Top 10 Things Unfolded in Google I/O 2017

Raj Sanghvi — Mon, 29 May 2017 04:57:08 +0000

It’s a while already since Google I/O 2017 concluded, but even now, the tech world is throbbing with anticipation for the release of the new insane technologies. As it was I/O’s 10th anniversary, everybody was expecting something huge – well, at least the app developers got their share. But as there were over 100 new updates, it’s rather challenging to extract the essentials.

Therefore, to help you out, here are the 10 biggest announcements at Google I/O.

Android O

Google announced that there were now over 2 billion Android users! And accompanied with this news, they launched the beta version of their new OS, Android O. It comes with several new luring features such as: Picture in Picture, Notification Dots, Autofill, and many more. So, if you are an app developer, get started now by migrating your apps to Android O.

Android Go

You’d think with 2 billion users Google would be satisfied – well, no. It is now targeting the next billion, that is, users who survive with low-cost phones. Smartphones with less than 1GB of RAM accounted for more than one-fourth of the total shipment in India during Q1 2017. And for that, Google is releasing Android Go next year, an OS which can run on less than 1GB of memory! If you want reach out to a bigger market to gain an edge over your competitors, it’s time to start developing “Lite” apps.

Google Assistant

Google is rapidly going from “Mobile first to AI first”, and therefore, invested a lot of time presenting the updates for Google Home and Google Assistant. First and foremost, Assistant is expanding to iOS and will be available to iPhones and iPads.

Starting today, we’re bringing the #GoogleAssistant to iPhones. Whether at home or on the go, your Assistant is here to help. #io17 pic.twitter.com/a6T20HwnU9

— Google (@Google) May 17, 2017

Furthermore, now you can also type, instead of just talking to your assistant – which honestly is a huge relief! The third major upgrade is the integration of Google Lens, which we’ll discuss in just a moment.

Google Home

Google Home, at long last, can now place calls in US and Canada for free! Connect your Google speakers with Home, and you can experience hands-free calling. This major update makes it a close competitor to Amazon’s Echo. The device can now be connected by Bluetooth to listen to music and songs. It can also give visual response if connected to an iPhone, Chromecast or Android device. Lastly, Home can now give revised updates on your schedule, for example, ask you to leave early for a meeting if there is more traffic. It was evident at I/O that Google is putting in great effort to make Home as essential as a smartphone.

Google Lens

http://www.bitcot.com/wp-content/uploads/2018/11/Google_lens.mp4

The future tech giants will be those who can conquer AI today. At Google I/O, CEO Sundar Pichai announced a new technology called Google Lens. It will be integrated with Assistant, and will not only see, but also understand. Using powerful Machine Vision algorithms, it will help you identify objects and scenes around you. For the demo, Google pointed the camera at a flower, and Lens immediately identified which flower it was! Pichai also showed how convenient it can now be to connect to your home’s wifi – all you have to do is take a picture of your wifi sticker and the phone will connect! As a third example, you can point your phone’s camera at a restaurant, and Lens will give you the information of its name, rating and other information. With the integration with Assistant, you can now take a pic of your concert ticket and ask Assistant to set a reminder based on it! Lastly, you can also get live translation. As a demo, Scott Huffman pointed his phone to a Japanese sign and asked “What does it say?”, and got the immediate translation!

Google Photos

“More than 500 million people use Google Photos every month, backing up more than 1.2 billion photos and videos per day” Google tweeted. Therefore now, Google Photos will enable Suggested Sharing. When you take a photo of your friend, Google will automatically suggest that you share it with him or her. It also introduce Sharing Libraries, which will let families share picture libraries with other members. Lastly, Google Photos will automatically enhance and clean your photos.

Kotlin

Java is currently the most popular programming language for Android app developers. But Google wants to change that with the introduction of Kotlin. This new programming language, widely compared to Apple’s Swift, attempts to ease app development, enables clearer syntax and helps develop faster apps. For a demo, Google showed how a dozen of lines of Java code could be replaced by a single one of Kotlin!

Virtual Reality

Source: Google Events

Google Daydream project for VR got a major upgrade. Conjoined with Qualcomm, Google will now release standalone VR headsets. So now, you won’t need a phone, wires or PC to get your new virtual experience. Furthermore, it will have better tracking, most sophisticated apps and better user experience.

