We welcome the convening of the Lake Lucerne Summit in Switzerland today and the continuation of US-Iran talks. We thank Pakistan and all parties that contributed to this understanding and look forward to building on it. We also thank Switzerland for hosting the summit.

Granit Xhaka, the Sunderland midfielder and captain, has admitted to forging a Covid-19 vaccination certificate. Xhaka has apologised for what he described as a “mistake” made in a “state of emotional turmoil”, and has been left out of Switzerland’s squad for the upcoming internationals. According to a report from Blick, an outlet in Xhaka’s native Switzerland, over the weekend, the Lucerne public prosecutor’s office has opened proceedings against the national team captain, who is expected to be questioned in early October. More from @PJBuckingham & @CWeatherspoon_

Luzerner Kantonalbank, one of Switzerland's leading cantonal banks, returns as a partner for CV Summit 2026! Join us on Sept 29-30 to explore how LUKB and other institutions are creating more efficient, secure, and interconnected financial markets.

Families in Luzerne County have been getting a bill for the rain that hits their own roofs, all to pay for a cleanup 200 miles away. Not anymore. Thank you @POTUS for reversing the Obama-era Rain Tax mandate and @RepBresnahan for fighting for this since before he took office and for getting it done. Congressman Bresnahan made this happen!!!

Congratulations to our very own Eddie White, who will be inducted into the Luzerne County Chapter of the Pennsylvania Sports Hall of Fame this summer 👏 Learn more:

⚡ Make aggregations over billions of records up to 100x faster by adding one line at the top of your query, with statistically rigorous confidence intervals built in. That's approximate queries in Elasticsearch ES|QL. Title: Approximate queries in Elasticsearch ES|QL: 100x faster on billions of records, with built-in confidence intervals URL: 📝 Overview Elasticsearch 9.4 adds approximate query execution to ES|QL. Just prepend SET approximation = true; to an existing query and automatic sampling and extrapolation kick in, with no query rewrites needed. ❓ Challenges Solved Exact aggregations over billions of documents are costly because compute scales linearly with row count. That hampered interactive exploration and real-time dashboards on large indices. 💡 Methodology & Proposed Approach ・Sampling happens at the Lucene layer, reading only the sampled documents, so I/O and compute savings are proportional to the sampling rate ・The query runs on the sample, then results are automatically scaled up to represent the full dataset ・Confidence intervals are computed rigorously via a bootstrap over sub-partitions of the sample ・Each result carries a certified flag indicating whether formal statistical guarantees hold 🎯 Use Cases An agent can sweep billions of documents in sub-second time, narrow down candidates, and zoom into exact queries only where needed. It also speeds up dashboards and pattern detection over massive logs. 📊 Results ・On ClickBench, an average of 23x with confidence intervals, peaks around 100x per query, and up to ~300x without interval computation ・Since sampling cost stays constant, speedup grows with dataset size ・Supported aggregations include COUNT, SUM, AVG, MEDIAN, PERCENTILE, and STD_DEV, with rows and confidence_level tuning accuracy versus speed #Elasticsearch# #DataAnalytics#