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Introduction As the demand for smarter, more automated systems grows across industries, machine learning (ML) and deep learning (DL) have become the backbone of innovation. From self-driving cars to personalized recommendations, AI applications are transforming the way we live and work. One of the key frameworks driving this revolution is TensorFlow. TensorFlow is an open-source Read More
Source: analyticsinsight.net While organizations are increasingly leveraging ML tools, most of the projects fail during the test phase. Machine learning (ML) has been touted as one of the key enablers of the Fourth Industrial Revolution. In recent times, businesses explore new approaches to maximize their profits and reach, without compromising on customer services. Machine learning helps Read More
Source: channelasia.tech Google’s Android Studio IDE team has released the stable version of Android Studio 4.1, featuring machine learning improvements and a database inspector. With the 4.1 release, Android Studio improves on-device machine learning support via backing for TensorFlow Lite models in Android projects. Android Studio generates classes so models can be run with better type safety and less Read More
Source: venturebeat.com Did you ever wonder what goes on inside the brain of a data scientist? A few years ago, PerceptiLabs, a deep tech startup, took on an ambitious goal — to visualize what data scientists see when they are building a machine learning model. In doing so, they reinvented the process of model building, Read More
Source: marktechpost.com Google recently released TensorFlow Quantum, a toolset for combining state-of-the-art machine learning techniques with quantum algorithm design. This is an essential step to build tools for developers working on quantum applications. Simultaneously, they have focused on improving quantum computing hardware performance by integrating a set of quantum firmware techniques and building a TensorFlow-based toolset Read More
Source: analyticsinsight.net While deep learning is viewed as a small part of the field of artificial intelligence, it’s now a field that is by all accounts growing out of the AI space itself. Deep learning is the advancement of ‘thinking’ computer systems, called neural networks, and using it requires coding procedures unfamiliar to old-school developers. Read More
Source: aithority.com Himax Technologies, Inc., a leading supplier and fabless manufacturer of display drivers and other semiconductor products, announced the launch of WiseEye WE-I Plus HX6537-A solution that supports Google’s TensorFlow Lite for Microcontrollers. In this collaboration, Himax is providing the HX6537-A processor with NN (neural network) based SDK (Software Development Kit) for developers to Read More
Source: sdtimes.com Google has announced a new TensorFlow runtime designed to make it easier to build and deploy machine learning models across many different devices. The company explained that ML ecosystems are vastly different than they were 4 or 5 years ago. Today, innovation in ML has led to more complex models and deployment scenarios Read More
Source: analyticsindiamag.com Google has launched TensorFlow RunTime (TFRT), which is a new runtime for its TensorFlow machine learning framework. According to a recent blog post by Eric Johnson, TFRT Product Manager and Mingsheng Hong, TFRT Tech Lead/Manager, “TensorFlow RunTime aims to provide a unified, extensible infrastructure layer with best-in-class performance across a wide variety of domain-specific hardware. Read More
Source: sg.channelasia.tech Google has announced TensorFlow Lite Model Maker, a tool for converting an existing TensorFlow model to the TensorFlow Lite format used to serve predictions on lightweight hardware such as mobile devices. TensorFlow models can be quite large, and serving predictions remotely from beefy hardware capable of handling them isn’t always possible. Google created the TensorFlow Lite Read More
Source: analyticsindiamag.com The TensorFlow team at Google recently introduced a new tool for TensorFlow Lite (TFLite) known as Model Maker. The TFLite Model Maker simplifies the process of adapting and converting a TensorFlow Neural Network model to particular input data when deploying this model for on-device ML applications. Developed by researchers and engineers from the Google Brain Read More
Source: venturebeat.com Google today announced TensorFlow Lite Model Maker, a tool that adapts state-of-the-art machine learning models to custom data sets using a technique known as transfer learning. It wraps machine learning concepts with an API that enables developers to train models in Google’s TensorFlow AI framework with only a few lines of code, and to deploy those Read More
Source: insights.dice.com Over the past few years, many companies have embraced artificial intelligence (A.I.) and machine learning as the way of the future. That’s been good news for those technologists who’ve mastered the tools and concepts related to A.I. and machine learning; those with the right combination of experience and skills can easily earn six-figure salaries (with accompanying perks and Read More
Source: technowize.com Google announced the launch of TensorFlow Quantum, which is based on Machine learning and quantum computing coming together to build hybrid AI models. The TFQ was built in collaboration with the University of Waterloo, X, and Volkswagen. TensorFlow Quantum is an opensource library for rapid prototyping of quantum ML models. “TensorFlow Quantum will Read More
Source: dqindia.com Udacity announced the launch of its new Nanodegree program: Intro to Machine Learning with TensorFlow. The next-generation program in machine learning (ML) introduces learners to the fundamentals of Machine Learning in a way that is effective and engaging at the same time. The Nanodegree program incorporates advanced areas such as manipulating data, supervised Read More
Source: siliconangle.com Google LLC today launched an enterprise version of TensorFlow, the popular open-source artificial intelligence framework it created to run machine learning, deep learning and other statistical and predictive analytics workloads. The TensorFlow framework simplifies the process of acquiring data, training models, serving predictions and refining future results. Common use cases include training algorithms for image Read More
Source – androidauthority.com After helping to define the modern internet era with Search and Android, Google is already at the forefront of the next wave in computing research and development: AI. Many consider artificial intelligence and neural network computers to be the next step in computing, enabling new use cases and faster computation to solve currently Read More
