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AI Infrastructure - Coggle Diagram
AI Infrastructure
Storage
HDD
SDD
Cloud Storage
Storage Capacity
Training Large Models
Data Retention needs
Intermediate Results
Storage Speeds
Training Time
Real Time applications
Data Preprocessing and Augmentation
Right Balance
Type of AI
Training frequency and duration
Real time application requirements
Cost considerations
Performance needs
Scalability requirements
Security requirements
Strategies for optimization
Data Tiering
Data Compression
Cloud Storage
Data Pipelines
Energy consumption
Model complexity
Training hardware
Training duration
Training optimization
Deployment hardware
Future
Neuromorphic computing
Efficient algorthms
Approaches
Model architecture selection
Data Augmentation
Transfer learning
Early stopping
Efficient training algorthms
Measuring and comparing Processing Power
Clock Speed (GHz)
Cores and Threads
Benchmarks
Cinebench R32
Geekbench
7-Zip
FLOPS
Instruction Sets
Memory Bandwidth
Physical Space
Model complexity
Training vs deployment
Type of hardware
Data center design
High Density Racks
Modular design
Model sizes
Jurassic -1 Jumbo (178B)
WuDao 2.0 (100B)
BLOOM (176B)
ERNIE 3.0 Titan (11B)
Elegia (137B)
Basic building blocks
CPU
Memory
Storage
HDD
SSD
Processing Power
Complex Alogrithms
Matrix calculations
Statistical Calculations
Deep learning
Training and Learning data
Real Time applications
Self driving cars
Speech recognition
Fraud Detection
Communication
Communication Protocol
APIs
Messaging Protocol
Network Infrastructure
LAN
WAN
Cloud storage and Computing
Data Access methods
Structured Data Access
No SQL database
Data Lakes
Network Bandwidth and Latency Impact
Network Bandwidth
Data Transfer
Model distribution
Real Time applications
Model updates and remote access
Latency
Communication overhead
Real time decisions
Remote control and monitoring
Mitigating impact
Network optimization
Data compression
Edge Computing
High Bandwidth networks
Model pruning and quantization
Software Tools
Programming Languages
Python
R
C++
Machine learning Frameworks
TensorFlow
Pytorch
Scikit-Learn
Additional tools
Git
Jupyter notebooks
Data Visualization library
Matplotlib
Seaborn
The Two stages
Compilation
Execution