AI x Product Series 6: How LLM Might Disrupt Recommendation & Search Roundtable

Will the recent waves of AI and large models change how we search or receive recommendations every day? Is there an opportunity to build a new traffic entrypoint to distribute content? What will be the next generation of recommendation systems?

Join us on Friday night of 7:30 pm at a roundtable discussion of these questions cohosted by Product Pub x SeaMate. This is the 6th event of Product Pub's signature AI X Product Series. We will invite a few knowledgeable speakers, and ~30 industry experts as key offline participants at the frontier of search and recommendation from Google, Meta, Amazon, startups.

Speaker:

• Chen Zheng, Senior Product Director, Roblox Head of Discovery, and Product Pub founder
• Bo Long, Meta Head of Recommendation and Foundation AI for Monetization

Moderator:

• Lydia Tang, Product Pub board member

Language:

• Chinese

Questions & Agenda:

Part 1: Are there any adopted applications of LLM in the Discovery systems such as recommendation and search?

Part 2: Has the user interactions of search and recommendation been changed by LLM?

1. For example, how do you think about the experiences of new Search UX presented by Bing and Perplexity? What about Notion and Github’s inline autopilot?
2. Are there any other examples of products that you noticed?
3. How do you think LLM might disrupt Search and Recommendation differently?
4. For these new product innovations, what will be the business models that back it up?

Part 3: Will LLM or Large Models disrupt the paradigm of the recommendation / search systems (Query Understanding -> Retrieval -> Rough Sort -> Fine Sort -> Merge Sort)?

1. What are applications of LLM in the traditional recommendation paradigm of Query Understanding -> Retrieval -> Rough Sort -> Fine Sort -> Merge Sort?
2. What problems are these innovative applications solving? Are they cost-effective?
3. What are some technical and product challenges or constraints?
4. Will the paradigm of Query Understanding ->  Merge Sort be challenged? What are the factors that challenge this paradigm?

Part 4: What do you envision to be the next era of information retrieval systems?

1. 1.0 List & Navigation by Yahoo, 2.0 Search by Google, 3.0 Personalized Recommendation by Meta & TikTok, what will be 4.0?
2. What are the driving forces that evolve 3.0 to 4.0?
3. Where will the changes land first? Startups or incumbents?

Ticket Options:

1. Apply for an offline seat: This is not a ticket, only an application. We will select 30 key participants who are industry experts to join this event offline at Mountain View. Offline participants will have a lot of opportunities to speak up to contribute to the discussion, and connect with other speakers key participants in person. If you are selected, we will send you an email with an entry to buy a ticket for $20 and confirm your seat.
2. Online streaming ticket: This is your ticket to attend the event with online Zoom streaming options. If you are admitted to be an offline participant, this ticket can be upgraded to an offline seat. This ticket is not refundable.