DSS WEBINARS

Discover the latest and sharpen your skills in AI, data science, machine learning, and related topics

Visit our recordings page to find training videos on various topics: AI webinars, NLP webinars, data engineer webinars, ChatGPT webinars, machine learning webinars, data analytics webinars, and more.

Upcoming webinars

Making Multimodal Generative-AI Work

Watch live: Wednesday, July 17 @ 2pm ET

The future of generative-AI is multimodal and yet, projects involving LLM and Large Vision Models in production are already struggling as teams try to scale up (and out) awe-inspiring Twitter demos. We’ll discuss what teams need to be doing to support the development and integration of multimodal models into product features.

Mikiko Bazeley

MLops & AI Engineer
Labelbox

 

Open Source Qualified Leads: A Marketing Framework for Commercial Open Source

Watch live: Wednesday, July 31 @ 12pm ET

Commercial open source businesses face a unique challenge compared to their proprietary software counterparts: many potential customers already have access to a free version of their product. Determining which open source users are most likely to be interested in paid support, premium features, or other business offerings can be daunting. In this talk, we present a novel framework that commercial open source businesses can utilize to score leads based on their open source usage. This framework helps them establish a thriving business around their open source project.

Avi Press

Founder & CEO
Scarf

Automated Testing of Bias, Fairness, and Robustness of Language Models in the Generative AI Lab

Watch live: Wednesday, July 31 @ 2pm ET

Testing and mitigating bias, fairness, and robustness issues in AI applications in now a legal requirement in the USA in regulated industries like healthcare, human resources, and financial services. This webinar presents new capabilities within the no-code Generative AI Lab, designed for building custom language models by non-technical domain experts, that enable compliance with such requirements and embody best practices for Responsible AI. We’ll cover how you can:

  1. Create, edit, and reuse test suites
  2. Automatically generate test cases for robustness & bias
  3. Manually review and edit tests when needed
  4. Run LLM test suites and see both summarized and drill-down results
  5. Run regression testing before certifying new versions of models, or competing models

This webinar is intended for anyone interested in testing, certifying, and mitigating bias issues in custom language models for real-world systems.

David Cecchini

Sr. Data Scientist
John Snow Labs

Looking for more?

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