Hudson  Kunde

Hudson Kunde

1590404280

Google Announces New TensorFlow Runtime: TFRT

Recently, Google announced TFRT, a new runtime that will replace the existing TensorFlow runtime. TFRT aims to offer a unified, extensible infrastructure layer with best-in-class performance across a wide variety of domain-specific hardware.

According to Google TFRT renders efficient use of multithreaded host CPUs, supports fully asynchronous programming models, and focuses on low-level efficiency. It provides efficient execution of kernels – low-level device-specific primitives – on targeted hardware.

Google said that TFRT plays a critical role in both eager and graph execution.

#google #tensorflow

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Google Announces New TensorFlow Runtime: TFRT
Jon  Gislason

Jon Gislason

1619247660

Google's TPU's being primed for the Quantum Jump

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

As the world is gearing towards more automation and AI, the need for quantum computing has also grown exponentially. Quantum computing lies at the intersection of quantum physics and high-end computer technology, and in more than one way, hold the key to our AI-driven future.

Quantum computing requires state-of-the-art tools to perform high-end computing. This is where TPUs come in handy. TPUs or Tensor Processing Units are custom-built ASICs (Application Specific Integrated Circuits) to execute machine learning tasks efficiently. TPUs are specific hardware developed by Google for neural network machine learning, specially customised to Google’s Machine Learning software, Tensorflow.

The liquid-cooled Tensor Processing units, built to slot into server racks, can deliver up to 100 petaflops of compute. It powers Google products like Google Search, Gmail, Google Photos and Google Cloud AI APIs.

#opinions #alphabet #asics #floq #google #google alphabet #google quantum computing #google tensorflow #google tensorflow quantum #google tpu #google tpus #machine learning #quantum computer #quantum computing #quantum computing programming #quantum leap #sandbox #secret development #tensorflow #tpu #tpus

Hudson  Kunde

Hudson Kunde

1590404280

Google Announces New TensorFlow Runtime: TFRT

Recently, Google announced TFRT, a new runtime that will replace the existing TensorFlow runtime. TFRT aims to offer a unified, extensible infrastructure layer with best-in-class performance across a wide variety of domain-specific hardware.

According to Google TFRT renders efficient use of multithreaded host CPUs, supports fully asynchronous programming models, and focuses on low-level efficiency. It provides efficient execution of kernels – low-level device-specific primitives – on targeted hardware.

Google said that TFRT plays a critical role in both eager and graph execution.

#google #tensorflow

Mckenzie  Osiki

Mckenzie Osiki

1622134500

Inside MoveNet, Google’s Latest Pose Detection Model

Ahead of Google I/O, Google Research launched a new pose detection model in TensorFlow.js called MoveNet. This ultra-fast and accurate model can detect 17 key points in the human body. MoveNet is currently available on TF Hub with two variants — Lightning and Thunder.

While Lightning is intended for latency-critical applications, Thunder is for applications that call for higher accuracy. Both models claim to run faster than real-time (30+ frames per second (FPS)) on most personal computers, laptops and phones.

The model can be launched in the browser using TensorFlow.js architecture with no server calls needed after the initial page load or external packages. The live demo version is available here.

Currently, the MoveNet model works for the individual in the camera field-of-view. But, soon, Google Research looks to extend the MoveNet model to the multi-person domain so that developers can support applications with multiple people.

#developers corner #body movements online #body movements virtual #fitness machine learning #google i/o #google latest #google new development #google research latest #machine learning models body poses #ose detection model #remote healthcare solutions #tensorflow latest model #track body movements #wellness machine learning

What Are Google Compute Engine ? - Explained

What Are Google Compute Engine ? - Explained

The Google computer engine exchanges a large number of scalable virtual machines to serve as clusters used for that purpose. GCE can be managed through a RESTful API, command line interface, or web console. The computing engine is serviced for a minimum of 10-minutes per use. There is no up or front fee or time commitment. GCE competes with Amazon’s Elastic Compute Cloud (EC2) and Microsoft Azure.

https://www.mrdeluofficial.com/2020/08/what-are-google-compute-engine-explained.html

#google compute engine #google compute engine tutorial #google app engine #google cloud console #google cloud storage #google compute engine documentation

Uriah  Dietrich

Uriah Dietrich

1617812820

Google Announces TensorFlow Quantum 0.5.0: Expected Features & Updates

Google is celebrating the first anniversary of TensorFlow Quantum (TFQ), a library for rapid prototyping of hybrid quantum-classical ML models. TFQ is regarded as a tipping point for developments in hybrid quantum and classic machine learning models the company has been pushing for years.

#developers corner #google tensorflow quantum #tensorflow quantum #tensorflow quantum 0.5.0