Collaborating Authors


Brave's privacy-focused Google alternative lets you customize your search rankings


Brave is probably best known among hardcore geeks as one of Chrome's challengers. But for awhile now, the company has offered more than just a privacy-minded browser. A year ago, it launched the beta for a search engine, too--and now, on its first anniversary, Brave Search has hit a milestone of 2.5 billion queries, with a peak of 14.1 million queries in one day. For a nascent search engine, these numbers are big. As Brave claims in a blog post, it's won this achievement faster than Google (who took over a year to meet the same goal), plus run circles around DuckDuckGo. Its privacy-oriented rival took four years to cross the same threshold.

Here's how Google's using ML to improve Chrome


Google on Thursday shared a few ways it's using machine learning to improve the Chrome browser, including reducing the number of annoying notifications that pop up. All of the latest updates are all powered by on-device machine learning models, so user data doesn't have to leave the device. For a less disruptive web browsing experience, Google is using ML to determine when a user may want to interact with a notification permission prompt. In the next release of Chrome, the browser will use an on-device model to predict how a person is likely to respond to a permission prompt. If the user is likely to reject it, the browser will silence it.

Exploring Neural Networks Visually in the Browser


While teaching myself the basics of neural networks, I was finding it hard to bridge the gap between the foundational theory and a practical "feeling" of how neural networks function at a fundamental level. I learned how pieces like gradient descent and different activation functions worked, and I played with building and training some networks in a Google Colab notebook. Modern toolkits like Tensorflow handle the full pipeline from data preparation to training to testing and everything else you can think of - all behind extremely high-level, well-documented APIs. The power of these tools is obvious. Anyone can load, run, and play with state of the art deep learning architectures in GPU-accelerated Python notebooks instantly in the web browser.

Microsoft Edge taps AI to make grainy images look nice and crisp in your browser


If images begin to look sharper on Microsoft Edge compared to other browsers, there's a reason for that. Microsoft is building in what it calls a "Turing Image Super Resolution engine" into Microsoft Edge, "upscaling" low-resolution images with higher fidelity. In effect, Edge will create a higher-resolution image using artificial intelligence, where it didn't exist before. Upscaling isn't new; Adobe Lightroom's Super Resolution allows you to upscale a 12 megapixel image to 48MP, for example, to print larger prints. TopazLabs' Gigapixel AI is a dedicated, paid tool to do the same, and there are other free services available on the Web that will perform the same services with varying results.

My First Impression Trying Python on Browser


Whenever we debate with other devs about the best programming language, we talk about JavaScript and Python for hours. Both are powerful, flexible languages that are dominating the world today. But a dead end to Python is its inability to run on browsers. JavaScript (JS), with the discovery of Node, runs on almost any platform. It even has modules to build machine learning algorithms.

How to Easily Build Your First Machine Learning Web App in Python


One of the coolest parts of building machine learning models is sharing the models we built with others. No matter how many models you've built, if they stay offline, only very few people will be able to see what you've accomplished. This is why we should deploy our models, so anyone can play with them through a nice UI. Flask is a Python framework that lets us develop web applications easily. After following this guide, you'll be able to play with a simple machine learning model in your browser as shown in the gif below.

Apple, Google, and Microsoft Team Up to Vanquish the Password


We've been promised the end of password-based logins on the internet for a very long time, but now it seems that promise may finally be fulfilled. The FIDO Alliance, an industry group aimed at standardizing authentication methods online, announced that its passwordless sign-on method has received support from the big browser builders: Apple, Microsoft, and Google. That means that later this year you will be able to sign in to your various web accounts across the internet without using a password in all the major browsers. If you use a modern smartphone, you'll recognize how this works. Instead of asking you to enter a password, websites will push a notification to your phone that prompts you to verify your identity.

