Skip to main content

TensorFlow announces its roadmap for the future with focus on speed and scalability

TensorFlow, the machine learning model company, recently released a blog post laying out the ideas for the future of the organization. 

According to TensorFlow, the ultimate goal is to provide users with the best machine learning platform possible as well as transform machine learning from a niche craft into a mature industry.  

In order to accomplish this, the company said they will listen to user needs, anticipate new industry trends, iterate APIs, and work to make it easier for customers to innovate at scale.

To facilitate this growth, TensorFlow intends on focusing on four pillars: make it fast and scalable, utilize applied ML, have it be ready to deploy, and keep simplicity. 

TensorFlow stated that it will be focusing on XLA compilation with the intention of making model training and inference workflows faster on GPUs and CPUs. Additionally, the company said that it will be investing in DTensor, a new API for large-scale model parallelism.

The new API allows users to develop models as if they were training on a single device, even when utilizing several different clients. 

TensorFlow also intends to invest in algorithmic performance optimization techniques such as mixed-precision and reduced-precision computation in order to accelerate GPUs and TPUs.

According to the company, new tools for CV and NLP are also a part of its roadmap. These tools will come as a result of the heightened support for the KerasCV and KerasNLP packages which offer modular and composable components for applied CV and NLP use cases. 

Next, TensorFlow stated that it will be adding more developer resources such as code examples, guides, and documentation for popular and emerging applied ML use cases in order to reduce the barrier of entry of machine learning. 

The company also intends to simplify the process of exporting to mobile (Android or iOS), edge (microcontrollers), server backends, or JavaScript as well as develop a public TF2 C++ API for native server-side inference as part of a C++ application.

TensorFlow also stated that the process for deploying models developed using JAX with TensorFlow Serving and to mobile and the web with TensorFlow Lite and TensorFlow.js will be made easier. 

Lastly, the company is working to consolidate and simplify APIs as well as minimize the time-to-solution for developing any applied ML system by focusing more on debugging capabilities. 

A preview of these new TensorFlow capabilities can be expected in Q2 2023 with the production version coming later in the year. To follow the progress, see the blog and YouTube channel. 

The post TensorFlow announces its roadmap for the future with focus on speed and scalability appeared first on SD Times.



from SD Times https://ift.tt/TW7xEZr
Labels:

Comments

Post a Comment

Popular posts from this blog

Difference between Web Designer and Web Developer Neeraj Mishra The Crazy Programmer

Have you ever wondered about the distinctions between web developers’ and web designers’ duties and obligations? You’re not alone! Many people have trouble distinguishing between these two. Although they collaborate to publish new websites on the internet, web developers and web designers play very different roles. To put these job possibilities into perspective, consider the construction of a house. To create a vision for the house, including the visual components, the space planning and layout, the materials, and the overall appearance and sense of the space, you need an architect. That said, to translate an idea into a building, you need construction professionals to take those architectural drawings and put them into practice. Image Source In a similar vein, web development and design work together to create websites. Let’s examine the major responsibilities and distinctions between web developers and web designers. Let’s get going, shall we? What Does a Web Designer Do?
Post a Comment
Read more

A guide to data integration tools

CData Software is a leader in data access and connectivity solutions. It specializes in the development of data drivers and data access technologies for real-time access to online or on-premise applications, databases and web APIs. The company is focused on bringing data connectivity capabilities natively into tools organizations already use. It also features ETL/ELT solutions, enterprise connectors, and data visualization. Matillion ’s data transformation software empowers customers to extract data from a wide number of sources, load it into their chosen cloud data warehouse (CDW) and transform that data from its siloed source state, into analytics-ready insights – prepared for advanced analytics, machine learning, and artificial intelligence use cases. Only Matillion is purpose-built for Snowflake, Amazon Redshift, Google BigQuery, and Microsoft Azure, enabling businesses to achieve new levels of simplicity, speed, scale, and savings. Trusted by companies of all sizes to meet
Post a Comment
Read more

2022: The year of hybrid work

Remote work was once considered a luxury to many, but in 2020, it became a necessity for a large portion of the workforce, as the scary and unknown COVID-19 virus sickened and even took the lives of so many people around the world.  Some workers were able to thrive in a remote setting, while others felt isolated and struggled to keep up a balance between their work and home lives. Last year saw the availability of life-saving vaccines, so companies were able to start having the conversation about what to do next. Should they keep everyone remote? Should they go back to working in the office full time? Or should they do something in between? Enter hybrid work, which offers a mix of the two. A Fall 2021 study conducted by Google revealed that over 75% of survey respondents expect hybrid work to become a standard practice within their organization within the next three years.  Thus, two years after the world abruptly shifted to widespread adoption of remote work, we are declaring 20
Post a Comment
Read more