Abstract: 

With notable innovations like Alexa and Siri becoming a part of our daily lives, there is a growing appreciation for Natural language Processing (NLP) as it is no longer a nascent facet of AI technology. From sentiment analysis techniques in retail to named entity recognition and virtual assistants in financial markets, NLP is attaining relevance across various industries.

Latest notable NLP trends such as multimodal language models, NLP libraries, transfer learning among various others are enabling enterprises to accelerate their NLP deployments and gain valuable insights for critical business decisions. Companies such as Google, use NLP for various functions ranging from autocorrection, smart search, language translation to email classification. Similarly, Quora employs NLP to deduct the frequency of repetitive questions with duplicate detection techniques.

According to recent research, the global NLP market size is expected to reach $35.1 billion by 2026. The reason is the significant shift from human-computer interaction to human-computer conversation. With AI-powered interfaces augmented with NLP, enterprises now have the ability to drive business growth with unprecedented technological advancements. However, in the vein of understanding the full scope of NLP, enterprises must be mindful of unsupervised models that generate biased outcomes and hinder the capabilities of NLP mechanisms.

In a talk that guides the audience through the key strategies, strengths and challenges around NLP, Dr. Sameer Maskey will deliver the following key takeaways:

Impact and application of NLP by enterprise across various industries
Key NLP techniques that are being leveraged to accelerate business success
The do’s and don’ts of adopting and deploying NLP techniques and how it can take businesses to the next level."

Bio: 

Sameer Maskey is the Founder & CEO of Fusemachines Inc, an AI talent platform and services provider. Dr. Maskey has more than 18 years of experience in artificial intelligence, natural language processing, machine learning, data science and is Adjunct Associate Professor at Columbia University. After completing his PhD in Computer Science from Columbia University, he joined IBM Watson Research Center where he invented various statistical algorithms to improve speech-to-speech translation and question answering systems.