Ovetta Sampson, Director of UX for AI compute enablement at Google shares what she hopes the latest AI capabilities can do, from augmenting some of the work that humans are doing thus increasing the speed of how we solve some of the perennial human problems. Watch more People of AI → https://goo.gle/PAI Speaker: Ashley Oldacre, Ovetta Sampson

Is AI a medium or tool? Artist Douglas Edrick Stanley and Dean of Research at Geneva University of Art and Design Anthony Masure answers this question. For more information, watch the People of AI podcast episode, “The intersection of AI, art, and design with Douglas Edric Stanley and Anthony Masure.” Watch more People of AI → https://goo.gle/PAI Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow Speaker: Ashley Oldacre

Hear about Dr. Oliver Aalami’s journey on incorporating AI in the healthcare industry and his passion for integrating technology in patient care. For more information, head over to the People of AI podcast episode, “Digital health with Dr. Oliver Aalami.” Watch more People of AI → https://goo.gle/PAI Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow Speaker: Ashley Oldacre

How can you use NotebookLM outside of your developer projects? Well, maybe our guests on this episode can help fuel your curiosity. Watch more People of AI → https://goo.gle/PAI Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow #PeopleofAI Speaker: Ashley Oldacre Products Mentioned: NotebookLM, Gemini

Find out what it means to be not only a person of AI, but responsibly. To learn more, head over to the related video “Responsible AI and emerging technology panel at DevFest Silicon Valley.” Watch more People of AI → https://goo.gle/PAI Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow #PeopleofAI Speaker: Ashley Oldacre Products Mentioned: AI

Learn the origin behind Checks and the inner workings of the Checks compliance framework. Want to hear more? Check out the People of AI podcast episode “3-step approach to mobile app compliance with Checks co-founders Fergus Hurley and Nia Castelli” for more information. Watch more People of AI → https://goo.gle/PAI Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow #PeopleofAI Speaker: Ashley Oldacre Products Mentioned: AI, Checks

We explore how AI can help hearing parents learn sign language like having an AI game to help judge their signing. Watch more People of AI → https://goo.gle/PAI Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow #PeopleofAI Speaker: Ashley Oldacre

We’re super excited to announce the latest season of People of AI. 🎉We talk about what we think it means to be a person of AI. Want to learn more? Check out the first episode of Season 4 where Ashley and Gus explore the different ways people are using and interacting with AI and more! Watch more People of AI → https://goo.gle/PAI Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow Speakers: Ashley Oldacre, Luiz Gustavo Martins Products Mentioned: AI

Learn how to use TensorFlow Ranking alone for recommendation. Wei, a Developer Advocate at Google, covers retrieval-ranking pipeline for large recommendation models, ranking-ony recommendations, and the relationship between TF Recommenders and TF Ranking. Chapters: 0:00 - Introduction 1:18 - TensorFlow Ranking 4:22 - Differences between TF Recommenders and TF Ranking Resources: Recommend movies for users with TensorFlow Ranking → https://goo.gle/3TexzPF Tech talk on TensorFlow Ranking at Recommendation Systems Dev Summit 2023 → https://goo.gle/4a7emWF Watch more Building recommendation systems with TensorFlow → https://goo.gle/3Bi8NUS Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow Speaker: Wei Wei Products mentioned: TensorFlow Recommenders

Learn how to perform object detection with a pretrained model in KerasCV. Prefer to build a custom model? Wei, a Developer Advocate at Google, has got you covered! He also covers how to build an object detection pipeline to train a custom model easily so that you can use it for your special use cases. Chapters: 0:00 - Introduction 1:39 - Object detection with a pre trained model 4:21 - Train a custom object detection model 7:04 - Resources Resources: Tutorial → https://goo.gle/4caM9Aq Model list → https://goo.gle/3wNfel6 Watch more Applied ML with KerasCV and KerasNLP → https://goo.gle/AppliedMLwithKeras Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow Speaker: Wei Wei

