The document discusses the various aspects of machine learning, including communication channels and the types of technologies involved. It highlights the importance of big data and advanced computing power, particularly through innovations like Google’s Tensor Processing Units (TPUs). Additionally, it notes potential pitfalls in hardware design and references a research presentation by several authors.

1. EMPOWERING
THE
MACHINE
LEARNING
REVOLUTION

2. Communications
 Communication theory states that
communication involves a sender and a
receiver (or receivers) conveying
information through a communication
channel.

3. Human2Human
Technologies:
 Telephone
 Mobile

4. Human2Machine
Technologies:
 TV Remote Control
 Remote Car locking

5. Machine2Machine
Technologies:
 Thermostat
 Motion Sensor light

6. Why Machine Learning Now

7.  Big Data
One of the important reasons is the
volume of available data. Terabyte-
sized Big Data can be easily
accessed with few clicks.
 Computing Power
The second reason is the advanced
computing power, especially
using Graphics Processing Unit
(GPU). GPU is a
specialized electronic
circuit designed to rapidly
manipulate and alter memory to
accelerate the creation of images in
a frame buffer.

8. Google Tensor Processing Unit(TPU)
 A tensor processing unit (TPU) is an AI accelerator
application-specific integrated circuit (ASIC)
developed by Google specifically for neural network
machine learning.
 1st Generation
 The tensor processing unit was announced in 2016
at Google I/O.The chip has been specifically
designed for Google's Tensor Flow framework, a
symbolic math library which is used for machine
learning applications such as neural networks.

9.  2nd Generation
 The second generation TPU was
announced in May 2017.Google stated
the first generation TPU design was
memory bandwidth limited, and using 16
GB of High Bandwidth Memory, In the
second generation design increased
bandwidth to 600GB/s and performance
to 45 TFLOPS.

11. Pitfalls Of Machine Learning
 Designing
hardware
using last
year’s
models.

12. Video

13. Presentation on Research Paper Made
by
 Rabbia Nasir
 Erum Shammim
 Ifra Batool
 Sara Khalique
 Laiba Jamil
 Yusra Raees