Tootfinder

Dogfooding was one of RDF’s biggest challenges prior to the arrival of LLMs as powerful general-purpose clients. Why? Because transforming and presenting RDF specifications in RDF form was difficult. Today, that problem is gone. Here’s an example of the new RDF 1.2 primer, deployed as a knowledge graph that uses Linked Data principles to manifest a Semantic Web.
#RDF

Florian Thierrys #OER zu #QGIS und #Wikidata: https://…

Has anyone reductio ad absurdum claims of LLM creativity?
E.g. assume an LLM trained on all human knowledge in say 2000. Would it come up with LLMs?
Trained in 1900. Would it invent relativity?
Trained in 1500. Steam engines?
Trained in 100,000 BC. Could it even talk?
(I’d love to know if there’s papers on this.)

New York-based Jedify, whose platform connects to enterprises' knowledge sources via APIs to build a "context graph" for AI agents, raised a $24M Series A (Ram Iyer/TechCrunch)
https://techcrunch.com/2026/06/10/jedi

Jedify raises $24M to help companies arm AI agents with context on their business | TechCrunch
The funding round was led by Norwest, with participation S Capital VC, Cerca Partners, and Oceans Ventures. Snowflake Ventures also participated as a strategic investor.

RE: https://hachyderm.io/@nathandyer/116553199114385177
And he was essentially murdered by MIT, the US government, and the copyright industry at age 26 for attempting to liberate academic knowledge.
Meanwhile, folks wholesale downloading the Internet…

I hope these Indigenous families find closure, and that all provinces in Canada start to undertake these investigations so that children and babies buried without the knowledge or consent of the parents can be properly located and identified.
#FirstNations #indigenous #everychildmatters
https://www.ctvnews.ca/montreal/article/dark-side-of-quebecs-history-indigenous-families-exhuming-their-childrens-bodies-for-answers-closure/?utm_source=flipboard&utm_medium=activitypub

The Trump administration is working with each federal agency to grow the number of jobs it can strip worker protections from, according to three people with knowledge of the process.
The effort is part of the White House’s push to tighten the president’s control over career civil servants.
In an executive order last month, Donald Trump stripped roughly 8,000 employees of protections they have historically had before facing discipline.
The Office of Personnel Management is e…

Trump Officials Have Told Agencies to Find More Workers to Make At-Will
Trump already cut worker protections for 8,000 career civil servants. Agencies have been tasked with growing that number.

The Brain That Goes Quiet: Serving a Large Model's Knowledge at 131 Tokens per Second on an 8 GB Laptop by Removing the Large Model from the Runtime Path
Myeong Jun Jo
https://arxiv.org/abs/2606.12154 https://arxiv.org/pdf/2606.12154 https://arxiv.org/html/2606.12154
arXiv:2606.12154v1 Announce Type: new
Abstract: In earlier work I showed that a 35B-class Mixture-of-Experts model can be loaded and executed on a consumer laptop with 8 GB of GPU memory. That result solved a placement problem and immediately exposed a different one: even correctly placed, the large model needed roughly four seconds to answer, because it was still being invoked at every query. This paper documents what happened when I stopped invoking it. During an offline phase, the large model reads source documents and writes verified answer entries into a structured knowledge store; at runtime, only a lightweight router, a deterministic renderer, and a 1B-class model are active. On the same 8 GB laptop, end-to-end response time fell from approximately 4,465 ms to 518 ms, effective end-to-end throughput rose from 15.7 to 131 tokens per second, and the small model's streaming decode rate held at 226-237 tokens per second with a time-to-first-token of 29-62 ms. The bottleneck is structural: three different large models (Qwen, Gemma, and GLM class) all showed the same multi-second runtime cost, and all three produced usable knowledge stores offline. On a 563-entry store built from seventeen real documents, keyword routing collapsed to 1.5% top-1 accuracy while BM25-based routing reached 92.8% (99.4% top-3), and a confidence gate raised effective top-1 to 98.0% by escalating 12.3% of queries. Exact-match fidelity of the small model ranged from 9/9 to 0/9 across envelope formats carrying identical content. A 16-case verification gate blocked all ten corrupted entries while admitting all six supported ones.
toXiv_bot_toot

The White House directed Kash Patel, the F.B.I. director, to oversee a leak investigation into reporting by The New York Times
about security issues with the new Air Force One,
leading to a flurry of subpoenas to several Times reporters Friday night, according to people with knowledge of the situation.
Mr. Patel scuttled a planned trip to Chicago and spent roughly eight hours at the White House on Friday,
running the investigation from there rather than F.B.I. headqua…

White House Directed Patel to Oversee Investigation Involving Times Reporting
The F.B.I. director spent about eight hours at the White House Friday focused on the effort, which led to the subpoenaing of several Times reporters who wrote about the security of Air Force One.

Sources: Kuaishou plans to spin off its Kling AI video unit for an IPO in 2027 and is seeking a $20B valuation in pre-IPO funding talks with potential investors (The Information)
https://www.theinformation.com/articles/chinas-kuaish…

China’s Kuaishou Plans to Spin Off Kling AI Video Unit at $20 Billion Valuation
Chinese social media giant Kuaishou Technology is planning to spin off its Kling AI video business ahead of an initial public offering next year, in an attempt to capitalize on investors’ appetite for AI stocks, according to two people with knowledge of the plans. Kuaishou has held talks with ...