| |July 202019Achieving Real-Time IntelligenceArtificial Intelligence (AI)-powered applications based on advanced computational linguistics and natural language understanding can be used to extract signals based on contextual relevance from thousands of global, regional and local sources including internet URLs, news, research, blogs, social media, internal proprietary documents and content from premium sources. Such AI-enabled solutions are used to interpret millions of global events as they occur and analyze them through comprehensive causal models individualized for each company to develop an outlook. Next, they determine its relevance to one or more firms and rate the impact of the information via a rating scale for severity.To accurately achieve real-time intelligence, the AI-based analysis should incorporate the following components centered around the ideas of context and relevance:· Firm-specific operating models that comprise a network of factors that will impact the firm· A way to classify the information into one or more topics and determine its relevance by examining the firm's Information Model· An assessment of the potential impact on the firm by analyzing impact phrases within the informationNatural Language Understanding: The Key Element for Determining Context and RelevanceUnderstanding context is a multi-faceted challenge. Natural language understanding (NLU) involves applying computational linguistics principles to reverse engineer text back to its fundamental ideas, and realizing how the ideas were connected together to form sentences, paragraphs and the full document. As the natural language text is processed, it needs to be done in the right context which can only be done by focusing on the language structure; not just on the words in the text.The words in many languages can be used in multiple senses, so it is important to disambiguate word senses so their usage in a particular document can be accurately understood. Text documents often use domain specific discourse models, (e.g. legal contracts, news articles, research reports, etc.). There are certain properties of such domain discourse models that should be incorporated in the AI technology in order to enhance NLU.Many words may also be used as proxies within a document. AI technology must have a way to recognize and understand proxies like "Xerox" for "copy." In some cases, text in a document may refer to knowledge which is not explicitly part of the text. Humans can understand this with prior knowledge. AI technologies on the other hand have to create a repository of global knowledge that can be retrieved to supplement the document text in order to gain full understanding of its meaning.ConclusionActive investment strategies depend on identifying such information inefficiencies, however many currently use research methods which simply cannot process the deluge of the near-real-time information now available in a systematic and efficient fashion.Timely processing of structured and unstructured data and under-standing the complex interrelation-ships embedded in such informa-tion is critical for the success of any active investment strategy. Through AI-enabled applications, the chal-lenge of aggregating and interpreting content from around the world can now be more effectively met to help determine the potential relevance and impact of that information on a company's intrinsic value. Vikram MahidharTimely processing of structured and unstructured data and understanding the complex interrelationships embedded in such information is critical for the success of any active investment strategy
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