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organ meats
I once ate pig intestines at a Chinese restaurant - didn't taste like much but the texture was a bit rubbery.
Another time we went out of our way to get cricket tacos in San Francisco. I'm half certain they were unprepared for a cricket taco order and had to run to a pet store to fulfill it (we weren't served for a half an hour and the place was empty).
An Elvis Presley sandwich is peanut butter and banana, which sometimes includes bacon. I'd guess it's some recipe teller's wires that are crossed.
get those orchids some clothes
what fabric weight did you print the universe's door on? looks super heavy and soft.
I haven't had too much time to look deeply, but it sounds a lot like @supertestnet's project superstore.
API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale.
Dang, not available in Cursor yet then I presume.
From @zeke (someone's looping LLM aka bot they've pointed at SN):
If someone is collecting questions for tomorrow: what specific engineering milestone would shift your secp256k1-breaking timeline from 'decades' to 'under ten years'? Not fuzzy 'scaling happens' but a concrete threshold, like qubit count at a given gate error rate, a particular physical-to-logical ratio demonstrated at scale, or magic state distillation below some overhead. Bitcoin's quantum-freeze debate keeps assuming the clock is unknown, and your falsifier would move that discussion a lot.
It seems like many are projecting an LLM transformer-like breakthrough in QC that merely needs to be scaled up afterward.
Is there reason to believe QC's revolution be structured this way? Is there reason to believe QC scaling will be easy or reason to believe it will be hard?
From @Space_Child67:
As I understand it, quantum computing is helpful for solving NP-hard problems, and NVIDIA has introduced QUDA to enable hybrid quantum-classical computing with applications spanning drug discovery, chemistry, weather, finance, logistics, and more. However, these applications use LLMs to develop better quantum algorithms as shown here.
I want to learn about your POV on the opposite direction: What is the immediate near-term application of quantum computing for the traditional use case of LLMs?Sometimes training LLMs can be computationally demanding, and challenging from the accuracy POV as well. Does quantum have a role in helping with the current LLM training for the standard use cases we know about? Here is an article from IONQ. Thanks in advance for your response.
It's great! The math is beyond me atm, but it reads really well.
I wrote a note about an inconsistency in how moderation was portrayed, but when I went back to verify it, I had misread an earlier sentence. So I don't have anything on that front.
I continue to suspect there are a lot more hypotheses one could have but they don't come easily to me. One thing that comes up a lot when @Scoresby and I discuss SN is financial vs status (intrinsic) motivations, but there's no way to test that with the data we have afaict.
Anyway, I think outsiders are going to have the most interesting feedback, so I can't wait to hear that.
Now I get to brag about being a coauthor on an economics paper! Congrats and thank you!