David Ferrucci is best-known as the researcher who led the team that developed IBM's Watson, which beat the best human players of Jeopardy in 2011. He left IBM a year later and formed his own company, Elemental Cognition, in 2015. Elemental cognition is taking a hybrid approach, combining aspects of machine learning and symbolic computation.
Elemental Cognition has recently developed a system that helps people plan and book round-the-world airline tickets:
The round-the-world ticket is a project for oneworld, an alliance of 13 airlines including American Airlines, British Airways, Qantas, Cathay Pacific and Japan Airlines. Its round-the-world tickets can have up to 16 different flights with stops of varying lengths over the course of a year.
Elemental Cognition supplies the technology behind a trip-planning intelligent agent on oneworld’s website. It was developed over the past year and introduced in April.
The user sees a global route map on the left and a chatbot dialogue begins on the right. A traveler starting from New York types in the desired locations — say, London, Rome and Tokyo. “OK,” replies the chatbot, “I have added London, Rome and Tokyo to the itinerary.”
Then, the customer wants to make changes — “add Paris before London,” and “replace Rome with Berlin.” That goes smoothly, too, before the system moves on to travel times and lengths of stays in each city.
Rob Gurney, chief executive of oneworld, is a former Qantas and British Airways executive familiar with the challenges of online travel planning and booking. Most chatbots are rigid systems that often repeat canned answers or make irrelevant suggestions, a frustrating “spiral of misery.”
Instead, Mr. Gurney said, the Elemental Cognition technology delivers a problem-solving dialogue on the fly. The rates of completing an itinerary online are three to four times higher than without the company’s software.
Elemental Cognition has developed an approach that all-but eliminates the hand-coding typcial of symbolic A.I.:
For example, the rules and options for a global airline ticket are spelled out in many pages of documents, which are scanned.
Dr. Ferrucci and his team use machine learning algorithms to convert them into suggested statements in a form a computer can interpret. Those statements can be facts, concepts, rules or relationships: Qantas is an airline, for example. When a person says “go to” a city, that means add a flight to that city. If a traveler adds four more destinations, that adds a certain amount to the cost of the ticket.
In training the round-the-world ticket assistant, an airline expert reviews the computer-generated statements, as a final check. The process eliminates most of the need for hand coding knowledge into a computer, a crippling handicap of the old expert systems.
There's more at the link.
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Lex Fridman interviews David Ferrucci (2019).
0:00 - Introduction
1:06 - Biological vs computer systems
8:03 - What is intelligence?
31:49 - Knowledge frameworks
52:02 - IBM Watson winning Jeopardy
1:24:21 - Watson vs human difference in approach
1:27:52 - Q&A vs dialogue
1:35:22 - Humor
1:41:33 - Good test of intelligence
1:46:36 - AlphaZero, AlphaStar accomplishments
1:51:29 - Explainability, induction, deduction in medical diagnosis
1:59:34 - Grand challenges
2:04:03 - Consciousness
2:08:26 - Timeline for AGI
2:13:55 - Embodied AI
2:17:07 - Love and companionship
2:18:06 - Concerns about AI
2:21:56 - Discussion with AGI
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