Learn how to leverage TPU embeddings to accelerate embedding lookup operation with SpareCore. SpareCore is the specially-designed hardware on Google’s latest TPU. Wei, a Developer Advocate at Google, covers how to speed up the embedding lookup operation with large embedding tables in recommendation models. Chapters: 0:00 - Introduction 0:35 - How retrieval works in large scale recommendation systems 1:55 - SparseCore 2:47 - How to use TPU embeddings 5:18 - Resources Resources: TPU v4: An optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings → https://goo.gle/3VsMMiT TensorFlow 2 TPUEmbeddingLayer: Quick Start → https://goo.gle/4clKs3d Building Large Scale Recommenders using Cloud TPUs → https://goo.gle/3V56kcN TPU Embedding tech talk at Recommendation Systems Dev Summit → https://goo.gle/3wOJNqE Watch more Building recommendation systems with TensorFlow → https://goo.gle/3Bi8NUS Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow Speaker: Wei Wei

Learn how to perform text classification using KerasNLP with Wei, a Developer Advocate at Google. This video covers a progressive approach of going from basic inference with a pretrained classifier and fine-tuning a custom model. Chapters: 0:00 - Introduction 1:48 - Inference with a pretrained classifier 2:30 - Fine-tuning a pretrained BERT backbone 2:53 - Fine-tuning with a user-controlled preprocessing 3:36 - Fine-turning with a custom model 4:10 - Resources Resources: Tutorial→ https://goo.gle/3wMBKKQ Model list → https://goo.gle/3uS0p08 Watch more Applied ML with KerasCV and KerasNLP → https://goo.gle/AppliedMLwithKeras Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow Speaker: Wei Wei

Learn how to use stable diffusion for image generation with KerasCV. Wei, a Developer Advocate at Google, shares how to create images from text prompts. Find out how TensorFlow tooling, mixed precision, and XLA compilation, allows you to experiment much faster. Chapters: 0:00 - Introduction 0:35 - How does stable diffusion work? 2:34 - How to run stable diffusion faster 4:13 - Resources Resources: Tutorial → https://goo.gle/49VStK2 Diffusion model with KerasCV video → https://goo.gle/3IteOmj Diffusion model implementation with Keras → https://goo.gle/3Tqxv0r Watch more Applied ML with KerasCV and KerasNLP → https://goo.gle/AppliedMLwithKeras Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow Speaker: Wei Wei

Learn about KerasCV and KerasNLP with Wei, a developer advocate at Google. In this video, you’ll learn about Keras Core, a modular backend architecture which allows you to run Keras code on top of arbitrary frameworks. From setting up the backend with KerasCV and KerasNLP. We also cover what you can do with KerasCV from image classification and object detection to data augmentation and image generation. Learn how you can use Keras NLP for text classification and text generation as well. Chapters: 0:00 - Intro 4:35 - What can you do with KerasCV? 9:50 - What can you do with KerasNLP? 17:17 - Resources Resources: KerasCV documentation → https://goo.gle/49ZNDeA KerasNLP documentation → https://goo.gle/4c1N8mp Keep up with the latest Keras announcements → https://goo.gle/3v5n0Gu Keras Core → https://goo.gle/4c4CtqX KerasCV on Github → https://goo.gle/404TD0v KerasNLP on Github → https://goo.gle/3nY4HPu Watch more Applied ML with KerasCV and KerasNLP → https://goo.gle/AppliedMLwithKeras Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #Keras #NLP Speaker: Wei Wei

Learn how to generate text with KerasNLP. Wei, a Developer Advocate at Google, shares how to fine-tune a Reddit dataset and how you can use the fine-tuned model on-device. Chapters: 0:00 - Introduction 0:31 - Generate text with a pretrained model 1:53 - Fine-tuning on Reddit dataset 3:04 - On-device running 3:22 - Sampling methods 3:58 - Resources Resources: Tutorial → https://goo.gle/3V9iuBf I/O 2023 workshop → https://goo.gle/3wSd9UN On-device Large Language Models with Keras and TensorFlow Lite → https://goo.gle/4a2Mpzr Github → https://goo.gle/3wH7KzT Samplers → https://goo.gle/3T5NjV6 Watch more Applied ML with KerasCV and KerasNLP → https://goo.gle/AppliedMLwithKeras Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #TensorFlow Speaker: Wei Wei