A brave eight-year-old boy helped save his grandad after the pair drifted more than two miles (3km) from the coast on a capsized kayak. Marley and his granscha, David Dai Jones, from Mountain Ash, Rhondda Cynon Taf, had been kayaking off Fontygary in the Vale of Glamorgan on 27 May when they capsized and were unable to get back onboard. Dai managed to help Marley back onto the kayak but could not climb back on himself. He remained in the water holding on as the pair drifted in the strong Bristol Channel currents. Despite the frightening situation, Marley remained calm and used a mobile phone kept in a waterproof pouch to contact his nan on shore, who called 999.

Sentence transformers are language models designed to perform semantic search. This study investigates the capacity of sentence transformers, fine-tuned on general question-answering datasets for asymmetric semantic search, to associate descriptions of human-generated routes across Great Britain with queries often used to describe hiking experiences. We find that sentence transformers have some zero-shot capabilities to understand quasi-geospatial concepts, such as route types and difficulty, suggesting their potential utility for routing recommendation systems.

Despite being able to generate fluent and grammatical text, current Seq2Seq summarization models still suffering from the unfaithful generation problem. In this paper, we study the faithfulness of existing systems from a new perspective of factual robustness which is the ability to correctly generate factual information over adversarial unfaithful information. We first measure a model's factual robustness by its success rate to defend against adversarial attacks when generating factual information. The factual robustness analysis on a wide range of current systems shows its good consistency with human judgments on faithfulness. Inspired by these findings, we propose to improve the faithfulness of a model by enhancing its factual robustness. Specifically, we propose a novel training strategy, namely FRSUM, which teaches the model to defend against both explicit adversarial samples and implicit factual adversarial perturbations. Extensive automatic and human evaluation results show that FRSUM consistently improves the faithfulness of various Seq2Seq models, such as T5, BART.

Schools are to be given £1.3m to set up clubs to teach computer coding. The investment over five years is part of the Welsh Government's £100m to raise school standards over the assembly term. Education Secretary Kirsty Williams said she wanted all pupils to have the opportunity to learn about and get involved in coding as the importance of digital skills continues to grow. It is estimated there will be 100,000 new coding jobs by 2020 in the UK. The Welsh Government said there are currently about 1.5 million jobs in the digital sector in the UK, 400,000 of which involve coding.