TensorFlow Programming Tutorials & Engineering Articles

LiteRT has evolved from its TensorFlow Lite foundation into a universal on-device AI inference framework, now offering production-ready GPU acceleration across six platforms and streamlined NPU int...

Shopify open-sources Tangle, an ML experimentation platform built to solve six common failure modes in machine learning development.

Metrax is a high-performance library designed for efficient and robust model evaluation metrics in JAX, addressing the need for standardized metrics during the migration from TensorFlow.

The article reflects on a decade of AI platform development at Pinterest, detailing the evolution from fragmented machine learning stacks to a unified AI platform that supports various models.

This article discusses how Uber has integrated explainability into its machine learning platform, Michelangelo, using Integrated Gradients (IG) to provide interpretable attributions for deep learni...

The article introduces Coral NPU, a full-stack, open-source platform designed to enhance Edge AI capabilities on low-power devices.

The article discusses building high-performance data pipelines using Grain, a data loading library for JAX, and ArrayRecord, an efficient file format.

The article discusses the relevance of the Common Vulnerabilities and Exposures (CVE) system in relation to AI models, arguing that CVEs should be focused on the frameworks and applications that ut...

The article discusses the development of AI face cropping technology by Cloudflare, which automatically crops images around detected faces.

This article provides a comprehensive guide on how to train a GPT-2 model using JAX on TPU, highlighting the ease of leveraging Google TPUs for free.

The article discusses the impending shortage of healthcare workers and how AI-enabled robotic systems, powered by NVIDIA Isaac for Healthcare, can address these challenges.

The article discusses the introduction of cuda-cccl, a Python library that provides high-level building blocks for NVIDIA CUDA kernel fusion, enabling developers to write efficient algorithms witho...

The article discusses how to use KerasHub for loading model weights from SafeTensors into Keras, enabling flexible end-to-end machine learning workflows across different frameworks like JAX, PyTorc...

The article discusses the advancements in React Native graphics through the integration of WebGPU and Skia, highlighting how these technologies enhance performance and enable new capabilities for d...

The article introduces Keras Recommenders, a new library designed to simplify the creation of state-of-the-art recommendation systems using Keras with JAX, TensorFlow, or PyTorch.

The article discusses how to accelerate Deep Learning (DL) and Large Language Model (LLM) inference using Apache Spark in cloud environments.

The article discusses optimizing transformer-based diffusion models for video generation using NVIDIA TensorRT, highlighting significant reductions in latency and total cost of ownership (TCO) achi...

A new AI-powered tool developed by researchers at the University of Florida and medical centers aims to improve the diagnosis of Parkinson's disease using standard MRI scans.

NVIDIA has open-sourced the KAI Scheduler, a Kubernetes-native GPU scheduling solution under the Apache 2. 0 license, originally developed for the Run:ai platform.

NVIDIA Dynamo is a newly released low-latency distributed inference framework designed to enhance the deployment of generative AI and reasoning models in large-scale environments.

NVIDIA has announced world-record inference performance for the DeepSeek-R1 model using the Blackwell architecture, achieving over 250 tokens per second per user and a maximum throughput of over 30...

The article discusses an advanced deep-learning model designed to automate X-ray analysis for spinal health diagnostics, enhancing speed and accuracy in assessing conditions like scoliosis and kyph...

The article discusses key insights from the NVIDIA 6G Developer Day 2024, highlighting the integration of AI into 6G infrastructure and the significance of AI-RAN.

The article discusses Liger-Kernel, an open-source library designed to enhance GPU efficiency for training large language models (LLMs).

The article announces that Francois Chollet, the creator of Keras, is leaving Google to pursue new opportunities.

The Web AI Summit 2024, hosted by Google on October 18, 2024, focused on client-side AI for developers, showcasing how machine learning models can operate offline in web browsers.

The article discusses the advancements in AI agents facilitated by NVIDIA AI Enterprise, emphasizing enhanced security, streamlined deployment, and management of AI pipelines.

The article discusses how to scale Large Language Models (LLMs) using NVIDIA Triton and NVIDIA TensorRT-LLM in a Kubernetes environment.

The article discusses the Brain-Machine Interactive Neuromodulation Research Tool (BMINT), which utilizes closed-loop neuromodulation techniques to treat brain diseases like epilepsy and Parkinson'...

This article discusses the implementation of Ray Batch Inference at Pinterest, highlighting its advantages over previous solutions like Apache Spark and Torch Dataloader.

The article discusses the development and deployment of real-time neural receivers (NRX) in 5G New Radio (5G NR) systems, highlighting their potential to enhance wireless communication through AI-d...

LiteRT, formerly known as TensorFlow Lite, is a high-performance runtime for on-device AI that now supports models from multiple frameworks including PyTorch, JAX, and Keras.

The article discusses the release of NVIDIA TAO 5. 5, a framework that simplifies AI model development and deployment.

The article discusses the impressive performance of the NVIDIA Triton Inference Server in the MLPerf Inference v4.

The article discusses optimizing Large Language Model (LLM) inference at the edge using TensorFlow Lite (TFLite) and XNNPack.

The article discusses NVIDIA's fVDB, a deep-learning framework designed to build spatial intelligence from real-world 3D data.

The article discusses the release of the Gemma 2 model with 27 billion parameters, highlighting its capabilities in Keras and integration with JAX for efficient model training.

Model Explorer is a powerful graph visualization tool designed to simplify the development and optimization of machine learning models for edge devices.

The article discusses NVIDIA Metropolis, a platform for real-time vision AI that streamlines deployment through microservices and workflows.

The article discusses how to build a zero-copy AI sensor processing pipeline using OpenCV within the NVIDIA Holoscan SDK.

The article introduces the AI Edge Torch Generative API, designed to enable developers to create high-performance LLMs in PyTorch for deployment on edge devices using the TensorFlow Lite runtime.

The article discusses the enhancements made in NVIDIA's cuDNN 9 library, focusing on the acceleration of Transformers through the implementation of Scaled Dot Product Attention (SDPA).

The article discusses how Snap's ML engineering team enhanced the apparel shopping experience using AI, specifically through the Screenshop service integrated into Snapchat.

Google AI Edge Torch provides a seamless integration from PyTorch to TensorFlow Lite (TFLite), enhancing model coverage and CPU performance for mobile devices.

The article recaps the Google I/O 2024 event, highlighting advancements in AI technologies aimed at making AI accessible for developers.

The article provides a comprehensive guide on building a Retrieval-Augmented Generation (RAG) pipeline using NVIDIA AI LangChain AI Endpoints.

This article discusses how to publish Keras models on Kaggle and Hugging Face, highlighting the ease of sharing fine-tuned models with the community.

The article discusses Uber's evolution in machine learning (ML) through its centralized platform, Michelangelo, highlighting its transition from predictive to generative AI.

The article discusses NVIDIA AI Enterprise IGX, a software solution designed for mission-critical AI applications at the edge.

The article discusses the NVIDIA 6G Developer Program, which aims to accelerate the development of 6G technology by providing access to AI/ML tools, simulation environments, and software-defined ne...