1. Ovonic Cognitive Computer, LLC formed 9/26/2002
Stan Ovshinsky Helmutt Fritsche Morel Cohen Dave Strand
Guy Wicker Boil Pashmakov Pat Klersy Robert Miller

2. The problem with computers
Memory
Processor
Data
Transmission
Processor is too slow
Memory access is too slow
Not enough memory

3. Memory Heirarchy gives unlimited Memory, but leads to “bottlenecks”
Processor
Cache
DRAM
SSD
NAND
HDD
cloud
slow
10 nanoseconds nanoseconds millisecond second second
128 Megabytes Gigabytes Gigabytes terrabytes infinity
Obfuscation
of origin
3DXpoint bridges the gap between DRAM and SSD

4. 3DXpoint is Ovonic Threshold and Memory switches connected
ECD 1970
3D version
ECD 1987

5. 3DXpoint solves the “bottleneck”, speeding up access 10 to 100X
But processors are still too slow
Memory
Processor
Data
Transmission
GPU
Data
Transmission
Graphics processors are now widely employed to speed large,
data intensive operations

6. Graphics Processors are 100X faster than normal microprocessors
But they require more data transmission and more memory
Nvidia Jetson TX2 GPU $600
Connect 6 video cameras to it
and it can drive a car unaided.
It can do 1.2 trillion calculations
per second

7. GPUs drive cars, recognize any human language, and analyze huge
amounts of data using ~1000X1000X8 Neural Network emulation
They emulate the function of a neuron in a network of neurons.
It takes an enormous amount of calculation to model each neuron
and sequentially calculate the entire network.
The Ovonic Cognitive Computer elements have similar function
to a neuron. They don’t emulate neural networks, they actually are
Neural networks.

8. Output fires when the threshold is reached by summing the inputs
Neurosynaptic Cell
Ovonic Single and Multiple Cells have the same properties as neurons and biological cells
Dendrites
Output fires when the threshold is reached by summing the inputs
Nucleus
Axon
Inputs saturate with a sigmoidal response
Neural Network computing
Uses a nerve-like connected array of elements with saturating, weighted inputs and outputs when a threshold is reached

9. Ovonic switches can implement a Physical Neural Network
Ovonic Threshold Device
Ovonic Memory Device
Switching in chalcogenide materials based on lone-pair excitation:
Threshold noncrystallizing OTS
Memory phase change OMS
The voltage and current characteristics can be tailored for the requirements of the application
This is the only practical device that works. RRAMs, Memristors
and quantum computing devices are being researched. Ovonic
devices are now commercial products.

10. Ovonic Memory Multi-State Data Storage
PROGRAMMING VOLTAGE (V)
DEVICE RESISTANCE (Ohms)
For Storage:
Multiple bits per cell increases storage density and reduces cost
For Processing:
The analog characteristic provides ideal means for synaptic weighting

11. Ovonic Multi-Terminal Threshold Device
This simplifies control in a synaptic environment

12. The Ovonic Cognitive Computer
Conventional Silicon Computers
Each Element:
Computes based on
single bit (binary)
manipulation
Manipulates data
sequentially, bit by
bit
Ovonic Cognitive Computer
Manipulates, processes and stores information in a non-
volatile radiation hard and multilevel manner
Hardware and software are unified
Low voltage and low current operation
Performs arithmetic operations (+,-,x, ) on multi-bit numbers
(0,1,2,3…n)
Performs modular arithmetic
Combines logic and memory in a single device
Executes multi-valued logic
Stores the result in a non-volatile manner
Simple, powerful encryption
Acts as a neurosynaptic cell; i.e. possesses intelligence
capability
Scales down to angstrom scale dimensions; huge density
Device speed in the picosecond range
Capable of massive parallelism; also addressing different
values

13. Ovonic Cognitive Device Operation

14. Well over 1000 startups are pursuing cognition with >$20B invested

15. September 10 - 16, 2017 Aachen, Germany
2016
2011