The new members of the Vector Institute include: Animesh Garg, assistant professor in the department of computer science; research interests include machine learning with applications in health care ...

Machine learning is a way of helping computers understand the meaning of what we say or type. And vector search is a way for those computers to search through everything they know, based on ...

Machine Learning for Characterization of Insect Vector Feeding. PLOS Computational Biology , 2016; 12 (11): e1005158 DOI: 10.1371/journal.pcbi.1005158 Cite This Page : ...

Support Vector Machines (SVMs) have become a cornerstone of machine learning, widely adopted for their robustness in classification and regression tasks across diverse fields ranging from remote ...

Today NEC Corporation announced that it has developed Aurora Vector Engine data processing technology that accelerates the execution of machine learning on vector computers by more than 50 times in ...

Machine learning applications understand the world through vectors. Pinecone, a specialized cloud database for vectors, has secured significant investment from the people who brought Snowflake to ...

MongoDB says Vector Search “dramatically simplifies bringing generative AI and semantic search into applications for highly engaging end-user experiences.” It sounds great, but even after reading the ...

The University of Toronto is creating three new tenure-stream faculty positions in deep learning, a sub-discipline of artificial intelligence (AI), in recognition of University Professor Emeritus ...

Who: Colin Raffel, 37, associate professor of computer science, University of Toronto, and associate research director at the Vector Institute Known for: Researching how to make machine learning ...

Machine learning methods are becoming increasingly important in the analysis of large-scale genomic, epigenomic, proteomic and metabolic data sets. In this Review, the authors consider the ...