There are certainly other, less pretty, ways to looks at the data, but producing something that can be intuitively understood, such as a 2D image, can also be helpful scientifically.
802 karma · joined April 14, 2016
There are certainly other, less pretty, ways to looks at the data, but producing something that can be intuitively understood, such as a 2D image, can also be helpful scientifically.
> In this approach, we apply principal components analysis (PCA) to a large library of high-fidelity, high- resolution general relativistic magnetohydrodynamic (GRMHD) simulations and obtain an orthogonal basis of image components. PRIMO then uses a Markov Chain Monte Carlo (MCMC) approach to sample the space of linear combinations of the Fourier transforms of a number of PCA components while minimizing a loss function that compares the resulting interferometric maps to the EHT data.
As an exercise in matching up MHD models with real data this can be an interesting study. Too bad the reporting is so off point, as usual. But I guess adding "AI" to your titles gets you more clicks these days.
What happens if interoperability is enforced and messages have to be end-to-end encrypted? Wouldn't that mean that any side-loaded Android app would have to be able to get hold of my friend's private iMessage key?
On iOS I guess you could still keep the key private through Apple's SDK, but what about other platforms?
That confused me a bit. Otherwise this looks interesting, thanks for sharing.
The assumption I make to make this work is that dependencies are more likely to be drowned out by internal variation in a larger sample. So you get to pick which assumption you like better.
Cooking for many people, sharing tools, common areas, etc, saves a lot of money and resources. We are thus able to support a wide range of income levels. With the caveat that we're in a fairly equal country (Northern Europe), the community attracts a wide range of backgrounds, from unskilled workers to teachers and doctors. Everyone gets chores and responsibilities assigned based on personal priorities, skills and the needs at the time.
We have a "rule-book" that defines a democratic voting system for making decisions. We hold meetings every other week. I would lie if I said it was always pleasant or easy, but it does work surprisingly well. I think it helps that the place is around 50 years old, so we've had the chance to learn from mistakes and update the "rule-book" along the way.
I don't think it's for everyone, and I'm not sure how well this scales beyond 50-100 people, but I do think that you can be happier, healthier and wealthier living in suitable small-scale communities, sharing everyday tasks and tools. Instead of everyone owning their own everything.
It's incredible how much stuff is produced just to be thrown away. But I guess it keeps the wheels turning? I often wonder wether this is the best system there is. Something tells me it's not.
I'm sure we'll figure out the regulation sooner or later, but for now it looks like things will get worse before they get better.
I would say it's more like a club where everyone knows each other. If you are authoring a paper you often know who the potential referees are (those that published most in the field), and you politely ask the editor to exclude referees that are in open conflict with you. Editors usually abide and you get a reasonable review of your paper.
I agree about most other issues raised about peer review in general and related incentives, but the issues raised here are not some that I recognize.
The fact that we observe what looks like emergent structures such as "understanding", "knowledge" or "reasoning" is fantastic, but it is not in any way incompatible with a P(text|internet) model simply "mimicking" humans.
I agree that exploring the inner workings of these emergent features is interesting in it's own right, but all that glitters is not gold.
I can't even believe I'm even spelling this out. What is the point of associating anything even remotely human with a chatbot like ChatGPT? I really don't get it. What benefit do we get from this? If anything is confuses us in ways that makes it more difficult to understand and argue about AI specifically, and technology generally.
ChatGPT is being grossly misinterpreted, and it's a shame, really, because it's such a cool piece of software.
I feel like something is missing in this equation. :)
I guess that could probably be said about most research fields though. We've just not reached novelty-saturation in machine learning sciences yet. Let's enjoy the attention while it lasts!
Another kind of knowledge exploration perhaps? If they find a way for it to not produce factually incorrect output. Isn't that a big if?
Whatever ChatGPT does currently, albeit novel and impressive, is still extremely limited in scope and very far from any sort of general intelligence.
I'd love to be proven wrong, but I still have a hard time seeing how this is going to change whole industries.
Original title (dec 1.): "Physicists Create a Wormhole Using a Quantum Computer" [1]
Current title (dec 2.): "Physicists Create a Holographic Wormhole Using a Quantum Computer" [2]
[1]: https://web.archive.org/web/20221201021130/https://www.quant...
[2]: https://web.archive.org/web/20221202022713/https://www.quant...
> “I sit ten feet from him, and I walked over, thinking, Oh, shit, that was really good,” remembers Arora. “And it turns out that that fucker was playing League of Legends through the entire meeting.”
> “We were incredibly impressed,” Bailhe says. “It was one of those your-hair-is-blown-back type of meetings.”
https://web.archive.org/web/20221027180943/https://www.sequo...
If we elevate "correlations" to mean "understanding", we're quickly going to run out of words.
If you prefer driving your car, that's fine, but don't pretend that biking is somehow reserved for young fit people, that's simply not true.
Go to any northern European city and see for yourself.
I actually didn't know this, but that makes a lot more sense.