March 2024
Read updates from the new release, run LLMs on-device with MediaPipe LLM Inference API (experimental), learn how ML can reduce operational costs, and more.
|
What’s new in TensorFlow 2.16
|
|
Updates include Clang as default compiler for building TensorFlow CPU wheels on Windows, Keras 3 as default version, support for Python 3.12, and more!
|
|
|
|
|
|
|
|
Google I/O is back!
|
Join us online on May 14 to discover, innovate, and unlock new possibilities with AI and all of Google’s latest developer tools.
|
|
|
|
|
|
|
How Tokopedia reduced operational costs using ML for identity verification
|
The team at Tokopedia decided to use MediaPipe and TensorFlow.js's Face Detection library to detect a user’s face with six key points during the seller onboarding process.
|
|
|
|
|
|
|
Run large language models on-device with MediaPipe and TensorFlow Lite
|
The new experimental MediaPipe LLM Inference API includes performance optimizations such as quantization, caching, and weight sharing to run LLMs on Web, Android, and iOS with low latency.
|
|
|
|
|
|
|
Learn applied ML with KerasNLP and KerasCV
|
Watch new videos explaining how to use the KerasNLP and KerasCV libraries for applications including:
|
|
|
|
|
|
|
|
Make datasets easier to find and use with Croissant
|
Use TensorFlow Datasets
CrossaintBuilder
to define Croissant metadata, a format that builds upon
schema.org
structure and combines resource file descriptions, data structure, and default ML semantics into a single file.
|
|
|
|
|
|
|
|
|
|
|
Stay Connected
|
|
|
|
|
|