligence.
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