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We are delighted to announce the eighteenth London Information Retrieval Meetup, a free evening event aimed at enthusiasts and professionals curious to explore and discuss the latest trends in the field.

This time the Meetup is ON TRAVEL, with a live event in Milan (Italy) being streamed online on Zoom!

ATTENTION: Remember to fill out the form to confirm the registration:
https://forms.gle/oWj4WWr2LcjkTxuWA

>>>> IN-PRESENCE MEETUP

Location:
HUAWEI ITALIA
Via Lorenteggio, 240, 20147 (Tower A, second floor)
Milan, ITALY

Date: 23rd October 2023 | open doors from 5:30 PM (GMT+1) - Italian time: 6:30 PM

>>>> ONLINE MEETUP

Location: Zoom (you will receive the link after filling out the registration form https://forms.gle/oWj4WWr2LcjkTxuWA)

Date: 23rd October 2023 | 6:15-8:00 PM (GMT+1) - Italian time: 7:15-9:00 PM)

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The event will be structured around 3 technical talks, each followed by a Q&A session. The event will end with a networking session.

> Open doors from 5:30 GMT+1 (in-presence) - Italian time: 6:30 PM

> 6:15 GMT+1 open doors for virtual attendees - Italian time: 7:15 PM

  • Welcome & Latest News - Alessandro Benedetti, Director @ Sease
  • Huawei Intro - Luca Frigerio, Online Marketing Manager @ Huawei
    Huawei Cloud - Francesco Stranieri, Developer Advocate @ Huawei Cloud

> 6:30 GMT+1 First talk - Open Source Large Language Models in Search | Alessandro Benedetti - Director @ Sease
> 7:00 GMT+1 Second talk - **GenerativeAI with Apache Solr and LangStream.ai** | Enrico Olivelli - Senior Software Engineer @ DataStax
> 7:30 GMT+1 Third talk - A Deep Dive into Personalized Information Retrieval | Pranav Kasela - PhD Student @ Università Milano-Bicocca
> 8:00 GMT+1 Huawei presents ModelArts - Simple tooling for your AI | Francesco Stranieri - Developer Advocate @ Huawei Cloud
> 8:15 GMT+1 Networking session + buffet

For more info, including speaker bios, abstracts and timing please check our website https://sease.io/

Argomenti correlati

Deep Learning
Neural Networks
Open Source
Search, Information Retrieval
Enterprise Search

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