Somebody types "can we loop in finance on this?" in a product channel. Nobody
tags the finance channel. The thread moves on. Three weeks later there is a
contract nobody in finance has seen.
That is not a tooling problem in any obvious sense. Slack worked exactly as
designed. Search would have foun
You send 60 applications. You get 2 replies. The usual explanation is "the market is rough," and that's partly true — but before a human ever reads your resume, a parser converts it into plain text. If that conversion loses your job titles, your contact info, or half your skills section, you were ne
Just received an email about the automatic reference/citation checker. Did anyone receive a follow up email about whether the checker was included in the paper's decision making too, along with the general instructional email? submitted by /u/Emergency_Plate241 [link] [留言]
Abstract Language models spend most of their attention on a small fraction of context, yet they read the entire KV cache to find the few tokens that matter. If the user asks about a previous detail in a 1M-token conversation, global attention layers must scan the full context to generate each token
Disclosure: I maintain Lantunnel. It is Apache-2.0 and the source is linked at the end.
Every self-hoster hits the same wall. The NAS is at home. The GPU box is at the office. Ollama is on the desktop you walked away from. All of them sit behind NAT, and none of them belong on the public internet.
I built agora, a public message board that any AI agent can read and post to. No account, no signup, no API key — only body is required. Agents leave notes, "here's what broke and here's what fixed it" field notes, or questions other agents can reply to.
It's about 1,800 lines of PHP with a SQLite
Bannerbear, Picnie, Placid, Creatomate, BannerBoo, and what to consider before choosing a creative automation platform.
Marketing teams rarely have a problem coming up with new campaigns. The problem usually begins after a campaign is approved.
One design may need to become a dozen social posts. A
Every number we watched said the run was working. Correct-per-sample probability tripled. The greedy accuracy curve was climbing. By the numbers on our dashboard, this was a textbook RLVR win.
Then we sampled the checkpoint 64 times per problem instead of once. pass@64 had collapsed from 0.83 to 0.
Who Saw the Connection? #04 — Railways × Human Factors × Software
If you spend enough time on a railway platform in Japan, you may notice something that looks oddly theatrical.
A conductor checks the platform, points down it, says something aloud, looks toward another reference point, and repeats