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Introduction to Federated Learning

#artificialintelligence

There are over 5 billion mobile device users all over the world. Such users generate massive amounts of data--via cameras, microphones, and other sensors like accelerometers--which can, in turn, be used for building intelligent applications. Such data is then collected in data centers for training machine/deep learning models in order to build intelligent applications. However, due to data privacy concerns and bandwidth limitations, common centralized learning techniques aren't appropriate--users are much less likely to share data, and thus the data will be only available on the devices. This is where federated learning comes into play. According to Google's research paper titled, Communication-Efficient Learning of Deep Networks from Decentralized Data [1], the researchers provide the following high-level definition of federated learning: A learning technique that allows users to collectively reap the benefits of shared models trained from [this] rich data, without the need to centrally store it.


Smart Artificial Intelligence Needs An Open (Source) Classroom

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As schoolchildren and students of all ages will widely confirm after the Covid-19 (Coronavirus) pandemic with the imposition of home-schooling for many, it's harder to learn in a vacuum. It's not impossible, but it's generally agreed that we humans learn better in groups through mutual discovery, intercommunication on problem-solving and through the general process and pursuit of team-based challenges and goals. This, after all, is why we have schools. Could the same need for interconnected cross-fertilization also help computers to'learn' as they build their data-powered Artificial Intelligence (AI) knowledge bases and software-driven analytics engines? More examples of open AI are surfacing all the time.


Smart Artificial Intelligence Needs An Open (Source) Classroom

#artificialintelligence

Because of the corona regulations, special hygiene measures apply. Furthermore, the pupils are not taught in the full class size. As schoolchildren and students of all ages will widely confirm after the Covid-19 (Coronavirus) pandemic with the imposition of home-schooling for many, it's harder to learn in a vacuum. It's not impossible, but it's generally agreed that we humans learn better in groups through mutual discovery, intercommunication on problem-solving and through the general process and pursuit of team-based challenges and goals. This, after all, is why we have schools.


9 Augmented Reality Trends to Watch in 2020: The Future Is Here - MobiDev

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Brands, development companies, agencies, and startups rapidly followed, taking advantage of their potential. ARKit 2 landed at WWDC 18, with Apple introducing the USDZ format that makes adding models, data and animations to AR landscapes simple.


Measuring AI Performance On Mobile Devices And Why It Matters

#artificialintelligence

Artificial Intelligence And Machine Learning Are More Important Than You Might Think For Mobile ... [ ] Devices AI is a common buzz word these days, but most consumers probably aren't aware how it's interwoven in their everyday lives. Some of us in the analyst and tech press communities may also scoff at how often the term is used for some technologies that hardly resemble true artificial intelligence. That said, there are a few platforms, beyond just powerful data centers, that are a natural for AI processing and the NNs (Neural Networks) that drive them. One of those is AI inferencing (using the AI to infer information, versus training an NN) at the edge, and in your pocket, with a smartphone. As you might imagine, smartphone platforms from Android to Apple vary greatly, but there are common workloads like speech-to-text translation, and recommender engines (like Google Assistant and Siri), that make heavy use of common AI NN models, and they do so on-device for speed and latency advantages.


Facebook's 3D Photos feature now simulates depth for any image

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In late 2018, Facebook launched 3D Photos, a feature that leverages depth data to create images that look flat but that can be examined from different angles using virtual reality (VR) headsets, through Facebook on the web or Facebook's mobile apps. It initially required a depth map file on desktop or dual-camera phones like the Galaxy Note10 or iPhone 11, but starting today, 3D Photos is compatible with any modern handset with a single camera -- specifically an iPhone 7 or higher or a midrange or better Android device. Facebook says that "state-of-the-art" machine learning techniques made the expanded phone support possible. Newly deployed AI models can infer the 3D structure of images without depth data, regardless of the images' ages or origins. It even works with selfies, paintings, and complex scenes.


How COVID-19 is Transforming E-Commerce

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Just over 306 million Americans are affected by stay-at-home orders, nearly 95% of the U.S. population. COVID-19 will forever change retailing, and its initial impact on e-Commerce is creating challenges to online selling & service no one imagined in January. Mobile devices are the most popular device for online shopping by a wide margin. E-Commerce and online retailers' supply chains, order management, and fulfillment systems are all being tested by the triple-digit order and revenue growth going on today. And best of all, more energy and intensity is being put into improving customer experiences online.


CoCoPIE: A software solution for putting real artificial intelligence in smaller spaces

#artificialintelligence

Bit by bit, byte by byte, artificial intelligence has been working its way into public consciousness and into everyday computer use. Artificial intelligence and deep learning have been deeply woven into more and more aspects of end-user computing. Smartphones and other mobile devices use AI as well. Up until now, the artificial intelligence work has been done in the cloud, but a new approach to software design aims to arm mobile devices with real artificial-intelligence capability. "A mobile device is very resource-constrained," explained William & Mary computer scientist Bin Ren.


How 5G Will Unleash AI

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When it comes to the 5G roll-out, AI will definitely be supercharged. "AI is a huge priority," said John Smee, who is the VP of engineering and head of 5G R&D for Qualcomm. "We are seeing at transformation happening, with AI going from the cloud to being distributed, such as on the edge or IoT devices." In preparation for this, Qualcomm has been embedding AI capabilities on its chips. Note that its AI engine has applications for cameras, battery life, security and gaming--allowing for neural network processing.


How 5G Will Unleash AI

#artificialintelligence

When it comes to the 5G roll-out, AI will definitely be supercharged. "AI is a huge priority," said John Smee, who is the VP of engineering and head of 5G R&D for Qualcomm. "We are seeing at transformation happening, with AI going from the cloud to being distributed, such as on the edge or IoT devices." In preparation for this, Qualcomm has been embedding AI capabilities on its chips. Note that its AI engine has applications for cameras, battery life, security and gaming--allowing for neural network processing.