Artificial Intelligence Reseach Challenges and Industrial opportunities in 2019.

1. http://www.cit.ie
Artificial Intelligence in 2019:
The Good, the Bad and the Ugly
Research challenges and Industrial opprtunities
Dr Haithem Afli
Haithem.afli@cit.ie
@AfliHaithem
INDUSTRIAL INTERNET CONSORTIUM FORUM 2019
Cork, Ireland

2. Artificial intelligence (AI)
Beyond the Hype
Haithem.afli@cit.ie
Ø The Good
Deep Learning state of the art*
Ø The Bad
Malicious AI applications
Ø The Ugly
Challenges in current AI systems
* I will be focusing mainly in some examples of
Natural language Processing and Computer Vision
applications
https://nativevideotube.blogspot.com/

3. The 1956 Dartmouth Conference, the first
Artificial Intelligence Conference
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”Every aspect of learning or any other
feature of intelligence can in principle be so
precisely described that a machine can be
made to simulate it."
John McCarthy

4. Timeline of AI
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Graph from The University Of Queensland Brain Institute
The 1st AI
Winter
The second AI
Winter
Including CIT MSc in AI
https://www.cit.ie/course/CRKARIN9

5. The first AI winter
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By 1964, the National Research Council (NRC)
had become concerned about the lack of progress
and formed the Automatic Language Processing
Advisory Committee (ALPAC) to look into the
problem.
They concluded, in a famous 1966 report, that
machine translation was more expensive, less
accurate and slower than human translation.
After spending some 20 million dollars, the NRC
ended all support.
Image from Wikipedia

6. Haithem.afli@cit.ie
In 1984, John McCarthy criticized expert systems because they lacked common sense
and knowledge about their own limitations.
Schwarz, Director of DARPA ISTO from 1987 to 1989 concluded that AI research has
always had
“… very limited success in particular areas, followed immediately by failure to reach the
broader goal at which these initial successes seem at first to hint…”.
Ø Decrease in funding in AI research.
Ø Many AI companies closed their doors.
Ø The AAAI conference that attracted over 6000
visitors in 1986 quickly decreased to just 2000
by 1991.
The second AI winter

7. The survivors
The Deep Learning God Fathers
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8. Deep Learning Era
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9. 2014: Generative Adversarial
Networks (the Good)
§ The neural network at
the top is the
discriminator, and its task
is to distinguish the
training set’s real
information from the
generator’s creations.
§ In the simplest GAN
structure, the generator
starts with random data
and learns to transform
this noise into
information that matches
the distribution of the
real data.
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Ian Goodfellow

10. Do you know this person?
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11. Hopefully you don’t ..
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https://thispersondoesnotexist.com/

12. 2018: StyleGAN
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13. DeepFake (the Bad)
§ The development of
deepfakes has taken place
to a large extent in two
settings: research at
academic institutions, and
development by amateurs
in online communities.
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14. GAN (the Good)
Applications of GANs
ØGANs for Image Editing
ØUsing GANs for Security
(SSGAN: Secure Steganography Based on GAN)
ØGenerating Data using GANs
ØGANs for Attention Prediction
ØGANs for 3D Object Generation
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15. 2016: Sequence to Sequence
Learning with Attention
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This mechanism allows the
network to refer back to the input
sequence, instead of forcing it to
encode all information into one
fixed-length vector

16. Attending the Unattainable (the ugly)
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17. Challenges in Machine Translation
(the bad)
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18. BERT (the Good)
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BERT makes use of Transformer, an
attention mechanism that learns
contextual relations between words (or
sub-words) in a text.

19. 2019: OpenAI GP2
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20. Haithem.afli@cit.ie
OpenAI GP2 (the Good)

21. OpenAI GP2 (the bad)
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22. Natural Language Processing
(NLP)
Current Applications of NLP and Future Possibilities
§ Address Customer Pain — Monitor Through Sentiment Analysis
§ Gather Market Intelligence — Extract From Unstructured Data
§ Reduce Customer Frustration — Enhance Experience with Hybrid Bots
§ Virtual healthcare assistant
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23. Business Opportunities
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24. Thank you
Haithem.afli@cit.ie
@AfliHaithem
Haithem.afli@cit.ie