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Google Assistant supercharged with AI Gemini - Vimarsana News

Google Assistant supercharged with AI Gemini

In an era-shifting update, Google unleashed its new AI model Gemini, launched a premium subscription service, and slipped AI into the core of consumers' phones

Source: qz.com
Meta to tighten policies on misinformation and deep fakes during elections - Vimarsana News

Meta to tighten policies on misinformation and deep fakes during elections

SAN ANTONIO - Meta is going to take a harder stance on misinformation and deep fakes during election season.The parent company of Facebook and Instagram said to

Palantir's stock surged as AI demand drives revenue - Vimarsana News

Palantir's stock surged as AI demand drives revenue

The data management company's stock is up 30%, as investors are happy to see companies making money on AI

Source: qz.com
"Extracting Symptoms of Agitation in Dementia from Free-Text Nursing No" by Dinithi Vithanage, Yunshu Zhu et al. - Vimarsana News

"Extracting Symptoms of Agitation in Dementia from Free-Text Nursing No" by Dinithi Vithanage, Yunshu Zhu et al.

Nursing staff record observations about older people under their care in free-text nursing notes. These notes contain older people's care needs, disease symptoms, frequency of symptom occurrence, nursing actions, etc. Therefore, it is vital to develop a technique to uncover important data from these notes. This study developed and evaluated a deep learning and transfer learning-based named entity recognition (NER) model for extracting symptoms of agitation in dementia from the nursing notes. We employed a Clinical BioBERT model for word embedding. Then we applied bidirectional long-short-...

Source: uow.edu.au
"DFN: A deep fusion network for flexible single and multi-modal action " by Chuankun Li, Yonghong Hou et al. - Vimarsana News

"DFN: A deep fusion network for flexible single and multi-modal action " by Chuankun Li, Yonghong Hou et al.

Multi-modal action recognition methods can be generally classified into two categories: (1) fusing multi-modal features with simple concatenation or fusing the classification scores of individual modalities without considering the interaction among the multi-modalities; (2) using one of the modalities as privileged information in training to boost the recognition on the other modalities in inference. The former approach usually is not able to deal with the cases where one of the modalities is missing. In the latter, the trained classifier does not work on the privileged modality. To address th...

Source: uow.edu.au