Practical AI Serving deep learning models with RedisAI
Aug 12, 2019
Pieter Cailliau, a Senior Product Manager at Redis Labs, dives into the world of RedisAI and its groundbreaking applications. He explains how RedisAI integrates deep learning models into the Redis ecosystem, enhancing AI deployment efficiency. The discussion also covers Redis's versatility as an open-source database and shares insights on using RedisAI for chatbot conversation management and dynamic knowledge graphs. Pieter emphasizes community involvement in developing RedisAI, inviting developers to contribute and collaborate for future advancements.
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Pieter's Journey to Redis
- Pieter Cailliau's interest in astronomy led him to electromechanical and computer science engineering.
- His work on map quality at TomTom introduced him to NoSQL databases like Neo4j and Redis.
Redis: Beyond Key-Value Store
- Redis is an in-memory key-value store offering various data types beyond strings, unlike Memcache.
- It supports diverse data structures with corresponding commands and fits within the broader NoSQL database landscape.
Redis Set Operations
- Redis handles sets with commands like intersection and union, reflecting its data structure approach.
- This allows efficient querying, as demonstrated by intersecting product tag sets.