From this track
Designing AI Agents with System Thinking
Wednesday Oct 4 / 10:35AM PDT
AI agents are a perfect fit for serverless environments, as they can leverage the power of the cloud and the edge for fast and accurate decision making. It is often the case that AI applications do not require the costly vector database and compute solutions which are often used today, to s
Logan Grasby
Founder @Azule.ai
Can’t Apps and Databases All Just Get Along?
Wednesday Oct 4 / 11:45AM PDT
Availability is a tricky thing. In order for your tier 0 endpoints to be available all their hard dependencies have to be available. For Stytch that means basically network, compute, database, and messaging providers.
Joshua Hight
Software Engineer @Stytch
Introduction to Real-Time Training and Scoring in AI/ML
Wednesday Oct 4 / 01:35PM PDT
In the rapidly evolving landscape of AI/ML, the shift from batch to real-time data processing is significant. It impacts how quickly and dynamically we can learn from data, leading to more responsive AI applications.
Wes Wagner
Solutions Engineer @Redpanda
Simple Platform Engineering and Simply High Cardinality Observability
Wednesday Oct 4 / 02:45PM PDT
Platform engineering transforms repetitive Engineering requirements into standardised and dependable services, or "paved roads". These paved roads offer engineering teams a smooth way to develop and deploy business logic layers continuously.
Piyush Verma
Co-Founder and CTO @Last9
LLMs + Knowledge Graphs = Better Together
Wednesday Oct 4 / 03:55PM PDT
LLMs are often like the know-it-all at a bar - they can quickly and confidently produce realistic sounding answers to just about any question - even if the answers are complete fabrications.
Mark Quinsland
Senior Field Engineer @Neo4j