Amazon Echo Show 15 review: bigger Alexa is good, but not yet better

The Guardian

The Echo Show 15 is Amazon's biggest Alexa smart display and is designed to be a command centre or digital noticeboard for all the family. It is considerable larger than the rest of Amazon's Echo Show devices, which were recently given a motorised screen and small desk-ready displays. That illusion is furthered by its wall-mountable form – it is designed to be hung in a central place like the digital equivalent of the pinboards common to kitchens of homes of the 1980s, and can be mounted in landscape or portrait orientation. It can be bought with a stand for £30 more if you would rather not screw 2.2kg of technology into your wall. The 1080p touchscreen is bright and crisp when viewed at arm's reach.

Deep Learning In Javascript


Today is the day you build a Neural Network in Javascript.Deep Learning is ushering in a sea change in the way we build software. Andrew Ng famously refers to AI as the "New Electricity": a change destined to become as ubiquitous as electricity, imbued in every product around us, that will revolutionize how we interact with technology.Deep Learning has traditionally required vast server farms of specialized GPU chips, a PhD degree, and huge petabytes of data. Recently, however, - just this year, in fact - its become feasible to deploy and train cutting-edge Neural Networks in your browser, using Javascript. Deep Learning In Javascript will teach you how to build a Neural Network in Javascript in your browser, today.The Future of Deep Learning Is In Edge DevicesConsider: 1) Apple's new NPU chip - specialized for Deep Learning - features a 60x increase over the 2017 model. We're just in the opening rounds of specialized hardware bringing AI to your computer and phone.2) Consumers are more conscious of privacy than ever before. Techniques that can keep Deep Learning on-device, without ever hitting a remote server, allow you to leverage Deep Learning techniques without handling people's data.3) Many types of sensor data - video, audio, or cutting-edge AR and VR techniques - are too big and slow to send back and forth to a remote server for realtime processing. Leveraging Deep Learning in the browser lets you handle sensor data in realtime with no lag.Deep Learning is coming to the computer on your desk and the phone in your pocket. And guess which technology is well positioned to take advantage of this change? You guessed it: Javascript.What This Book CoversThis book is aimed at teaching Javascript developers how to leverage Deep Learning in the browser today. It's aimed at hackers looking to jump in quickly and learn through coding.This book includes:* An overview of how Deep Learning works, various approaches and when to use them* Techniques for manipulating, cleaning, and processing datasets, and how to effectively work with smaller datasets* How Image Recognition works, and how to interpret what a Neural Network "sees" when it looks at an image* How to effectively train a model in your browser, and tune it for better performance* How to take models built by others and leverage them in your apps, tweaking them for your specific use case* A step-by-step walkthrough of how to build an Image Classifier in your browser, from scratchToday is the day you build a Neural Network in Javascript.FAQWhat happens after I purchase?You'll get an email delivery with the PDF, Kindle (.mobi), and .epub files. You'll also be subscribed to receive future updates of the book for free.Do I need a math or statistics background to use this book?No! Math or Statistics background is not required. We will touch on theory as it applies to the Deep Learning models you will build, but there will be little-to-no math or statistics.Do I need to know Javascript to use this book?We'll be using modern Javascript to demonstrate techniques and build the Neural Networks and spending little time delving into Javascript. However, a passing familiarity should be all you need.What if this book is too advanced for me?Unlimited money-back guarantee: if you're not happy with your purchase, email and you will get your money back, no questions asked (well, I will ask you how the book could be improved!)What if this book is not advanced enough for me?Take advantage of the unlimited money-back guarantee!What if I buy this book today, and next year it's out of date?Buying the book today guarantees you unlimited access to future updates in digital format.Also, though the tools will change, the basics of building a Neural Network and techniques for training and tuning will stay the same.

Review: Vizy Linux-Powered AI Camera


Vizy is a Linux-based "AI camera" based on the Raspberry Pi 4 that uses machine learning and machine vision to pull off some neat tricks, and has a design centered around hackability. I found it ridiculously simple to get up and running, and it was just as easy to make changes of my own, and start getting ideas. I was running pre-installed examples written in Python within minutes, and editing that very same code in about 30 seconds more. Even better, I did it all without installing a development environment, or even leaving my web browser, for that matter. I have to say, it made for a very hacker-friendly experience.