Layla El Asri is a research Scientist at Maluuba. Her work explores artificial intelligence in the context of language understanding, dialogue and human-machine interaction. Layla leads a team seeking to build artificial intelligence systems that are knowledgeable and can exchange information with users to help users accomplish tasks or gain knowledge. Layla completed her PhD at Université de Lorraine in France.
Abstract Summary:
Teaching AI To Make Decisions and Communicate:
Many advances have been made in the area of artificial intelligence, with the goal of building agents that understand how they can interact with their environments, reason and solve complex tasks, and communicate their findings to humans. In this talk, I will focus on efficient decision-making and communication. For decision-making, I will present some work on building an efficient representation of the environment and breaking down tasks into generalizable subtasks. For communication, I will focus on dialogue through natural language and present some of our work in this area.
Unraveling Multimodality with Large Language Models.pdf
Layla El Asri, Research Scientist, Maluuba
1. A Microsoft company
Teaching AI to Make Decisions
and Communicate
Layla El Asri, Research Manager
with slides by Paul Gray, Harm Van Seijen, and Adam Trischler
2. Maluuba, a Microsoft company
Maluuba’s Vision: Solving AGI by Creating
Literate Machines
Machine Reading
Comprehension
Teaching artificial agents to read
and understand natural language
Advanced Conversational
Systems
Building knowledgeable systems
that can exchange information
with users to help users
accomplish tasks or gain
knowledge
Reinforcement Learning
Fundamental research in
scalability of Reinforcement
Learning to allow machines to
perform complex tasks in the
real world
3. Maluuba, a Microsoft company
Teaching AI to Make Decisions and
Communicate
• Expectations of AI
• Learning to Learn
• Learning to Perceive
• Learning to Communicate
4. Maluuba, a Microsoft company
Expectations of AI
Nice, thanks
When is my appointment with Marc?
You have a meeting with Marc Villeneuve
tomorrow at 10am.
Ok, where is it again?
At Starbucks on Maisonneuve and
Montagne so you should leave the office
at 9:40.
Ok is it the same Starbucks when I met
Harry last week?
Yes
I see. Do you know what Marc’s been up
to lately?
Yes, there was an article on MIT Tech
review yesterday. His company will start
commercializing affordable 3d printers.
Learning to
Communicate
Learning to
Learn
Learning to Perceive
5. Maluuba, a Microsoft company
Learning to Learn
• Human beings decompose
tasks into subtasks in an
efficient way.
• Subtasks are achieved
without conscious
awareness.
6. Maluuba, a Microsoft company
Learning to Learn: Separation of
Concerns
• Separation between performance metric and
learning objective.
• Each agent has its own learning objective.
• The goal is to find a reasonable policy efficiently.
8. Maluuba, a Microsoft company
Collecting the fruits
Goal
Get all fruits as quickly as
possible
Reward
+1 if all fruits are eaten
0 otherwise
Number of fruits: n
State space: 100x100n = 102n + n
NP-complete problem
Using one agent per fruit
State space reduced to nx100
9. Maluuba, a Microsoft company
Pac-Boy
Reward
+1 for eating a fruit
-10 for each collision with
a ghost
The episode ends after all
fruits are eaten or after
300 time steps.
State space
Approximately 1028
states
10. Maluuba, a Microsoft company
Configuration
1 agent per fruit
1 agent per ghost
75 fruit agents with 76 states
2 ghost agents with 76x76 states
13. Maluuba, a Microsoft company
Learning to
Perceive
• For living creatures,
perception is adapted to task
achievement
• First living creatures: ability to
react
• Evolution: ability to foresee
• Challenge: correlate sensory
inputs with events
• Modern human beings: ability
to focus
14. Maluuba, a Microsoft company
Learning to Perceive: Information
Gathering
Guessing Game tasks that progress in difficulty
• Battleship – sink the enemy’s ships
quickly
• Hangman – guess the phrase quickly
• Blockworld
We developed a model that achieves super-
human performance on these tasks.
15. Maluuba, a Microsoft company
Blockworld
Environmen
t
Observation
s
Model’s World
Belief
Peeking
Policy
Model’s Answer Belief
Is the red sphere above the red cross?
17. Maluuba, a Microsoft company
Learning to
Communicate
• Language is the most
precise communication tool
that we have
• … but it is still very
imprecise
• Easier to give orders and
strictly define the meaning
of words
18. Maluuba, a Microsoft company
How to Build a Goal-Driven
Dialogue System?
Inform(city = Rio)
State tracker
Natural Language
Understanding
(NLU)
Natural Language
Generation
(NLG)
Dialogue
Management
(DM)
City = Rio, budget =
$2000, hotel =
Hilton, price =
$1950
Database
city = Rio, budget = $2000 Hotel = Hilton, price =
$1950
Offer(name =
Hilton, price =
$1950)
“You can book the
Hilton for $1950.”
“I want to go to Rio.”
20. Maluuba, a Microsoft company
Frames Dataset Overview
15
Turns per
Dialogue
268 Hotels
109
Cities
19,986
Turns
1369
Dialogues
21. Maluuba, a Microsoft company
Frame Tracking
Curitiba, August
15th – August
26th, 4 stars,
$2877.68
Columbus,
August 15th,
Request(price)
“And how much if I were to go to
Columbus?”
Curitiba, August
15th
Curitiba, August
15th
Curitiba, August
15th – August
26th, 4 stars,
$2877.68
Curitiba, August
15th
“And how much if I were to go to
Columbus?”
Columbus,
August 15th,
Request(price)
State Tracking
Frame Tracking
22. Maluuba, a Microsoft company
Frame Tracking Model
Input
The NLU labels, the list of frames,
the previous active frame, and the
user utterance
Output
The current active frame and the
frames referred by the dialogue
acts
Model
23. Maluuba, a Microsoft company
Thank you!
Papers discussed
• Improving Scalability of Reinforcement Learning by Separation of Concerns
• Towards Information-Seeking Agents
• Frames: A Corpus For Adding Memory To Goal-Oriented Dialogue Systems
24. Maluuba, a Microsoft company
We’re hiring!
• Research Scientists
• Research Engineers
• Developers
• Product/Program Managers
www.maluuba.com/careers
Editor's Notes
I’m Layla from Maluuba. Our vision is to solve artificial general intelligence by creating machines that can read, think and communicate like humans.
We started in 2011 and operate a deep and reinforcement learning lab in Montreal.
In January, Maluuba was acquired by Microsoft.
Our work focuses on three areas
MRC / Dialogue / RL (quick intro for each)