14th NLP Meetup with Siemens and Jina AI

Dear NLP community,

We hope you are all doing well in these highly dynamic times of Large Language Models and NLP.

We would like to invite you to our 14th NLP meetup, third in 2023 and actually the second in May ;) This time, we are happy to be invited by Siemens to come to a cool collaboration space inside the compound of the Siemens Corporate Technology in Perlach.

You will experience two very interesting talks by Siemens focusing the application of large language models in industrial use cases and the challenge of evaluating LLM-based solutions. Additionally, we are happy to welcome Jina AI to give a deep dive on their products and example use cases.

We want to thank Siemens for hosting this evening and for providing our NLP community another great meetup experience. 🚀

Important note: Please also register unter this Eventbrite site as well as Siemens need your full name for entering their location. Thank you!

Hope we all meet, learn and discuss 😊
Best Bernhard, Christoph, Kristian and Kun

=== Agenda ===

18:00 - Doors open
18:15 - [Introduction] Welcome by Siemens & appliedAI
18:25 - [Presentation incl. Q&A]:

• Topic: Applications of Large Language Models in industrial context
• Maria Sukhareva, Senior Key Expert Computer Linguistics @ Siemens

19:05 - [Presentation, incl Q&A]:

• Topic: Challenges and methods for evaluating LLMs and generative AI
• Mark Buckley, Principal Key Expert NLP @ Siemens

19:45 - Break
20:00 - [Presentation incl Q&A]:

• Topic: Cutting Through the Hype: Jina AI's Scalable Open-Source Solutions for Multimodal AI
• Saahil Ognawala, Senior Product Manager @ Jina AI

20:30 - [Networking] Get-together with sponsored food and drinks
21:30 - Doors closed latest

=== Talk #1 ===
Title:
Applications of Large Language Models in industrial context
Abstract:
Large language models are becoming increasingly popular in the industry, offering a new level of performance for many natural language processing tasks such as information extraction, text classification. Being zero-shot multi-task learners, LLMs can also simplify productive operations as well as shorten the time which takes to bring an application into production. These models have the potential to revolutionize the daily workflow, but also come with ethical considerations. This talk will explore the use cases for large language models in industrial applications, as well as the ethical implications of using them, such as the potential for bias and the spread of misinformation.

=== Talk #2 ===
Title:
Challenges and methods for evaluating LLMs and generative AI
Abstract:
In the past, evaluating NLP models was a case of taking the right test data and computing some well-defined, reproducible metrics. Even complex outputs like machine translation or relation extraction can be tested against gold standard test sets. Now however, with the advent of generative AI and LLMs, the models' outputs are more complex, more variable and more subjective. Set against a requirement for factual correctness, this leads to stringent demands for reliable evaluation.

=== Talk #3 ===
Title:
Cutting Through the Hype: Jina AI's Scalable Open-Source Solutions for Multimodal AI
Abstract:
In this talk, we will showcase how Jina AI helps organizations cut through the AI hype by providing practical and scalable AI solutions for industrial domains where stability, availability, and business value are crucial. You will learn how our open-source MLOps framework and multimodal products empower a seamless transition from research to industry-level applications across various sectors.