Join us for a power-packed night of learning, sharing, and networking at AI Dev Day - New York. 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 by AI startups, panel discussion, and career opportunities.
- 4:30pm~5:30pm: Checkin, food/drink and networking
- 5:30pm~8:00pm: Tech talks, and panel
- 8:00pm: open discussion, mixer
Tech Talk 1: Working with LLMs at Scale
Speaker: Yujian Tang, Developer @Zilliz
Abstract: we’ll introduce LLMs and two main problems they face when it comes to production: high cost and lack of domain knowledge. We then introduce vector databases as a solution to this problem. We cover how a vector database can facilitate data injection and caching through the use of vector embeddings.
Tech Talk 2: Enter the Brave New World of GenAI with Vector Search
Speaker: Mary Grygleski @DataStax
Abstract: We will go over the history and evolution of AI and ML, then look at how it has evolved to where it is today. We will touch upon as many new concepts that have popped up in the last 6-9 months, which include: Generative AI (GenAI), ChatGPT, Large Language Models (LLMs), Natural Language Processing (NLP), Vector DB, and the growing importance of Vector Search. We will also point out the new operational concerns when it comes to managing the life-cycle of a machine learning environment. We will then look at a demo on how Vector Search is being done behind the scenes. We will discuss the benefits of this new wave of technology as well as the challenges that it brings to the industry and the marketplace.
Tech Talk 3: Evaluating LLM Agents
Speaker: Josh Reini, @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
Lightning Talk 1: Towards Effective LLM Observability
Speaker: Sally-Ann Delucia @Arize AI
Abstract: We will discuss how to leverage LLM observability to evaluate LLM responses, pinpoint where to improve with prompt engineering, and identify fine-tuning opportunities.
Lightning Talk 2: Data-in-Motion to Supercharge AI
Speaker: Timothy Spann @Cloudera
Abstract: We will discuss real-time streaming for powering both data ingest and transformation to provide training and enhancement data to models. Also how to use streaming to feed a pipeline of data against your models or models hosted a HuggingFace or elsewhere.
Lightning Talk 3: Developing applications on Generative AI technologies
Speaker: Andrew Hoh @LastMile AI
Abstract: We will discuss the steps necessary (such as prompt engineering, evaluation, data-preparation, tuning/fine-tuning, model serving, and scheduled re-tuning) to go from idea to a production-ready app using a Generative AI (ChatGPT, GPT-4, Claude 2, Palm 2, Stable Diffusion) and get into production.
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
159 West 25th Street 2nd Floor, New York, NY 10001
We will raffle winners for prizes during the event. To enter the lucky draw, "comment" the post on LinkedIn: LinkedIn Post
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 #nyc channel)
Contact us if you are interested in partnership.