Machine Learning and AI
Wasmer is a market leader for enabling WebAssembly on the server. It nearly eliminates all the challenges developers must deal with for deploying machine learning applications in and outside of data center environments.
Challenges
Wasmer is a market leader for enabling WebAssembly on the server. It nearly eliminates all the challenges developers must deal with for deploying machine learning applications in and outside of data center environments.
Model Portability
It is difficult and expensive to collect data or deploy models to heterogeneous infrastructure and devices.
Data Explosion
More devices mean more data must be collected, processed, and incorporated into ML/AI models.
Limited Connectivity
High-speed networks are not always available, or devices may be offline for extended periods.
Limited Power
Training ML/AI models require significant infrastructure resources and power that may not always be available outside data centers.
Security
ML/AI applications on IoT devices are especially susceptible to common security risks like data poisoning or transfer learning attacks where existing trained models are hijacked for malicious intent.
Wasmer Benefits
Ultra-Portability
WebAssembly enables universal binaries, and the Wasmer Runtime ensures ML/AI Wasm apps run on any device.
Small Footprint
Wasmer's headless and architecture-specific compilation options scale down to the more resource-constrained devices.
Performance
Wasmer provides multiple engines and compilers to help developers optimize their deployments for their specific performance requirements.
Security
Isolate server-side WebAssembly from host devices explicitly enabling access only to required components or sensor data.
Wasmer is an open-source runtime for executing WebAssembly on the Server.
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