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RailsConf 2017: Syntax Isn't Everything: NLP for Rubyists by Aja Hammerly Natural Language Processing is an interesting field of computing. The way humans use language is nuanced and deeply context sensitive. For example, the word work can be both a noun and a verb. This talk will give an introduction to the field of NLP using Ruby. There will be demonstrations of how computers fail and succeed at human language. You'll leave the presentation with an understanding of both the challenges and the possibilities of NLP and some tools for getting started with it.
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The video titled "Syntax Isn't Everything: NLP for Rubyists" by Aja Hammerly, presented at RailsConf 2017, offers an introduction to Natural Language Processing (NLP) specifically tailored for Ruby developers. In the talk, Hammerly emphasizes the complexities and challenges of teaching computers to understand human language, which is often nuanced and context-sensitive. The speaker begins by defining NLP as the intersection of computer science, artificial intelligence, and linguistics, focusing on the interactions between computers and human language. Key points discussed in the presentation include: - **Bad NLP Experiences**: Hammerly connects the audience's experiences with poor natural language interfaces, explaining how current systems struggle with understanding human nuances, often leading to frustrating interactions. - **The Promise of NLP**: The speaker highlights improvements in NLP as essential for achieving better user experiences, proposing a shift where computers learn to engage in conversations similar to human interactions. - **Accessibility Use Cases**: A significant benefit of enhanced NLP is its application in accessibility, particularly for children or individuals with disabilities who rely on voice interactions due to limitations in reading or typing. - **Sentiment Analysis Example**: Hammerly shares her past experience of conducting sentiment analysis on tweets using emoji scores, demonstrating how NLP can help analyze user feedback more effectively. - **Challenges with Language**: The speaker starkly outlines the difficulties in NLP by describing the irregularities and imprecision of human languages, which complicate machine understanding. She notes how idioms, slang, and evolving language patterns significantly challenge NLP efforts. - **Historical Context**: Hammerly mentions historical milestones in NLP development, including Alan Turing's contributions and the emergence of early chatbots, underlining the long-standing efforts in this field. - **Demo and Tools**: She provides a live demo using the Google Cloud Natural Language API, illustrating how Ruby developers can implement NLP functionalities by leveraging existing models rather than building them from scratch. - **Conclusion**: Hammerly concludes by encouraging developers to experiment with NLP technologies and presents Google’s resources for getting started. The session ends with a live sentiment analysis demo reflecting the audience's interactions on Twitter, showcasing practical applications of NLP concepts. Overall, the presentation conveys not only the potential of NLP in enhancing interactions with technology but also the significant obstacles posed by human language complexity. Rubyists in the audience leave with an understanding of basic NLP concepts, challenges, and practical tools to help them begin exploring this fascinating area of tech.
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