Iran war: What is happening on day 19 of US-Israel attacks? Iran has pledged "revenge" after Israeli strikes killed security chief Ali Larijani and commander of Basij paramilitary forces Gholamreza Soleimani, with Foreign Minister Abbas Araghchi saying Tehran's political system remains strong as the war entered its 19th day . Iran launched more attacks on Israel, causing extensive property damage, after an earlier strike killed two people in Ramat Gan. Political tensions are also rising in the United States, as senior counterterrorism official Joe Kent resigned, saying "we started this war due to pressure from Israel and its powerful American lobby". Meanwhile, President Donald Trump criticised NATO allies and partners for failing to provide stronger military support in efforts to end Iran's chokehold on the Strait of Hormuz.

Could Iran be using China's BeiDou system? Iran war: What is happening on day 17 of US-Israel attacks? Israel launched a new wave of attacks on Tehran as the US-Israel war on Iran entered its 17th day on Monday. Escalations continue in the Gulf region, where authorities suspended flights at Dubai international airport after a drone incident sparked a fire nearby. Dubai-based Emirates announced later that it was resuming limited flights, with several planned routes cancelled for the day.

Precise hardware performance models play a crucial role in code optimizations. They can assist compilers in making heuristic decisions or aid autotuners in identifying the optimal configuration for a given program.

Generative models are being increasingly used in science and industry applications.

Recent language models have shown impressive multilingual performance, even when not explicitly trained for it. Despite this, there are concerns about the quality of their outputs across different languages. In this paper, we show how disparity in the treatment of different languages arises at the tokenization stage, well before a model is even invoked. The same text translated into different languages can have drastically different tok-enization lengths, with differences up to 15 times in some cases. These disparities persist even for tokenizers that are intentionally trained for multilingual support.

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