CreepGin
And just the other day, I wanted to finally setup a private WoW server for me to play with my wife and kids. We had some random devices around the house: 2 PCs, a Steamdeck, and a MBP. I made sure they were all on the same network. Then, asked Claude Code to set it all up so we can play on the "most stable and latest" client for WoW. We all headed out for tennis. Came back in 2 hours and it was 99% done.
It setup AzerothCore and downloaded Chromiecraft for all 4 devices. It even setup VM Fusion on my mac correctly. I just had to tweak some mouse settings in the end. Normally, all this would take me an entire weekend to do. Pretty crazy how much of the tedious stuff AI can just take care of now.
I'm not aware of any other similar site with general topics, except for Hacker New and Reddit. =)
1) tldr summary of each post (when a link is first submitted). 2) Deduping posts. 3) Detecting when there are multiple stories (different links) that are basically covering the same thing, in which case it'll "merge" them by using only the best post (it decides). 4) Come up with titles for posts that don't have them (like twitter/bluesky posts).
Jev is used for:
1) Quickly getting rid of bad posts during the 1st stage of crawling. 2) Determining initial amount of points (based on a scale) awarded to post when it was first submitted.
There are probably few other cases I'm not thinking of right now. But basically, the gist is to use Jev for super frequent classifier tasks that are early in the pipeline so it can save cost.
This will roughly use about $40 of my AI credits per month. Anthropic gives Ultra users $200 monthly credit for API usage. So I'm happy I can make some good use out of it.
It's totally rad that something like this can be built now in less than 24 hours.
Grounded, buried, couchy, deep-seated, eyes, baked... It's like a thesaurus!
I feel like human comedians would have to deal with a lot of layered subtleties. They would make the potatoes _serve the bit_ instead of _be the bit_.
However, the concepts of comedic timing, subversion of expectations, and emotional punch are kinda contrary to how LLMs work. LLMs are trained to minimize cross-entropy loss. So by construction, they're biased toward the statistically expected.
Models are structurally biased toward the expected, which is the opposite of what makes a joke land or a poem transcend.
lowercase, maybe, but not em dashes.
Yup, same reason you can't throw manpower at a software project and expect a proportional outcome (Brooks's Law). AI amplifies what's already there; it doesn't conjure taste or product vision out of thin air.
For modding and OTA stuff I just use a scripting language with good interop (I made OneJS partially for this purpose). No more AOT issue and no more waiting for domain reload, etc.
Now I think about it, writing SourceGenerators is actually a great fit for AI agents.
> Rivlin told me that the bogus customer service number and the impostor representative were believable.
My wife said it was the persistent CC# inquiry combined with the heavy Indian accent that put her on alert.
Ask HN: Is Google AI Overview giving you scam phone numbers?
Today my wife was trying to cancel a GEICO policy. She searched for "geico home insurance phone number". On top of the results page in the AI Overview section, it gave out a phone number (1-800-442-9393) in the first sentence. So my wife called. The guy on the other end didn't ask anything insurance-related and just went straight for home address and credit card information. She got scared and...
Show HN: Unity WebGL Playground
Example: https://onejs.com/docs/web/tailwind#quick-example
Without TW, that snippet may need to take 3x more lines.
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My major issue with TW at the moment is that I use TW in a non-browser environment (Unity), so TW3 is fine since I can tweak everything with JavaScript. TW4 shifts everything to CSS, gives zero workarounds, and my setup crumbles.
For folks who don't know: Unity.Mathematics is a package that ships a low-level math library whose types (`float2`, `float3`, `float4`, `int4x4`, etc.) are a 1-to-1 mirror of HLSL's built-in vector and matrix types. Because the syntax, swizzling, and operators are identical, any pure-math function you write in C# compiles under Burst to SIMD-friendly machine code on the CPU and can be dropped into a `.hlsl` file with almost zero edits for the GPU.
I was scratching my head pretty much the whole time during the first read.
> It reads to me like typical marketing writing.
hmm maybe that's why it rubbed me the wrong way.
Even when they are not a telltale-sign, folks are afraid of using them now because of AI. I'm not saying em dashes are bad. Our books are littered with them, and that's why LLMs spit them out consistently.
https://medium.com/@brentcsutoras/the-em-dash-dilemma-how-a-...
Sorry, the article itself was really painful for me to read.