Welcome to our in-person machine learning meetup in Toronto. Join us for deep dive tech talks on AI/ML/Data, food/drink, networking with speakers&peers developers.

Agenda (EST):
* 5:00pm~5:30pm: Checkin, Food/drink and networking
* 5:30pm~7:30pm: Tech talks
* 7:30pm: Open discussion & Mixer

Tech Talk 1: Customizing Large Language Models for Your Own Data
Speaker: Zain Hasan, Engineer @Weaviate
Abstract: In this talk, you will learn how to enable ChatGPT-like LLMs on your own data by using vector search engines. Generative LLMs like ChatGPT are trained on huge datasets of open data from the internet. This enables them to have vast amounts of general knowledge about the world and natural language. However, there is one disadvantage: once trained, you can only use Generative Pretrained Transformers (GPT) only on the data that it was trained on. When you ask what today news is, ChatGPT cannot answer that question.
In order to benefit from the capabilities of LLMs like ChatGPT in real-life use cases, it would be ideal if we could apply the generative power to new or custom data, such as a chatbot for your e-commerce platform which has knowledge about the products you sell, your detailed return policies or specific promotions currently going on. This becomes possible if we combine ChatGPT with a vector search engine! Integrating a generative LLM with a vector search engine allows you to filter through your entire personal database and search for information relevant to a prompt, which can then be provided to ChatGPT along with the prompt. This framework allows you to harness the LLM model power to solve tasks grounded in the context of your own data!
In this session, you will learn what vector search is, why and when you would need it and you will see vector search in action during live demos.

Tech Talk 2: TBD

Venue:
Microsoft Reactor Toronto
101 College St Suite 120 · Toronto, ON. Google Map

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