The Benefits of HeatWave Generative AI
summary
HeatWave claims to embed in-database LLMs plus an automated vector store so documents and Lakehouse data are converted to embeddings, searched, and used for retrieval-augmented generation without leaving the database. Customers across a dozen industries use AutoML recommendation engines plus GenAI — a food-delivery app generates menu summaries — and one customer moves from idea to production in one month to production using three or four lines of code. Data stays inside HeatWave for security and Oracle manages provisioning to cut cost.
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chapters (11)
- 0:00HeatWave GenAI intro
- 0:25What is HeatWave GenAI
- 1:30In-database large language models
- 3:21Vector store automation
- 5:47Simplicity and cost savings
- 6:30Customer response
- 7:34Real-world use cases
- 8:38HeatWave GenAI on AWS
- 10:03Oracle multi-cloud
- 10:46HeatWave innovations
- 11:49Where to learn more
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