Salman is a Chartered Financial Analyst and heads up the Tech Team at Thomson Reuters in Singapore. He has led over 20 risk, trading and technology implementations from start to finish over his career. As the Head of the Tech Team at Thomson Reuters, Salman combines his rare skill set of strong knowledge in technology and finance to formulate unique solutions. He holds a degree and a number of professional qualifications in the fields of Computer Science, Machine Learning, Big Data and Technology from King's College London, Imperial College and the Massachusetts Institute of Technology.
As the world continues to undergo rapid technological advancements and societal changes, the way we work and conduct business is also evolving.
Artificial intelligence (AI) is stepping up in more concrete ways in blockchain, education, internet of things, quantum computing, arm race and vaccine development.
Startup Genome published the Global Startup Ecosystem Report for 2018 recently and I wanted to quickly summarise some of the key findings.
In March 2018, I read an article about the new Artificial Intelligence Arms Race which has been on my interests radar for a few years. What was new, was that this article referred to a paper from the Future of Humanity Institute, University of Oxford.
As the Text Metadata Services (TMS) Lead in Singapore, I wanted to share my knowledge by writing a short piece on an important aspect of Natural Language Processing (NLP) called Named Entity Recognition (NER). Named Entity Recognition is not to be confused with Named Entity Resolution. A simple example to distinguish between the two is that a machine reading a document might recognize a person, say William Henry Gates and a second person in the same document, say Bill Gates. Named Entity Resolution is a way in which these two names can be resolved to a single person whom we all know as one of the founders of Microsoft, Bill Gates.
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