| Sumario: | Sponsored by deepset Reaching a million users in less than a week, ChatGPT has ignited discussions about the potential of artificial intelligence to disrupt industries from law to academia, art to medicine. OpenAI and Google, Meta, and others are releasing large language models that are fueling innovations in the development of search engines, recommendation systems, and tools we use to generate content from text, images, and music to code and software. While the possibilities for new products and services built on these state-of-the-art AI systems are endless, business leaders and machine learning practitioners alike are searching for answers on how to get the most of these technologies for their work. Important questions are also emerging around the limitations and potential obstacles to integrating new large AI models such as ChatGPT into existing systems. Join our expert speakers to discuss these issues and learn how you can leverage ChatGPT and other large AI models to build new products, increase productivity, and more. What you'll learn and how you can apply it You're a current or future machine learning product owner or machine learning practitioner, or you're simply interested in the state of the art of artificial intelligence. You want to learn more about ChatGPT and other large AI models and how they will impact other technologies as well as nontechnological fields. This recording of a live event is for you because... Discover possibilities for ChatGPT and large language models Uncover pitfalls and avoid missteps as you integrate this new frontier in AI into organizations of all types Learn actionable suggestions on dealing with large datasets and data augmentation, various model architectures, domain adaptation, and inference challenges Recommended follow-up: Read Natural Language Processing with Transformers, revised edition (book) Follow ChatGPT (expert playlist) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.
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