Automatic Validation of User-contributed Content Using Learned Similarity Function

The quality of user-contributed content at online platforms can vary. Manual validation of such content for quality and relevance is difficult and not scalable. No current techniques utilize known high quality content to rank user-contributed content. This disclosure describes techniques for scalable automatic validation of user-contributed content (UCC) provided to an online platform. A similarity function is learned based on merchant media and known high-quality user submitted media. The similarity function is used to score new UCC media and determine whether the new UCC media is relevant and of sufficient quality to include on the platform. The techniques improve the experience of using online platforms by ensuring that UCC is relevant to the entity with reference to which it is contributed and is of good quality. Further, the techniques can generate feedback on improving UCC contributions

Making User-Generated Content Available When a Device is Offline

Some applications such as digital maps support offline use, including download of certain types of data, e.g., map data of a region for navigation. However, the downloaded information does not include user-generated content (UGC), reviews, external feeds, problem reports, geo-tagged news, etc. Such content can include timely and topical information which is unavailable to users if their device is offline. This disclosure describes techniques to make curated UGC and third-party feeds of specific types available when a device is offline. UGC is curated by topic and location using a multimodal large language model or other suitable technique. With user permission, a map annotated with recent, relevant UGC is downloaded or pushed to a mobile app on the user device prior to the loss of wireless connectivity. Summarized UGC content is provided to enable offline operation. Key pieces of information that can enhance safety and improve user experience are thus made available even in the absence of a network. The described techniques can also be of value to users on low-bandwidth networks or in remote areas

A new cryptic species of \u3cem\u3eScorpiops\u3c/em\u3e Peters, 1861 (Scorpiones: Scorpiopidae) from the northern Western Ghats, India

A new cryptic species of Scorpiops (Scorpiopidae) is described from northern Western Ghats of India with integrated taxonomic approach. Scorpiops telbaila sp. n. is closely related to S. tenuicauda and differs from all species of Scorpiops in morphological features and raw genetic divergence of 5.4-14.1 %

A new species of Isometrus (Scorpiones Buthidae) from southern India

A new species of Isometrus (Buthidae) is described from India using integarted taxonomic approach. Isometrus kovariki sp. n. is closely related to I. thurstoni, and differs in morphological features and raw genetic divergence of more than 9

A new species of \u3cem\u3eIsometrus\u3c/em\u3e (Scorpiones: Buthidae) from southern India

A new species of Isometrus (Buthidae) is described from India using integrated taxonomic approach. Isometrus kovariki sp. n. is closely related to I. thurstoni, and differs in morphological features and raw genetic divergence of more than 9%

Two new species of \u3cem\u3eChiromachetes\u3c/em\u3e (Scorpiones: Hormuridae) from the northern Western Ghats, India

Two new species of Chiromachetes Pocock, 1899 (Hormuridae) are described from the northern Western Ghats of India using an integrated taxonomic approach. Chiromachetes parakrami sp. n. and C. ramdasswamii sp. n. are closely related and differ from each other and C. sahyadriensis by morphological features and raw genetic divergence of 7.9–9.4 %

Evaluation of the Amphibian Fauna of the Semi-arid and Arid Grassland Habitats in and around the Mayureshwar, Rehekuri, and Karmala Wildlife Sanctuaries in Maharashtra, India

Few studies document amphibian species composition from arid and semiarid environments. Scatteredbodies of water in the semi-arid and arid landscape around Pune, Maharashtra, India, could be viable amphibian habitats; however; information on amphibians using these bodies of water is not available. In a preliminary study, we assessed the amphibian diversity and population status in three wildlife sanctuaries and surrounding areas near Pune. We also compared the use of artificial and natural ponds by amphibians and surveyed the amphibians for the presence of the chytrid fungus

SparCML: High-Performance Sparse Communication for Machine Learning

Applying machine learning techniques to the quickly growing data in science and industry requires highly-scalable algorithms. Large datasets are most commonly processed "data parallel" distributed across many nodes. Each node's contribution to the overall gradient is summed using a global allreduce. This allreduce is the single communication and thus scalability bottleneck for most machine learning workloads. We observe that frequently, many gradient values are (close to) zero, leading to sparse of sparsifyable communications. To exploit this insight, we analyze, design, and implement a set of communication-efficient protocols for sparse input data, in conjunction with efficient machine learning algorithms which can leverage these primitives. Our communication protocols generalize standard collective operations, by allowing processes to contribute arbitrary sparse input data vectors. Our generic communication library, SparCML, extends MPI to support additional features, such as non-blocking (asynchronous) operations and low-precision data representations. As such, SparCML and its techniques will form the basis of future highly-scalable machine learning frameworks