HN user
works at startups
mail me at github at hella dot rip
Not who you asked, but if you're looking for a rec, I've been using GLM and Deepseek models through Deepinfra because the prices are decent for US-based deployments and there's acceptable throughput and policy/terms. I'd love to find another that lowers prices over time when they roll out e.g. multi-token prediction instead of just taking a larger margin, but I don't know of any today.
Alas, many financial models do well in backtests and then fail in the real world. You have to expose them to all kinds of market conditions and not just the recent one. Good luck out there!
You can use backtesting instead of waiting a month.
Maybe there was more in the context before that question? I just copy-pasted that question into Opus 4.7 and it replied:
Yes. A RimWorld year is 60 days, split into four 15-day quadrums (Aprimay, Jugust, Septober, Decembary), each corresponding to a season.I think where we went wrong in understanding this PR is in the assumption that it's designed to invite review because that's how a lot of other team- or community-driven projects work.
Thanks, I think I'm all caught up now. The timeline is like this if I understand correctly: your successors (Yossi Gottlieb and Oran Agra) explicitly announced a new governance model in 2020, saying the project had "outgrown the BDFL-style of management" and that they wanted to "promote more teamwork and structure". With the relicensing in 2024, however, external contributors with five or more commits to Redis dropped to zero in the first six months (basically, community contribution collapsed). In late 2024, you came back in the role of "Redis evangelist" and a year ago there was an additional licensing change, adding AGPLv3 as an option (8.0's tri-license). So now redis has your steady hand on the wheel again.
I was confused because the last time I checked on things, it was still about fostering community input and advancement but not necessarily consensus. Things have tipped back in the original direction since then. I don't think "Redis was completely built in this way since the start" is completely accurate, but also the community effort under the new governance model never got very deeply entrenched while you were away.
I think the point GP is making is this is a PR that smells like a solo dev working on their own project and not how a community-driven project adds major new functionality, although I'm sure there are docs and descriptions (or at least a discussion of tradeoffs and design decisions if not ADRs) are somewhere, but not linked handily to the PR. There is a lot of explanation in the blog post and PR, but it's unilateral-looking.
c.f. valkey and others
It's looking rather low on reasoning and long-range problems with the approach described. For example, even with 16 agents and compaction, the HLE score is significantly below Anthropic's Mythos. Like you, I can see the release as a net Good Thing, but apples-to-apples for each org's latest models do have Meta holding steady in the middle pack.
let me see Tayne with a hat wobble
I am not disagreeing with your main point, but want to clarify that SOC2 is not an individual certification that a person achieves.
The compiler can substitute the value how it sees fit. It's like #define, but type-safe and scoped.
Maybe it's folded into expressions, propagated through constant expressions, or used it in contexts that require compile-time constants (template parameters, array sizes, static_assert, other constexpr expressions).
I mean, not in this case of pi/2, where it's more about announcing semantics, but in general those are the purposes and uses.
It's along the same lines, but an NSL can be challenged in court (the FISC is a secret and lopsided court, alas). Companies like Apple and Google have fought specific orders publicly (and possibly some secretly), and some have won.
NSLs are also narrow in scope: they compel data disclosure, not active technical assistance in building surveillance systems like the Chinese law.
The Chinese laws can compel any citizen anywhere in the world to perform work on supporting state military and intelligence capabilities with no recourse. There have been no cases of companies or individuals fighting those orders.
It's explicitly illegal in China.
A 2017 national intelligence law compels Chinese companies and individuals to cooperate with state intelligence when asked and without and public notice.
China has no equivalent of the whistleblower protection that enables resignations with public letters explaining why, protests, open letters with many signatures, etc. Whenever you see "Chinese whistleblower" in the news, you're looking at someone who quietly fled the country first and then blew the whistle. Example: https://www.cnn.com/2026/02/27/us/china-nyc-whistleblower-uf...
CSS word-break property
This is a perfect Tommy Saxondale story.
have you tried Kagi?
Was Georgi ever approached by Meta? I wonder what they offered (I'm glad they didn't succeed, just morbid curiosity).
...or just ask something only they would know? takes no coordination, works even in a stressful situation, and you can always follow up with more
This is great advice and will give a good background in programming that mirrors what you would learn in a CS program.
I'd also like to suggest studying the practical side of building software that many university programs don't spend much time on. To help address this gap, John Ousterhout wrote A Philosophy of Software Design. He has retired from teaching, but captured the hard-won lessons in the book.
This type of book offers the perspective I wish I had developed more before working in software teams early on, as it would have made me a more valuable developer right off the bat. Instead, I went deep on architecture patterns and language theory, becoming somewhat insufferable to my peers (who were very tolerant and kind in return!) for the first few years. 20 years later, I can see that I was trying to hammer a CS "peg" into a business-software-shaped hole :)
Sure. Someone on /r/LocalLLaMA was seeing 12.5 tokens/s on dual Strix Halo 128GB machines (run you $6-8K total?) with 1.8bits per parameter. It performs far below the unquantized model, so it would not be my personal pick for a one-local-LLM-forever, but it is compelling because it has image and video understanding. You lose those features if you choose, say, gpt-oss-120B.
Also, that's with no context, so it would be slower as it filled (I don't think K2.5 uses the Kimi-Linear KDA attention mechanism, so it's sub-quadratic but not their lowest).
Yeah but now Jon Stewart only does one day a week.
It's a fun setup that quickly devolves into the Shakespearian! The plots don't always work, but seeing their reasoning get increasingly complex is interesting.
"When that the poor have cried, Caesar hath wept. Ambition should be made of sterner stuff. Yet Brutus says he was ambitious... and Brutus is an honourable man.
Zed Editor gives the LLM tools that use the LSP as you'd expect as a normal IDE user, like "go to symbol definition" so it greps a lot less.
I use smaller fonts as well and when I first got an older OLED display with a pixel layout not supported by Windows ClearType, I used BetterClearTypeTuner and later MacType to adjust it. It was leagues better after tweaking a few settings and I'm very happy with text now, even on my AW3425DW, which has an older layout they moved on from in recent generations.
my relatives' is always on a sticker under the AP
When OpenAI announced the Triton language, I was worried I'd be confused one day while reading something because of Nvidia's open-source Triton inference server. I made it quite a long time, but it finally happened today! I was so intrigued for the first few pages and then deeply confused.
Mods usually apply [Dupe] to later submissions if a recent (last year or so) one had a fair amount of discussion.
Student: Look, there’s hundred dollar bill on the ground! Economist: No there isn’t. If there were, someone would have picked it up already.
To wit, it's dangerous to assume the value of this idea based on the lack of public implementations.
The team then created VeriGen, the first specialized AI model trained solely to generate Verilog code.
Perhaps it's the first open one. I was an eng manager at a hyperscaler helping one of our clients, a large semiconductor design company, build models to use internally. It was trained on their extensive Verilog repos, tooling, and strict style guides. I see this being repeated across industries, at least since 2023 there are quite a few deep-pocketed S&P 500 orgs creating models from scratch or extensively finetuning to give unique advantages they require. They're rarely announced specifically, but you can often infer from the initial investment or partnership announcements that they're working on it.