The document discusses recent trends in artificial intelligence, including Gartner's Hype Cycle for AI technologies and where AI currently stands. It covers neural networks and how they are trained through techniques like backpropagation and stochastic gradient descent. Computer vision applications of AI like image recognition, convolution, max pooling, and autoencoders are described. Recurrent neural networks and LSTMs are discussed in the context of temporal data and prediction. Potential career paths in AI fields like data analytics, user experience, natural language processing, and computer science research are listed. Free online learning resources for AI are provided, and some examples of AI startup companies are mentioned.

1. Recent trends in Technology
ARTIFICIAL
INTELLIGENCE

2. Hype Curve Review
•Gartner’s Hype Curve
•Hype Cycle published in July 2020
•Where does AI stand today?

3. Gartner’s Hype Curve

4. Where AI Stands in the run?
AI has a
bright
future

5. Deeper into AI
•Human Intelligence and
AI
•Neural Network in Play

6. Human Intelligence and AI
Eye (Sensor)
Long-term
Memory
Short-term/
Working
Memory
Image
Recognition

7. Artificial Neuron and Neural Network Training
X1
X2
X3
y
W1
W2
W3
Activation Function:
http://proceedings.mlr.press/v15/glorot11a/glorot11a.pdf

8. Neural Networks

9. Supervised Training

10. Back Propagation From Michael Nielsen
http://neuralnetworksanddeeplearning.com/chap2.html

11. Curse of Dimensionality
For 1000 combinations with 25 Weights
Total combination comes to 10^75. For Sunway
TauhuLight Super Computer in China will be able
To complete the training through brute force by
The time
Gradient Descent
Stochastic Gradient Descent
Andrew Trask on Stochastic Gradient Descent
http://iamtrask.github.io/2015/07/27/python-network-part2/

12. Neural Network in Play - Vision

13. Convolution
0 0 0 0 0 0 0
0 1 0 0 0 1 0
0 0 0 0 0 0 0
0 0 0 1 0 0 0
0 1 0 0 0 1 0
0 0 1 1 1 0 0
0 0 0 0 0 0 0
0 0 1
1 0 0
0 1 1
0 0 0 0 0
0 1 0 0 0
0 0 0 0 0
0 0 0 1 0
0 1 0 0 0
X =
Input Image
Feature Detector
Feature Map
Are we losing information? YES
Are we Unique Feature? No
Feature
By Yann Lecun
http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf

14. Max Pooling
1 1 0
4 2 1
0 2 1
0 1 0 0 0
0 1 1 1 0
1 0 1 2 1
1 4 2 1 0
0 0 1 2 1
Feature Map
Feature Map
Pooled Feature Map
1
1
0
4
2
1
0
2
1
INPUT
TO
ANN

15. Image Recognition
Vision
Reconstructed

16. Dream State
Vision Construction of Image (Auto Encoder) Constructed Image
Construction of Image (Variational Auto Encoder)
Original Reconstructed
Auto-Encoders
https://probablydance.com/2016/04/30/neural-networks-are-impressively-
good-at-compression
Variation Auto encoder
https://worldmodels.github.io

17. Recurrent Network VISUALIZING AND UNDERSTANDING RECURRENT NETWORKS
https://arxiv.org/pdf/1506.02078.pdf

18. LSTM (Memory)
How do we guess the position of the ball ?
Standard RNN
LSTM
Forget Valve
Memory Valve
Output Valve
From Colah
https://colah.github.io/posts/2015-08-Understanding-LSTMs/

19. Predict the action with temporal short
term memory
Julian Vossen
https://www.researchgate.net/publication/325194613_Probabilistic_Forecasting
_of_Household_Electrical_Load_Using_Artificial_Neural_Networks

20. Future of Human Civilization
•Rise of Machine
•Lack of transparency
•Ethical Dilemma

21. Technological Singularity
When machine
becomes smarter
than we are and
starts taking
evolution on their
own.

22. Intent of Using Human Fed
Information!!!!
Corporations
promoting AI in the
consumer level is not
transparent enough
on the end agenda!!!

23. Ethical Dilemma
From the posts in
Social media, AI is
capable of predicting
possible state of
depression within
certain period of time.
Question?? If AI based HR system rejects the
candidate on the basis of possible mental ailment
in future.. Will that be ethical?

24. GO with the FLOW
•Career in AI – Grad Students
•Learning HUB for AI
•Entrepreneurship avenues

25. Career in AI – Grad / Post Grad Students
Data Analytics - Data analysts need to have a solid understanding of the data itself—including
the practices of managing, analyzing, and storing it—as well as the skills needed to effectively
communicate findings through visualization.
User Experience - User experience (UX) roles involve working with products—including those which
incorporate AI—to ensure that consumers understand their function and can easily use them.
Although Edmunds emphasizes that these roles do exist outside of the artificial intelligence sector,
the increased use of AI in technology today has led to a growing need for UX specialists that are
trained in this particular area.
Natural Language Processing - As there are many applications of natural language processing,
the responsibilities of the experts in this field will vary. However, in general, individuals in these roles
will use their complex understanding of both language and technology to develop systems through
which computers can successfully communicate with humans.

26. Career in AI – Grad / Post Grad Students
Computer Science & Artificial Intelligence Research - A computer science and artificial intelligence
researcher’s responsibilities will vary greatly depending on their specialization or their particular role
in the research field. Some may be in charge of advancing the data systems related to AI.
Software Engineering in AI - Software engineers are part of the overall design and development
process of digital programs or systems. In the scope of AI, individuals in these roles are responsible for
developing the technical functionality of the products which utilize machine learning to carry out
a variety of tasks.

27. Learning HUB in AI (Free Courses)
https://www.coursera.org/learn/machine-learning
https://www.youtube.com/user/MIT https://sdsclub.com/

28. Learning HUB in AI (edX.org / coursera.org)

29. Entrepreneurship avenues
AI. Reverie - The company provides synthetic data and vision APIs across industries
like smart cities, defense, retail, Agriculture, and more. It was amongst the Top 25 Machine learning
startups to watch in 2020 by Forbes
Anodot - It is an analytics platform that uses machine learning and artificial intelligence techniques
to constantly analyze and correlate every business parameter, providing real-time alerts and
forecasts using real-time structured metrics data and unstructured log data.
Instreamatic - Instreamatic is an AI-powered Voice Dialogue Marketing platform designed to power
interactive, dialogue-based advertisements on mobile platforms, the company uses natural
language understanding (NLU) for training Voice AI algorithms. It allows media companies and
advertisers to measure, manage, and monetize audio content by utilizing new interactive voice AI
technology
MixMode - Mixmode is an AI-driven cybersecurity startup company, earning a finalist award in
2018 and 2019 for “Best Computer Forensic Solution.

30. Platform is Set…. What is our destination?