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World Congress 2022 • Jun 15, 2022

Hybrid AI: Next Generation Natural Language Processing

Jan Schweiger

Why do 90% of AI projects fail to reach production? Discover how merging deep learning with classical NLP creates explainable, robust search systems that run four times faster.

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#1 about 3 min

Introduction to hybrid AI and production challenges

Why AI projects fail to reach production and how hybrid AI increases efficiency and robustness.

#2 about 2 min

Modern natural language processing using Transformers and deep learning

How Transformer models understand context and intent over simple exact keyword matching.

#3 about 3 min

Fine-tuning public models for domain-specific company search

Transforming paragraphs into vectors enables real-time semantic similarity scoring for specific enterprise domains.

#4 about 3 min

Limitations of neural networks for production search environments

The performance and contextual drawbacks isolated deep learning models exhibit without sufficient training data.

#5 about 2 min

Advantages of classical NLP and keyword search methods

Traditional knowledge graphs and search algorithms provide computational efficiency globally without extensive training data.

#6 about 3 min

Designing highly scalable hybrid AI search engines

Resolving the downsides of isolated paradigms by utilizing infrastructure to seamlessly combine searching methodologies.

#7 about 2 min

Configuring a hybrid search pipeline in Vespa

Running modern and classical algorithms simultaneously in parallel standardizes and sums overall relevance scores.

#8 about 2 min

Performance architecture results for advanced hybrid search

Leveraging lightweight models efficiently mapped with multi-phase sorting layers significantly boosts system query speeds.

#9 about 3 min

Applying hybrid AI to knowledge graphs and safety controls

Visualizing deep learning outputs with manual corrections bridges rule-based safety procedures for hardware applications.

#10 about 1 min

Open-source tooling and libraries for building hybrid NLP

A summary overview of initiating deployments via recommended open-source sentence and language processing packages.

#11 about 3 min

Optimizing model speed and text classification via hybrid AI

Executing text classification acceleration through simpler models effectively maps hybrid workflows to operational endpoints.

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1:48 min

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