Welcome to the monthly in-person AI meetup in Toronto, in collaboration with Agnostiq. Join us for deep dive tech talks on AI, GenAI, LLMs and machine learning, food/drink, networking with speakers and fellow developers.

Agenda:
* 5:00pm~6:00pm: Checkin, Food/drink and networking
* 6:00pm~8:00pm: Tech talks and Q&A
* 8:00pm~9:00pm: Open discussion and Mixer

Tech Talk: Navigating Cloud-Based Challenges in Generative AI Workflows and beyond
Speaker: Ara Ghukasyan @Agnostiq
Abstract: As the technological landscape shifts towards more compute-intensive operations, challenges in resource allocation, scalability, and cost are becoming more pronounced. Traditional orchestration tools, designed for myriad low-compute operations, fall short in managing specialized resources like GPUs, especially when transitioning from local to cloud-based environments. This important transition can be cumbersome in itself, requiring time-consuming code changes and reconfiguration. A capable orchestration framework is therefore essential in this setting, where the scarcity of specialized compute resources exacerbates existing challenges. Using a Generative AI model to illustrate the example, this tutorial introduces a unified approach for designing, dispatching, and monitoring cloud-based workflows in a cost- and time-efficient manner.

Tech Talk: Communication Channels of AI Explanations
Speaker: Zining Zhu @Stevens Institute of Technology
Abstract: As generative AI Technologies are deployed in our daily lives, the communication between AI and human users become more important than ever before. Here I present a communication channel framework, where AI as assistants can help humans process complex data and understand automatic prediction results. This framework uses information theory to reveal the mechanisms of the AI-generated explanations, and incorporates the audience to tailor the contents and the formats

Tech Talk: RAG Opportunities and Challenges
Speaker: Suhas Pai @Hudson Labs
Abstract: Adoption of LLMs in the enterprise and mainstream has been accelerating ever since the release of ChatGPT. The Retrieval-Augmented Generation (RAG) paradigm has played a crucial part in making LLM-based applications useful, by facilitating access to knowledge contained in external data sources, and helping extend the context memory accessible to an LLM. In this talk, we will go through the opportunities and challenges in this space, highlighting tools and techniques for implementing this paradigm. We will also go through the limitations of this approach and showcase examples where using RAG over relying on the LLMs own internal knowledge might be even detrimental. We will explore potential future work to make this paradigm more robust and production-ready

Speakers/Topics:
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

Venue:
OneEleven, 325 Front St W 4th Floor, Toronto

Sponsors:
We are actively seeking sponsors to support AI developers community.  Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will have the chance to speak at the meetups, receive prominent recognition, and gain exposure to our extensive membership base of 8,000+ local or 300K+ developers worldwide.

Community on Slack/Discord
- Event chat: chat and connect with speakers and attendees
- Sharing blogs, events, job openings, projects collaborations
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