Snips NLU An Open Source, Private by Design alternative to NLU cloud services

@adrien_ball, Senior Machine Learning Engineer

Wakeword Speech to text Natural Language Understanding

Speech to text Natural Language Understanding

“What will be the weather in Paris

tomorrow evening?”

{ "intent": { "intentName": "searchWeatherForecast", "probability": 0.95 }, "slots": [ { "value": “Paris", "entity": "locality", "slotName": "forecastLocality" }, { "value": { "kind": "InstantTime", "value": "2018-04-19 19:00:00 +00:00" }, "entity": "snips/datetime", "slotName": "forecastDatetime" } ] }

Natural Language Understanding

Why Snips NLU?

Data Privacy

Q. Are voice and text inputs processed by Amazon Lex stored, and how are they used by AWS?

Amazon Lex may store and use voice and text inputs processed by the service solely to provide and maintain the service and to improve and develop the quality of Amazon Lex and other Amazon machine-learning/artificial-intelligence technologies. Use of your content is necessary for continuous improvement of your Amazon Lex customer experience, including the development and training of related technologies.(…)

https://aws.amazon.com/lex/faqs/#data-privacy

AI logic developper code

NLU cloud

NLU cloud

AI logic developper code

NLU cloud as backendNLU cloud as frontend

NLU CLOUD SOLUTIONS + ALTERNATIVES

AI logic developper code

On premises NLU

AI logic developper code

NLU cloud

NLU cloud

AI logic developper code

NLU cloud as backendNLU cloud as frontend

NLU CLOUD SOLUTIONS + ALTERNATIVES

AI logic developper code

On premises NLU Embedded NLU

snips-nluPython library

Training + Inference

Apache 2

snips-nlu-rs Snips consoleRust library

Inference

Apache 2 / MIT

https://console.snips.ai

Training

Self service / Professional services

Snips NLU ecosystem

• deterministic behavior

• great generalization power

Objectives & Constraints

• rapid prototyping

• fast & lightweight

• portability

• extensibility

snips-nlu• Rapid prototyping

• Rapid debugging

• ML ecosystem

snips-nlu-rs

• Speed

• Portability

Python / Rust complementarity

snips-nlu• Rapid prototyping

• Rapid debugging

• ML ecosystem

snips-nlu-rs

• Speed

• Portability

Python / Rust complementarity

JSON serialization

🤔 Speed?

Accuracy?

Snips NLU inference time

🤔 Speed?

🤔 Accuracy?

Extension of Evaluating Natural Language Understanding Services for Conversational Question Answering Systems

NLU cloud frontend

NLU cloud backend

On premises NLU

Embedded NLU

Privacy

Speed 2 roundtrips 2 roundtrips 1 roundtrip Few milliseconds

Accuracy State of the art State of the art State of the art State of the art

https://github.com/snipsco/snips-nlu

Willing to integrate Snips NLU?

Want to join the Snips team?

Questions?

adrien.ball@snips.ai@adrien_ball

https://medium.com/snips-ai