What we've learned
The future of Language and Computers
Your future in NLP
"Hey Siri, how long to drive to work?"
"Hey Siri, how long to drive to work?"
"Hey Siri, how long to drive to work?"
"Hey Siri, how long to drive to work?"
"Hey Siri, how long to drive to work?"
"Hey Siri, how long to drive to work?"
"Hey Siri, how long to drive to work?"
"Hey Siri, how long to drive to work?"
We need ARGM-TMP of 'drive' when ARGM-GOL == 'work'
ARG0-PAG == $USER
$USERLOC == getlocation($DEVICE)
ARGM-GOL == $WORKLOC == 9500 Gilman Drive 92093
"Get ($TRAFFICSTATUS,$DRIVETIME,$DRIVEROUTE) for navigate($USERLOC,$WORKLOC,car)"
Traffic to $ARGM-GOL is $TRAFFICSTATUS, so it should take $DRIVETIME minutes via $DRIVEROUTE
"Hey Siri, how long to drive to work?" "Traffic to work is light, so it should take 10 minutes via Voigt drive"
"Hey Siri, how long to drive to work?" "Traffic to work is light, so it should take 10 minutes via Voigt drive"
Improved ASR accuracy
Improved TTS quality
Better automatic parsing and POS tagging
Improvements to Lexical Resources
Richer semantic parses
Duplication and expansion of existing resources for other world languages
Attempts at offering such a service to signed language users
Improved NLP and Virtual Assistant resources for less wealthy languages
Less of a 'happy path' effect
Improved ability to handle a greater diversity of phrasings of existing commands
Improved ability to handle a wider diversity of voices and accents
Improved ability to cope with subadjacency constructions
Improved conversational repair
Improved ability to interact with a wider number of systems
Improved integration with existing systems
More 'skills' to accomplish more tasks
This tech can be very good, but also very bad
We need to worry a bit about how to prevent incomplete AI from hurting people
Offline functionality for ASR and TTS and basic question-answering
Enhanced privacy protections, allowing deeper learning with little trouble
Improvements to wake-word technology allowing even more fluid access and lower idle power consumption
Increased ubiquity at decreased cost
Ability to refer to visual data
"What's that over there?"
Leveraging existing sensor meshes
We are all vats of brain matter sitting in a dark hole surrounded by bone
We build our understanding from a mesh of sensor data
The 'real world' is just inference from input data
Improved personalized knowledge to enhance inference on real-world topics
Improved discourse context, to allow this to feel more like a 'relationship'
Improved understanding of the person's actual life
"The next bus will arrive at Gilman and Eucalyptus in 10 minutes. I'll text Jessica and tell her you're on your way."
"It's time to leave for the airport. I've called a Lyft. Don't forget your passport and glasses, leave your pocketknife at home, and make sure to take your good razor out of your toiletry bag if you're using a carry-on."
"Hey, it's time to see the Dentist. Dr. Pradhan's got availability next Tuesday at 2pm, and so do you. Should I confirm?"
"It's Valentine's Day next week. You should remember to grab a card for Jessica. Would you like me to order some dark red roses?"
Long term knowledge of preferences and desires
Better knowledge of the people, places, and things in the user's life
Improved conversational latency
More natural-feeling conversation
Once we have the basics down, we can make these conversations more natural
Changes to dialect, word choice, etc
More conversational paths and approaches
Less 'wooden' interactions
General Artificial Intelligence may solve many of these problems
Even an artificial idiot solves many of them
AI comes with its own difficulties
... but the simple fact is ...
Improved machine learning
Improved resource efficiency
Better Digital Signal Processing
Better knowledge representations
Better understanding of speech
Better language modeling
Better models of semantics and semantic inference
LIGN 101 (Intro to Linguistics)
LIGN 110 (Articulatory Phonetics)
LIGN 121 (Syntax)
LIGN 130 (Semantics)
LIGN 17 (Making and Breaking Codes)
LIGN 165 (Computational Linguistics)
LIGN 167 (Deep Learning for Natural Language Understanding)
LIGN 168 (Computational Speech Processing)
... and lots of grad classes, coming soon!
Focuses on data-driven problems and work throughout the social sciences
NLP is a part of it, but there's lots more!
Academia and Research
Government
Industry
First, we had keyboards
Then, mice changed everything