- Google Talks About the Machine Learning Technology Behind Gboard
Google has been heavily investing in machine learning and neural network technology for a few years now.
- Once it was good enough to be announced, we started seeing Google apply various machine learning techniques to many of their applications and services.
- So as Google’s machine learning technology gets better, we will continue to see them figure out ways to implement it into their products.
- In a new post over on the Google Research Blog, Google spoke about how they’re using machine learning to improve the user experience of people using Gboard.
- With Neural Spatial Models, Google is able to address the ‘fat finger’ issue that some people experience when typing on a smartphone keyboard.
Google has been heavily investing in machine learning and neural network technology for a few years now. Once it was good enough to be announced, we started seeing Google apply various machine learning techniques to many of their applications and services.
Continue reading “Google Talks About the Machine Learning Technology Behind Gboard”
- At the moment, artificial intelligence lives in the cloud, but Google — and other big tech companies — want it work directly on your devices, too.
- At Google I/O today, the search giant announced a new initiative to help its AI make this leap down to earth: a mobile-optimized version of its machine learning framework named TensorFlowLite.
- The newly announced version, TensorFlowLite, will build on this, helping users slim down their machine learning algorithms to work on-device.
- The company also announced that an API for making machine learning work better with phone chips would be coming sometime in the future — a clear sign that Google thinks your next phone will have an AI-optimized chip in it.
- TensorFlowLite should help Google (and the wider AI research community) bring even more interesting functions like this to our most-used and most-important devices.
At the moment, artificial intelligence lives in the cloud, but Google — and other big tech companies — want it work directly on your devices, too. At Google I/O today, the search giant announced a…
Continue reading “Google’s new machine learning framework is going to put more AI on your phone”
- You can program these TPUs with TensorFlow, the most popular open-source machine learning framework on GitHub, and we’re introducing high-level APIs, which will make it easier to train machine learning models on CPUs, GPUs or Cloud TPUs with only minimal code changes.With Cloud TPUs, you have the opportunity to integrate state-of-the-art ML accelerators directly into your production infrastructure and benefit from on-demand, accelerated computing power without any up-front capital expenses.
- Since fast ML accelerators place extraordinary demands on surrounding storage systems and networks, we’re making optimizations throughout our Cloud infrastructure to help ensure that you can train powerful ML models quickly using real production data.Our goal is to help you build the best possible machine learning systems from top to bottom.
- For example, Shazam recently announced that they successfully migrated major portions of their music recognition workloads to NVIDIA GPUs on Google Cloud and saved money while gaining flexibility.Introducing the TensorFlow Research CloudMuch of the recent progress in machine learning has been driven by unprecedentedly open collaboration among researchers around the world across both industry and academia.
- To help as many researchers as we can and further accelerate the pace of open machine learning research, we’ll make 1,000 Cloud TPUs available at no cost to ML researchers via the TensorFlow Research Cloud.Sign up to learn moreIf you’re interested in accelerating training of machine learning models, accelerating batch processing of gigantic datasets, or processing live requests in production using more powerful ML models than ever before, please sign up today to learn more about our upcoming Cloud TPU Alpha program.
- If you’re a researcher expanding the frontier of machine learning and willing to share your findings with the world, please sign up to learn more about the TensorFlow Research Cloud program.
Announcing that our second-generation Tensor Processing Units (TPUs) will soon be available for Google Cloud customers who want to accelerate machine learning workloads.
Continue reading “Build and train machine learning models on our new Google Cloud TPUs”
- Typography enthusiasts likely already know how to identify fonts by name, but it’s always useful to explore visually similar fonts when you feel like changing up your options.
- Design consultant firm IDEO’s Font Map helps you do exactly that, with an interactive tool that lets you browse through fonts by clicking on them and seeing ones nearby that look similar, or by specifically searching for fonts by name.
- IDEO software designer Kevin Ho built the map using a machine learning algorithm that can sort fonts by visual characteristics, like weight, serif or san-serif, and cursive or non-cursive.
- “Designers need an easier way to discover alternative fonts with the same aesthetic — so I decided to see if a machine learning algorithm could sort fonts by visual characteristics, and enabling designers to explore type in a new way,” he wrote in a blog post.
- Services that compare and suggest visually similar fonts already exist, like Identifont and the blog Typewolf, but IDEO’s tool makes it easy to quickly browse and at the very least, appreciate all the options out there that help make the web more beautiful.
Typography enthusiasts likely already know how to identify fonts by name, but it’s always useful to explore visually similar fonts when you feel like changing up your options. Design consultant…
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- But with AutoDraw, Google is launching a new experiment today that uses machine learning algorithms to match your doodles with professional drawings to make you look like you know what you’re doing.
- Artists who want to donate their drawings to the project can do that here, by the way.
- This project actually uses the same technology as Google’s QuickDraw experiment.
- QuickDraw is more of a game, though, where you’re trying to draw a given object and hope that the AI algorithms recognize it within 20 seconds.
- With AutoDraw, you get more freedom to experiment, and, while you could read all about it here, it’s probably best you head over to AutoDraw.com and give it a
Drawing isn’t for everyone. I, for one, am definitely not very good at it. But with AutoDraw, Google is launching a new experiment today that uses machine..
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Originally published by Jason Brownlee in 2013, it still is a goldmine for all machine learning professionals. The algorithms are broken down in several categ…
Continue reading “A Tour of Machine Learning Algorithms”
- As inventors rush to create mind-blowing bits of kit that have the power to transform our daily lives forever, is there anyone out there pausing to think about the real impacts of technology on our lives, our psyches and our society?
- In the following TED talks, you’ll be able to navigate all the possibilities, and equip yourself with wisdom that will carry you through the changes.
- Apart from a paycheck, there are intangible values that, Barry Schwartz suggests, our current way of thinking about work simply ignores.
- Lisa Gansky, author of “The Mesh,” talks about a future of business that’s about sharing all kinds of stuff, either via smart and tech-enabled rental or, more boldly, peer-to-peer.
- In this talk about the future of work, economist David Autor addresses the question of why there are still so many jobs and comes up with a surprising, hopeful answer.
5 TED talks for anyone interested in the changing work landscape
Continue reading “Spotlight”