Rise of the Bots

by Rafael Casuso


Who is @Rafael_Casuso

  • Lead Front-End Engineer en StayApp

  • SnowStorm CEO and Co-Founder

  • Merlin Creator

  • Fullstack Senior Developer

  • Software Architect

  • JavaScript enthusiast


What is a Bot?

  • A Bot is an artificial intelligence with a human-like interface

  • A Conversational Bot simulates a conversation through programmatic responses

  • Are ChatBots the new apps?

  • Next big interface after Graphic, Mouse and Touch is Conversations (none is exclusive)

  • It usually runs on a messaging platform, external or custom, or is integrated into the OS

  • Famous bots (a type called Digital Assistants) include Siri, Cortana or Alexa


The Interface War

  • There is an ongoing War of Interfaces, driven by UX, with user adoption as the main goal

  • Conversation is the most natural interface for a human being

  • When Conversation is the Interface, Bot Personality is the UX

  • Different interfaces can be combined, graphical and conversational for example, as needed

  • There is also an ongoing Quest for the Lowest Friction

  • Bots on Messaging Platforms dodge the need for another app installation, thus reducing friction dramatically


Bot Types

  • There are endless possibilities for applications using conversational interfaces, both text and voice 

  • Internet of Things Device Manager: command-oriented

  • Customer Service: support and suggestions

  • Digital Assistant: hub for connected services, reservations, shopping

  • Advertisement: brand ambassadors, characters, friendly offers

  • Healthcare: medical appointments, diagnosis helper

  • Fintech: bank agent, financial advisor

  • Education: digital teachers, virtual tutors, examinators


Bot Intelligence

  • Rise of the Bots have come with the perfect storm: the emergence of AI, online services and the digital consumer

  • Conversational Accuracy is its UX success measure 

  • Simple Bots are applications that perform actions in response to keywords, exact phrases or predefined choices

  • Intelligent Bots can use Cognitive Services with Machine Learning

  • Natural Language Processing (NLP) is the most important cognitive process to achieve conversational accuracy

  • Machine Learning is based on general learning algorithms grounded in statistical inference instead of large sets of static rules 

Bot Intelligence


  • Discipline that uses Learning Algorithms, often grounded in statistical inference, to automatically learn rules through the analysis of large ammount of data

  • Statistical Inference is the process of infering Predictive Models

  • Predictive Models are created through main steps: data analysis, distribution visualization, transformation, predictive patterns inference from part of transformed data (Training) and finally model Evaluation with the other part of data

  • Neural Networks are a family of algorithms and models inspired by central nervous systems of animals

  • Examples are Google Cloud Machine Learning and Prediction APIAmazon Machine Learning or Microsoft Azure Machine Learning

Bot Intelligence

  • Bot main needs: Understand (parse text into structured data, categorize user intent), Converse (build natural answers), and Take Actions

  • Understanding includes extracting intents and entities from expressions through language models

  • Converse includes language generation, maintaining context (entities variables, user reference) and building a meaningful dialog

  • This main goals are achieved using Linguistic Analysis Libraries (Duckling) or APIs (IBM Linguistics)

  • Examples are Wit.ai (now Facebook Bot Engine), TextRazor, IBM Alchemy or Api.ai


Bot Intelligence

  • Taxonomy of models:

    • Retrieval-based models (easier) use a repository of predefined responses and heuristic to pick an appropriate response based on the input and context.

    • Generative models (harder) don’t rely on pre-defined responses. They generate new responses from scratch. Typically based on Machine Translation techniques.

  • Short (easier) conversations with goal of offering single response for single input vs Long (harder) ones with multiple turns and context.

  • Open domain (harder) where the user can take the conversation anywhere vs Closed domain (easier) where there is a specific goal.


Bot Intelligence

  • Image Analysis extracts useful information from images, related taxonomy (tags and categories) and face recognition

  • Emotion Recognition extracts range of feelings from images, texts or recordings

  • Speech Recognition allows text-to-speech and speech-to-text

  • ​Recommendations allows Frequently Bought Together, Item to Item and Personalized User Suggestions

  • Others include Academic Knowledge Relations or Articles Analysis

  • Examples are Microsoft Cognitive Services, IBM Watson and Google Cloud Vision, Speech Recognition and Translate APIs



Rise of the Bots Updated

By Rafael Casuso Romate

Rise of the Bots Updated

Conversations are the next big interface and software robots are the personification of software applications. Let's check out their possibilities.

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