nighthawk454

8 ms·

61.
by nighthawk454 1y ago
Frankly, you’re ignoring the definition at this point. A “good hash algo” only generates noise in the cryptographic hash sense. There are in fact other hashes. The fact that “semantic vectors” preserve a useful similarity is no different ma
62.
by nighthawk454 1y ago
No, mapping to a _fixed length code_, that’s it. Note that the output domain need not be smaller than the input domain either. If your model takes a sequence of 1 or 10,000 or N tokens and returns a vector of fixed length, say 1500 dimensio
63.
by nighthawk454 1y ago
I guess it depends on how loosely we take the definition. Wikipedia has it as just a function that maps variable length sequences to fixed length sequences. So by that definition most embedding networks fit. Hashes are often assumed to be 1
64.
by nighthawk454 1y ago
A hash function in general is only a function that maps input to a fixed-length output. So embeddings are hash functions. You’re probably thinking of cryptographic hashes, where avoiding collisions is important. But it’s not intrinsic. For
65.
by nighthawk454 1y ago
I certainly agree, I think the financial mechanisms are not very obvious. Presumably somewhat by design. And yet it also seems to be one of the main tricks in modern financial engineering - it just keeps turning up. See also: corporate buyb
66.
by nighthawk454 1y ago
This is blatantly just increasing debt load. What does a business do if they need forever growth, but can’t increase their prices further without losing net revenue? Raise prices anyway and push people to finance it. This is broadly not goo
67.
by nighthawk454 1y ago
By the looks of things, uv is telling you it’s creating a venv with Python 3.10.9 still. Since you didn’t specify you wanted another version, it probably defaulted to the first available system version. What you want is `uv venv —python 3.1
68.
by nighthawk454 1y ago
Interesting… from the intro the argument is that the Consumer Product Safety Commission ‘requested’ Amazon to issue recalls for products of third-party sellers due to safety hazards. Amazon complied “voluntarily”. Then CPSC wanted to treat
69.
by nighthawk454 1y ago
Gotcha, thanks for the reply. Makes sense to target burstables first - that seems to be the most common feature set. That’s interesting that it’s not readily available in the kernel. I once spoke to some AWS folks dealing with Batch/EC
70.
by nighthawk454 1y ago
Great article, thanks! I’ve been curious if there’s any scheduling optimizations for workloads that are extremely burst-y. Such as super low traffic websites or cron job type work - where you may want your database ‘provisioned’ all the tim
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by nighthawk454 1y ago
Got it - thanks! I might suggest adding a comparison section to the website (whenever appropriate). Appreciate the response, I look forward to checking it out.
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by nighthawk454 1y ago
It’s an option for payment. Detailed on the same link: > Storj created the STORJ utility token as a medium of exchange on its decentralized cloud storage network. The STORJ utility token facilitates payments from people around the world
73.
by nighthawk454 1y ago
Does anyone know how this compares to ErsatzTV?
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by nighthawk454 2y ago
Circuit breakers are now more common. The US has them at whole-market level and individual stock level. Somewhat like an API rate limit, there are tiered penalties - the bigger the intraday drop the longer the time-out period. In the worst
75.
by nighthawk454 2y ago
Hey, nice project. It was genuinely refreshing to just mess with some sliders on something interactive and no-bullshit. Cheers!
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by nighthawk454 2y ago
Discussed here: https://news.ycombinator.com/item?id=43489136
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by nighthawk454 2y ago
This was a great YouTube video on the subject: https://www.youtube.com/watch?v=a-767WnbaCQ A submission to 3blue1brown's SoME (summer of math explanation) competition
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by nighthawk454 2y ago
Some things don’t require scratch build, some do, some are in between. But there’s no prompt for taste.
79.
by nighthawk454 2y ago
Only if you’re describing orientation as two orthogonal rotations. I’m saying think of it like a ‘pointing’ vector that defines the axis of rotation. And such a vector does require 3 components in 3d space
80.
by nighthawk454 2y ago
If you click through to the interactive example, you can try it! You'll see that the if the above equations are `q`, then full formula to rotate a vector `v` is `v' = q * v * q^-1`
81.
by nighthawk454 2y ago
The easiest way for me to conceptualize it is to think of it as orientation + rotation. 3 dims for the orientation vector to get the object facing/pointing the right way, then a further 1 dim/var for rotation about that axis. For
82.
by nighthawk454 2y ago
Testing this out locally, repro'd pretty similar numbers on macOS ARM and docker. Unfortunately the CPU-only build isn't really any smaller either, thought it was
83.
by nighthawk454 2y ago
One ponders the connections with the Recall feature
84.
by nighthawk454 2y ago
Seems to be hugged, so here's a cached view https://archive.is/w8yFG https://web.archive.org/web/20250202094451/https://adriacabe... (images are cached better here)
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by nighthawk454 2y ago
Nice! Yeah that workflow feels pretty relatable. My other rule of thumb is if it's an architecture paper (system or neural net) without a diagram, I immediately bail haha
86.
by nighthawk454 2y ago
A nice trick for most papers is to skip the middle (at first). Just don’t read most of the lines of math. Focus on the inputs and outputs. If the premise and conclusion don’t make sense on fundamentals the math isn’t likely to fix it. Most
87.
by nighthawk454 2y ago
> eBPF is a technology that can run programs in a privileged context such as the operating system kernel. It is the successor to the Berkeley Packet Filter (BPF, with the "e" originally meaning "extended") filtering m
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by nighthawk454 2y ago
To run without setup: uv run --python 3.13 --no-project --with bagels bagels
89.
by nighthawk454 2y ago
Sorry, you’re right, it pools again to a single comparison scalar in the end
90.
by nighthawk454 2y ago
Usually, we destructively compress (mean-pooling) both the query and the document, and then compare the two compressed forms. With ColBERT, we compare first - at the full token level - for more detailed comparison. Then reduce the full set

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