Also look on MIT Technology Review
Conversational UI, Three Basic Types:
- Voice Assistants/Voice only: you talk to. Google has OK Google, Amazon has Echo. Note that both of these use visual cues to indicate states of listening, talking, confusion, etc.
- Chatbots: you type to. Facebook has M, Slack’s Slackbot, Read about other top chatbots
- Intermodal/ Virtual Agents: combination of talking and/or typing that interacts with traditional visual interface. Apple has Siri, Microsoft has Cortana. Combines voice, touch, visuals.
(Image from Design Actions for Smart Assistant)
Early Conversational UI/Natural Language Interface
“ELIZA is an early natural language processing computer program created from 1964 to 1966 at the MIT Artificial Intelligence Laboratory by Joseph Weizenbaum.”
“Created to demonstrate the superficiality of communication between humans and machines, Eliza simulated conversation by using a “pattern matching” and substitution methodology that gave users an illusion of understanding on the part of the program, but had no built in framework for contextualizing events…. ELIZA was one of the first chatterbots, but was also regarded as one of the first programs capable of passing the Turing Test.” (Wikipedia)
Fictional Voice Assistants
Hal from 2001: A Space Odyssey
WOPR from Wargames 1983
Apple Knowledge Navigator 1987
CUI Interface Timeline
2011: Siri—the first voice-enabled Virtual Assistant
2015: Amazon Echo (Alexa)
2016: Google Home
2018 Google Duplex (Which voice is the AI?) Can read more about Duplex in this article.
2019-20 Amazon Echo Expanding: Echo Show, Echo Auto, Echo Look, Echo Loop—
2023: Google ChatGPT Rival in May | Coming soon ChatGPT-4. The integration of ChatGPT into Microsoft Word. Plug-ins for Figma.
Future Facing Projects
Why Now? What tech breakthroughs?
—Processing Power: Cloud Computing (platforms like Amazon Web Services)
—Natural Language Processing (NLP): a machine’s ability to ingest what is said, break the language down, comprehend language meaning, determine appropriate action, and respond back in language the user will understand. NLP uses machine learning in several forms. One of these forms is Neural Networks that are inspired by biological neural networks in the brain.