If they shut down opus 4.5 I'll cry
I think we’re all very happy with the pricing on it.
Readit Newsteaearlgraycold commented on Elevated errors across many models status.claude.com/inciden... · Posted by u/pablo24602
teaearlgraycold commented on Elevated errors across many models status.claude.com/inciden... · Posted by u/pablo24602
I’m imagining a steampunk dystopia in 50 years: “all world production stopped, LLM hosting went down. The market is in free-fall. Sam, are you there?”
Man that cracks me up.
The nice thing is unlike Cloudflare or AWS you can actually host good LLMs locally. I see a future where a non-trivial percentage of devs have an expensive workstation that runs all of the AI locally.
teaearlgraycold commented on Kimi K2 1T model runs on 2 512GB M3 Ultras twitter.com/awnihannun/st... · Posted by u/jeudesprits
In their AMA moonshot said it was mainly finetuning
OpenAI and the other big players clearly RLHF with different users in mind than professionals. They’re optimizing for sycophancy and general pleasantness. It’s beautiful to finally see a big model that hasn’t been warped in this way. I want a model that is borderline rude in its responses. Concise, strict, and as distrustful of me as I am of it.
It's also gotten cheaper nominally. I just got a new base MBA for $750. Kinda surprised, like there has to be some catch.
I feel bad for their competitors. We need good competition in the long run but over the last few years it's made less and less sense to get something other than an Apple laptop for most use cases.
It would be incredibly ironic if, with Apple's relatively stable supply chain relative to the chaos of the RAM market these days (projected to last for years), Apple compute became known as a cost-effective way to build medium-sized clusters for inference.
It already is depending on your needs.
There are two very simple causes to point to why touch keyboards turned to shit:
1. Crowdsourced word weighting: your keyboard's stochastic predictions are no longer mostly based on your typing, but rather on what 'everyone' is typing as their next word. This makes the word replacements it does often suboptimal to downright nonsensical.
2. Aggressive lookbehind correction: these days you have to be seriously on your guard for your keyboard to not sneak-edit something you typed 5 words back, because autocorrect suddenly decided that the probability is high you meant to say something else there (which it clearly isn't, as your eyes and brain exist)
The problem your encountering is downstream from point 1. Basically your keyboard thinks due to the way most people construct a particular sentence, you're gonna want to type "bold" next, despite "hold" clearly clearly making more sense. So it'll force "b" on you 4 times in a row until it realizes you really want to type "h".
Going back to the old style of doing keyboards (mostly user-learned dictionaries and probability weighting, and little lookbehind autocorrrect) could be done, but within Google and Apple there are probably people who got promoted by switching to the current shitty system. They'll block off any attempt at someone messing with their pride.
(There is a third 'problem' where your visual keys do not correspond to the touchmap at all. Swiftkey has a feature where it can show you what your touchmap and heatmap look like versus the actual layout and it its often staggeringly different, with many keys vastly tilted. When you try to desperately type "h" after 4 misses, you're doing that with your index finger in "hunt and peck" mode, which does correspond to the visual layout but not with your usual typing on the touchmap layout. There is no way for your keyboard to know you're in "hunt and peck" accuracy mode.)
Sometimes I think about how much harm has been done to the world just so a few people can get a vacation home on Lake Tahoe. Every increase in YouTube ads leading to millions of hours wasted - but hey that L7 got a sweet new lake house!
teaearlgraycold commented on It's cheaper to buy a new printer every month idiallo.com/byte-size/che... · Posted by u/foxfired
The seeming paradox reminds me of a simlar flavor one: the fact that if you accidentally knock a hole in your drywall, it's cheaper to cover it with a flat screen TV than to pay someone to fix the hole.
Not that hard to patch the drywall yourself though.
teaearlgraycold commented on Django: what’s new in 6.0 adamj.eu/tech/2025/12/03/... · Posted by u/rbanffy
> your side effects (e.g. database writes) aren't idempotent
What does idempotent mean in this context, or did you mean atomic/rollback on error?
I'm confused because how could a database write be idempotent in Django? Maybe if it introduced a version on each entity and used that for crdt on writes? But that'd be a significant performance impact, as it couldn't just be a single write anymore, instead they'd have to do it via multiple round trips
In my experience async job idempotency is implemented as upserts. Insert all job outputs on the first run. Do (mostly) nothing on subsequent runs. Maybe increment a counter or timestamp.
teaearlgraycold commented on The programmers who live in Flatland blog.redplanetlabs.com/20... · Posted by u/winkywooster
Talk about moving the goalposts! Did you implement TypeScript yourself before using it?
The parent comment implies that the tool does not exist yet.
teaearlgraycold commented on The programmers who live in Flatland blog.redplanetlabs.com/20... · Posted by u/winkywooster
As others have said, the lack of any examples makes this post fall flat.
Also, consider that good work - particularly in art but also in engineering - requires constraints. Knowing what you cannot do adds guard rails and a base set of axioms around which you can build. Perhaps the power of LISP macros and AST manipulation is not “powerful and thus good”, but rather “too powerful and thus complicated”. Needing to write out a boring old function/class/module instead might leave you with code that is simpler to read and design around.