AI Dev Day - San Francisco

Pre-registration is required for admission: https://www.aicamp.ai/event/eventdetails/W2023091217
(Venue security may not let you in if you don't pre-register at the link above)

Description:
Join us for a power-packed night of learning, sharing, and networking at AI Dev Day - Silicon Valley. We are excited to bring the AI developer community together to learn and discuss the latest trends, practical experiences, and best practices in the field of AI, LLMs, generative AI, and machine learning.

In addition to the tech talks, there will be plenty of opportunities to network with AI developers, live demos, AI community showcases, panel discussion, and career opportunities.

Agenda (PDT):
- 4:30pm~5:30pm: Checkin, food/drink and networking
- 5:30pm~7:30pm: keynotes, tech talks, and panel
- 7:30pm: open discussion and mixer
- 8:00pm: close & heading to bar.

Tech Talk 1: From Generic To Genius: Personalize Generative AI
Speaker: Ryan Michael, VP of Engineering @Kaskada
Abstract: Generative AI has already demonstrated immense value, but systems like ChatGPT don’t know anything about who we are as individuals. At Kaskada, we have developed a compute engine to help LLM’s understand who they’re talking to and what they’re talking about. Kaskada does this by augmenting prompts with real-time contextual information and making it easy to recreate the context of past prompts, significantly accelerating the prompt engineering process. In this talk, we introduce the abstraction that makes this possible: the concept of timelines. Timelines can be interpreted as a history of changes or as snapshots at specific time points.

Tech Talk 2: Building a Petabyte-Scale Vector Store: Powering Future AGI
Speaker: Preethi Srinivasan @Astra Vector DB
Abstract: This talk will focus on the work in the Apache Cassandra® project to develop a vector store capable of handling petabytes of data, discussing why this capacity is critical for future AI applications. I will also connect how this pertains to the exciting new generation of AI technologies like Improved Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Forward-Looking Active Retrieval Augmented Generation (FLARE) that all contribute to the growing need for such scalable solutions. Finally, we’ll discuss the importance of planning for future scalability and how to effectively manage AI agents in this new age of data.

Tech Talk 3: Evaluating LLM Agents
Speaker: Shayak Sen @TruEra
Abstract: In a LLM-powered autonomous agent system, LLM functions as the agent’s brain by using planning and inference to decide what tools to use and how. As requests to your agent drift, evaluation is needed to identify gaps in tool coverage and keep the agent performing. This talk will cover the basics of building an LLM agent and how to evaluate it with open-source TruLens

Stay tuned as we are updating speakers and schedules.
If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors:
GitHub, DataStax, TruEra

Community on Slack
- Event chat: chat and connect with speakers and attendees
- Sharing blogs, events, job openings, projects collaborations
Join Slack (search and join the #sanfrancisco channel)