TPU

As already mentioned, Google’s future depends on AI. That’s why, in his keynote speech, Sundar Pichai announced the new Tensor Processing Unit (TPU), which are next-generation chips to enhance machine learning algorithms. These new chips will significantly speed up Google’s platform for cloud computing. Additionally, as the TPUs are optimized to work with TensorFlow, Google’s open-source deep learning platform, we can expect to soon have powerful machine learning apps in our Android devices.

All Things Android

Several new updates were announced for Android developers. First, is the release of the new Android Studio 3, which will support Kotlin, enable faster Gradle build and ease app development with other tools. Second, Android Instant Apps are finally available to all developers. Instant Apps lets users run them without installing! Third, Android Things enable developers to create connected devices with greater ease, thus letting them explore the world of IoT.

These are just the top 10 announcements at Google I/O 2017. Go ahead and check out the full list of Google announcements here.

The Difference between Artificial Intelligence, Machine Learning and Deep Learning

Raj Sanghvi — Wed, 05 Apr 2017 05:42:29 +0000

Today, read any tech article or news and you will be fired with the terms “Artificial Intelligence”, “Machine Learning” and “Deep Learning”. The biggest corporate giants Google, IBM, Facebook, Microsoft, and Amazon are voraciously acquiring Artificial Intelligence startups and companies. In just 3 months of 2017, 34 acquisitions were made. Forrester in the new report, “Prediction 2017: Artificial Intelligence Will Drive the Insights Revolution”, predicts a 300% increase in investment in Artificial Intelligence from 2016 to 2017. The report further proceeds to say that “insight-driven businesses will steal $ 1.2 trillion per annum from their less-informed peer by 2020.” Therefore, it is a worthy investment to disambiguate between the terms Artificial Intelligence, Machine Learning, and Deep Learning and explore the 20 best platforms.

Artificial Intelligence (AI)

Artificial Intelligence, or simply AI, is the broad umbrella term describing computer systems attempting to mimic human-like intelligence. John McCarthy, who coined the term in 1956, defines it as “the science and engineering of making intelligent machines.” Today, the areas of AI technology are primarily Robotics, Machine Learning, Machine Vision and Natural Language Processing. But the key benefit of AI in business is Predictive Analytics. Using AI algorithms, enterprises can grow exponentially to gain a significant competitive advantage over their peers. Venture Scanner reveals the exponential growth of funding in AI startups, with 2016 seeing over $ 2.5 Billion.

Machine Learning (ML)

The subfield of AI called Machine Learning (ML) focuses on developing algorithms that can help computer systems learn automatically, without being explicitly programmed. To accomplish this task, a wide range of algorithms have been developed such as Linear Regression, Logistic Regression, Support Vector Machines (SVM), K-Means, Decision Trees, Random Forests, Naive Bayes, PCA and lastly, Artificial Neural Networks (ANN). Venture Scanner reveals that over $ 3.5 billion has been invested in ML applications with over 400 companies investing in the field.

Deep Learning (DL)

But today, the new buzzword ruling the market is Deep Learning (DL), and this technique was born out of ANNs. Not only is it insanely popular, but it is slowly wiping out all other techniques of ML. Deep Learning uses multi-layered neural nets and learns by crunching a large amount of data. Though the core idea was presented in the ’60s, it is only today with the availability of data and powerful Graphical Processing Units (GPUs) that it proved successful. The recent accomplishments of DL were in the field of Machine Vision, Machine Translation, Speech Recognition, Automated Game Playing and Self Driving Vehicles.

20 Best Platforms for AI

Currently, instead of selling their AI software directly, the tech giants are developing platforms to implement Machine Learning and Deep Learning, which will allow customers to build mobile applications on them. And therefore, even smaller companies can develop state-of-the-art software using AI without getting lost in the nitty-gritty of the algorithmic technicalities. Here are 20 of the most popular platforms and APIs:

Today in the world, AI is the biggest game-changer which is causing technology to advance faster than ever before. With the huge availability of data and open-source platforms, it is extremely easy for enterprises to implement AI. Therefore, if you fail to plunge into AI today, you might just find yourself out of business in a few years.

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