Language Model for Dialogue Applications | 15 Jun 2022

Why in News?

A senior engineer at Google claimed that the company’s artificial intelligence-based chatbot Language Model for Dialogue Applications (LaMDA) had become “sentient”.

What is LaMDA?

• About:
  • Google had first announced LaMDA at its flagship developer conference I/O (Input/Output) in 2021 as its generative language model for the dialogue applications which can assure that the application will be able to converse on any topic.
  • LaMDA can engage in a free-flowing way about a seemingly endless number of topics, an ability that the company thinks can unlock more natural ways of interacting with technology and the entirely new categories of helpful applications.
  • LaMDA can have a discussion on the basis of the user’s inputs thanks completely to its language processing model which has been trained on large amounts of dialogue.
• LaMDA 2.O:
  • Google at I/O 2022 announced LaMDA 2.0 which will further build on these capabilities.
  • The new model will possibly take an idea and generate imaginative and relevant descriptions, can stay on a particular topic even if a user strays off-topic, and can also suggest a list of things that are needed for a specified activity.

What is the other language-based AI tool capable of?

• Generative Pre-trained Transformer 3:
  • An autoregressive language model that uses deep learning to produce human-like text.
  • In 2020, an article was published, claiming that it was written entirely by an AI text generator known as Generative Pre-Trained Transformer 3 (GPT-3).

What is a Chatbot?

• About:
  • Chatbots, also called chatterbots, is a form of Artificial Intelligence (AI) used in messaging apps.
  • This tool helps add convenience for customers—they are automated programs that interact with customers like a human would and cost little to nothing to engage with.
    • Key examples are chatbots used by businesses in Facebook Messenger, or as virtual assistants, such as Amazon's Alexa.
  • Chatbots tend to operate in one of two ways—either via machine learning or with set guidelines.
  • However, due to advancements in AI technology, chatbots using set guidelines are becoming a historical footnote.
• Types:
  • Chatbot with Set Guidelines:
    • It can only respond to a set number of requests and vocabulary and is only as intelligent as its programming code.
    • An example of a limited bot is an automated banking bot that asks the caller some questions to understand what the caller wants to do.
  • Machine Learning Chatbot:
    • A chatbot that functions through machine learning has an artificial neural network inspired by the neural nodes of the human brain.
    • The bot is programmed to self-learn as it is introduced to new dialogues and words.
    • In effect, as a chatbot receives new voice or textual dialogues, the number of inquiries that it can reply to and the accuracy of each response it gives increases.
      • Meta (as Facebook's parent company is now known) has a machine learning chatbot that creates a platform for companies to interact with their consumers through the Messenger application.
  • Advantages:
    • Chatbots are convenient for providing customer service and support 24 hours a day, 7 days a week.
    • They also free up phone lines and are far less expensive over the long run than hiring people to perform support.
    • Using AI and natural language processing, chatbots are becoming better at understanding what customers want and providing the help they need.
    • Companies also like chatbots because they can collect data about customer queries, response times, satisfaction, and so on.
  • Disadvantages:
    • Even with natural language processing, they may not fully comprehend a customer's input and may provide incoherent answers.
    • Many chatbots are also limited in the scope of queries that they are able to respond to.
    • Chatbots can be expensive to implement and maintain, especially if they must be customized and updated often.
    • The challenges of AI metamorphosing into sentient are far in the future; however, unethical AI perpetuating historical bias and echoing hate speech are the real dangers to watch for.

Source: IE