vlowther
vlowther on Hacker News
Yeah, most of what I did was to add fused TQ support to leave more memory free for other nefarious purposes.
It is pretty nifty. I spend some time over last weekend implementing fused TQ to allow for 1m context lengths on a 128 gb MacBook M5 Max when using Qwen 3.8 flash next (
https://github.com/antirez/ds4/pull/1115 if you are interested). If I get bored I might port over the Metal kernels from oMLX -- the speed increase they have for the v0.7.0 release is amazeballs.
It also isn't a unique thing. See (for example) the entire history of, well, pretty much any country. There is a reason Utopia literally means "no place".
* Genocide of the natives? Literally all countries in the Americas, for starters.
* Slavery of captives from Africa? Pretty much everyone with colonies in and around the Caribbean was guilty of that too.
* Multiple unnecessary wars that have killed millions of people? That encompasses more or less all of European history.
By all means, criticize Palantir. But don't pretend US history has anything in particular that would set up the prerequisites for it to exist.
Pretty sure it is sexually transmissible, so I would not be too sure about that.
Same. Opencode + oMLX (0.3.4) + unsloth-Qwen3-Coder-Next-mlx-8bit on my M5 Max w 128GB is the sweet spot for me locally. The prompt decode caching keeps things coherent and fast even when contexts get north of 100k tokens.
The 8 bit MLX unsloth quant of qwen3-coder-next seems to be a local best on an MBB M5 Max with 128GB memory. With oMLX doing prompt caching I can run two in parallel doing different tasks pretty reasonably. I found that lower quants tend to lose the plot after about 170k tokens in context.
No really, no. the last thing Github needs is yet another vibe coded fork of a mostly vibe coded app in the first place.
If I ever get around to vibe rewriting-it-in-go I might share that.
MBP M5 Max. 128GB ram. oMLX. unsloth-Qwen3-Coder-Next-mlx-8bit. opencode with the telemetry stripped out. This seems to be the sweet spot for now for my local dev. Helps me to not accidentally blow through $100 in Claude tokens in a day when exploring different performance tradeoffs the backend of my $DAYJOB codebase.
In my case, "background writes" literally means "do the io.WriteAt for this fixed-size buffer in another goroutine so that the one servicing the blob write can get on with encryption / CRC calculation / stuffing the resulting byte stream into fixed-size buffers". Handling it that way lets me keep the IO to the kernel as saturated as possible without the added schedule + mutex overhead sending stuff thru a channel incurs, while still keeping a hard upper bound on IO in flight (max semaphore weight) and write buffer allocations (sync.Pool). My fixed-size buffers are 32k, and it is a net win even there.
My usecase was building an append-only blob store with mandatory encryption, but using a semaphore + direct goroutine calls to limit background write concurrency instead of a channel + dedicated writer goroutines was a net win across a wide variety of write sizes and max concurrent inflight writes. It is interesting that frankenphp + caddy came up with almost the same conclusion despite vastly different work being done.
If the performance charts are to be believed, this has uniformly worse performance in fetching and iterating over items than a boring old b-tree, which makes it a total nonstarter for most workloads I care about.
It is also sort of ironic that one of the key performance callouts is a lack of pointer chasing, but the Go implementation is a slice that contains other slices without making sure they are using the same backing array, which is just pointer chasing under the hood. I have not examined the code closely, but it is also probably what let them get rid of the black array as a performance optimization.
That is the most cursed description I have seen on how defer works. Ever.
Microsoft Active Career Copilot 365 ONE, thankyouverymuch.
It took quite a bit of scrolling until I found my old faves of dexed and zynaddsubfx, and I didn't see Helm (
https://tytel.org/helm/) at all.
None of the big browsers can be trusted at this point. Firefox is at best the least worst out of the big cross platform browsers.
DOS, early Windows, and early MacOS worked more or less exactly that way. Somehow, we all survived.
No, you cannot. Our abstract language abilities (especially the written word part) are a very thin layer on top of hundreds of millions of years of evolution in an information dense environment.
Only if you are doing in-place updates. If append-only datastores are your jam, writes via mmap are Just Fine:
$ go test -v
=== RUN TestChunkOps
chunk_test.go:26: Checking basic persistence and Store expansion.
chunk_test.go:74: Checking close and reopen read-only
chunk_test.go:106: Checking that readonly blocks write ops
chunk_test.go:116: Checking Clear
chunk_test.go:175: Checking interrupted write
--- PASS: TestChunkOps (0.06s)
=== RUN TestEncWriteSpeed
chunk_test.go:246: Wrote 1443 MB/s
chunk_test.go:264: Read 5525.418751 MB/s
--- PASS: TestEncWriteSpeed (1.42s)
=== RUN TestPlaintextWriteSpeed
chunk_test.go:301: Wrote 1693 MB/s
chunk_test.go:319: Read 10528.744206 MB/s
--- PASS: TestPlaintextWriteSpeed (1.36s)
PASS
It isn't even really that -- most CLI tools are single-threaded and have a short lifespan, so your memory allocation strategy can be as simple as allocating what you need as you go along and then letting program termination clean it up.
"I came up with a step-by-step plan to achieve World Peace, and now I am on a government watchlist!"
That sort of thing is why I wrote my own DHCPv4 server that is directly integrated with the core product at $DAYJOB. 10 years ago. Having the DHCP server determine how to handle PXE requests straight from the machine database made my life so much simpler.
Code by vibes and copy/paste instead of R'ing TFM for your language and libraries and understanding your problem domain, introduce security vulnerabilities. Film at 11.
Seriously, the only one that is arguably bad design is the case insensitive JSON keys thing. Everything else is just a reasonable engineering tradeoff given the intersection of the marshalling format design constraints and Go's design. Parsing untrusted data always has the capacity to introduce security vulnerabilities.
Just need to make sure all your computation is done in a volume with infinite surface area and zero volume. Encoding problem solved. Now then, how hyperbolic can we make the geometry of spacetime before things get too weird?
From I Palindrome I, few albums later on Apollo 18:
Son, I am able, she said, though you scare me. Watch, said I. Beloved, I said, watch me scare you though. Said she, able am I, son.
Brilliant.
Give monthly donations to your local NPR affiliate. Most of them have decently middle-of-the-road biased news, and a few have really good music programming (looking at you, KUTX).
CoW adaptive radix trees are the entire basis of $WORK's in-memory database -- we use them to store everything, then use boring old btrees to handle sorting data in arbitrary ways. A nice, performant persistent CoW radix tree would be a nice thing to have in my back pocket.
$WORK project heavily utilizes the test op to enable atomic updates to objects across multiple competing clients. It winds up working really well for that purpose.
I reach for adaptive radix trees over b-trees when I have keys and don't need to have arbitrary sort orderings these days. They are just that much more CPU and memory efficient.