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

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

Memory Heirarchy gives unlimited Memory, but leads to “bottlenecks” Processor Cache DRAM SSD NAND HDD cloud slow 10 nanoseconds 60 nanoseconds 1 millisecond 1 second 10-100 second 128 Megabytes 8 Gigabytes 512 Gigabytes 10 terrabytes infinity Obfuscation of origin 3DXpoint bridges the gap between DRAM and SSD

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

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

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

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.

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

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.

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

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

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

Ovonic Cognitive Device Operation

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

September 10 - 16, 2017 Aachen, Germany 2016 2011