Luminoso BDAT 10.17 Transfer Learning · Transfer Learning How new technology is enabling Natural Language Understanding for multilingual text, domain jargon, and slang. Dr. Catherine

Transfer LearningHow new technology is enabling Natural Language

Understanding for multilingual text, domain jargon, and slang.

Dr. Catherine Havasi, LuminosoIlluminate the unknown in your data

www.luminoso.com

Artificial intelligence seems poised to change every aspect of our world.

Illuminate the unknown in your datawww.luminoso.com

The future of user interfaces is

conversational.

Siri and other systems have opened the

door.


Advances have transformed language understanding.

1960sPattern Matching

& Keywords

1990sRule Sets & Ontologies

2000sUnsupervised

ML (Bayes)Word Embeddings(“Deep Learning”)

2010s

Illuminate the unknown in your datawww.luminoso.comPhoto by: Wing-Chi Poon CC BY-SA 2.5.

Photo by: Johnny One Speed, CC BY-SA 3.0.


Accenture projects that the market value of the artificial intelligence industry will

rise to $2.1 trillion in Japan by 2035.

Accomplishments of deep learning systems have shown the business and end users the power and ease of automation that artificial intelligence can

bring.


Deep learning focuses on finding patterns in its input data

at a sophistication and scale that hasn’t been done before.

Photo by: Steve Evans CC BY-SA 3.0.


In 2013, Google popularized a type of machine learning called word embeddings that applied the power of deep

learning to natural language understanding.

Photo by: Steve Evans CC BY-SA 3.0.


Could this be the keyto language understanding?

Photo by: Petar Milošević CC BY-SA 3.0.


For natural language understanding to be successful, it must be:

Multilingual &Global

Explainable Unbiased &Ethical

Adaptable Automated


The flaw in deep learning is that it requires more data, time, and compute than is

practical in most circumstances.


Training a deep learning system can take

hundreds of millions or billionsof points of data.

Photo by: Karl E. Jorgensen CC BY-SA 3.0.


This data is needed because the model must learn from scratch each time it learns anything.

This isn’t how people work.

Photo by: Carl Hoffman


Imagine understanding the way the public & experts tasters talk about chocolate.

Photo by: leasqueaky CC BY-SA 3.0.


There would not be enough data for a deep learning system to understand chocolate.

This is worse for financial services, healthcare, and other jargon-heavy fields.

Photo by: Anna Dziubinska CC BY-SA 3.0.


Transfer learning helps apply what they learned in one context

to another context.

Photo by: Bill Evans/United States Air Force Academy.


“Transfer learning will be … the next driver of

ML commercial success.”

– Andrew Ng 2016


Transfer learning is what powers the app on your phone that makes it look like your cat

was painted by Picasso.

Photo by: Gene KoganIlluminate the unknown in your data

www.luminoso.com

Photo by: Chris Rodley


Or imagining what would happen if a book of dinosaurs was painted with flowers

instead of scales.

Transfer learning helps self-driving cars learn from simulation or generalize from

dangerous situations.

Photo by: Google Research Blog


We’ve used transfer learning to help computers understand under-

resourced languages.

Illuminate the unknown in your datawww.luminoso.comPhoto by: Koenders VrkiezingCC BY-SA 3.0.

It’s beginning to work for voice and video…


Photo by: UniversityofErlangen-Nuremberg

And its future implications are unpredictable!

Why does domain specificity matter for business?

Photo by: Steve Hobson CC BY-SA 3.0.


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CPG: Colors Matter

CASE STUDY

Finding the right color of a consumer toiletry product drove sales and customer brand loyalty –

even for men.

Photo by: leasqueaky CC BY-SA 4.0.


Technology: Language of Gaming

CASE STUDY Learning the ever-changing

language of online gaming

enables prioritization of bug fixes in new

releases.

Photo by: Tore Saetre CC BY-SA 4.0.


What do we do at Luminoso?

27Illuminate the unknown in your data

www.luminoso.com

We are transforming the contact center using our experience with transfer learning in the

enterprise.

Photo by: MAV Zrt CC BY-SA 3.0.Illuminate the unknown in your data

www.luminoso.com

We work in the technology/mobile, consumer finance, retail, and marketing verticals.


Photo by: Colin CC BY-SA 3.0.

We can automate discovering the reasons people call a contact center with 80-90% alignment with people…

…in 15 minutes instead of 4 months.

Illuminate the unknown in your datawww.luminoso.comPhoto by: Erika Aya Eiffel CC BY-SA 3.0.

We have built building models of how people think about the world in 70 languages – called ConceptNet.

Luminoso’s machine learning lets computers not start from scratch and bring a digital intuition of ConceptNet to natural

language understanding.


We’ve been using transfer learning in production for seven years to help brands and agencies do better market research.


Transfer learning is often referred to as “emerging technology”.

Photo by: Tommy Tang CC-BY-SA 3.0.

Our transfer learning is so accurate, it can outperform Facebook’s Spanish deep

learning model with no Spanish training data.

Photo by: Sanbernar CC BY-SA 3.0.


(This claim is externally verified.)

Our software works natively in Japanese. We also do Chinese, Korean, and ten additional languages.

Photo by: Aotearoa CC BY-SA 3.0.



Thank you so much for listening to my talk!

[email protected]

I’m here with my colleagues who would love to talk to you about your business problems or about machine learning on

Japanese text!

Photo by: Lisa TancsicsCC BY-SA 3.0.


Documents

Luminoso BDAT 10.17 Transfer Learning · Transfer Learning How new technology is enabling Natural Language Understanding for multilingual text, domain jargon, and slang. Dr. Catherine