Welcome!

Related Topics: @ThingsExpo, Machine Learning , Artificial Intelligence

@ThingsExpo: Article

How Is Apple Using Machine Learning? | @ThingsExpo #AI #ML #DL #DX #IoT

Today, machine learning is found in almost every product and service by Apple

Today, machine learning is found in almost every product and service by Apple. They use deep learning to extend battery life between charges on their devices and detect fraud on the Apple store, recognize the locations and faces in your photos, and help Apple choose news stories for you.

The concept of AI (Artificial Intelligence) has been the subject of many discussions lately. According to some predictions, AI will have the ability to learn by itself, outclassing the capabilities of the human brain, and even manage to fight for equal rights by the year 2100. Even though these are (still) just speculations and predictions, companies like Apple are developing and implementing machine learning technology, which is still in its infancy. How is Apple using machine learning?

Apple's beginnings with deep learning technologies
Let's start with Apple's beginnings with using AI. It was during the 1990s, when the company was using certain machine learning techniques in its products with handwriting recognition. This machine learning techniques were, of course, much more primitive.

Today, machine learning is found in almost every product and service by Apple. They use deep learning to extend battery life between charges on their devices and detect fraud on the Apple store, recognize the locations and faces in your photos, and help Apple choose news stories for you. Machine learning determines whether the owners of Apple Watch cloud are really exercising or just perambulating. It figures out whether you'd be better off switching to the cell network due to a weak Wi-Fi signal.

Apple's smart assistant
In 2011, Apple integrated a smart assistant into its operating system, and was the first tech giant to pull it off. The name of that smart assistant is Siri, and it was an adaptation of a standalone app that Apple had purchased (along with the app's developing team). Siri had ‘exploded', with ecstatic initial reviews. However, over the next few years, users wanted to see Apple deal with Siri's shortcomings. Thus, Siri got a ‘brain transplant' in 2014.

Siri's voice recognition was moved to a neural-net based system. The system began leveraging machine learning techniques, including DNN (deep neural networks), long short-term memory units, convolutional neural networks, n-grams, and gate recurrent units. Siri was operational with deep learning, while it still looked the same.

Every iPhone user has come across Apple's AI, for example, when you swipe on your device screen to get a shortlist of all the apps that you're most likely to open next, or when it identifies a caller who's not memorized in your contact list. Whenever a map location pops out for the accommodation you've reserved, or when you get reminded of an appointment that you forgot to put into your calendar. Apple's neural-network trained system watches as you type, detecting items and key events like appointments, contacts, and flight information. The information is not collected by the company, but stays on your iPhone and in cloud-based storage backups - the information is filtered so it can't be inferred. All this is made possible by Apple's adoption of neural nets and deep learning.

During this year's WWDC, Apple presented how machine learning is used by a new Siri-powered watch face to customize its content in real-time, including news, traffic information, reminders, upcoming meetings, etc., when they are supposed to be most relevant.

Making mobile AI faster with new machine learning API
Apple wants to make the AI on your iPhone as powerful and fast as possible. A week ago, the company unveiled a new machine learning API, named Core ML. The most important benefit of Core ML will be faster responsiveness of the AI when executing on the Apple Watch, iPad, and iPhone. What would this cover? Well, everything from face recognition to text analysis, with an effect of a wide range of apps.

The essential machine learning tools that the new Core ML will support include neural networks (deep, convolutional, and recurrent), tree ensembles, and linear models. As for privacy, the data that's used for improving user experience won't leave the users' tablets and phones.

The announcement of making AI work better on mobile devices became an industry-wide trend, meaning that other companies might be trying that as well. As for Apple, it's clear that deep learning technology has changed their products. However, it's not clear whether it's changing the company itself. Apple carefully controls the user experience, with everything being precisely coded and pre-designed. However, engineers must take a step back (when using machine learning) and let the software discover solutions by itself. Will machine learning systems have a hand in product design, if Apple manages to adjust to the modern reality?

More Stories By Nate Vickery

Nate M. Vickery is a business consultant from Sydney, Australia. He has a degree in marketing and almost a decade of experience in company management through latest technology trends. Nate is also the editor-in-chief at bizzmarkblog.com.

Latest Stories
"DX encompasses the continuing technology revolution, and is addressing society's most important issues throughout the entire $78 trillion 21st-century global economy," said Roger Strukhoff, Conference Chair. "DX World Expo has organized these issues along 10 tracks with more than 150 of the world's top speakers coming to Istanbul to help change the world."
"We focus on SAP workloads because they are among the most powerful but somewhat challenging workloads out there to take into public cloud," explained Swen Conrad, CEO of Ocean9, Inc., in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"As we've gone out into the public cloud we've seen that over time we may have lost a few things - we've lost control, we've given up cost to a certain extent, and then security, flexibility," explained Steve Conner, VP of Sales at Cloudistics,in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We provide IoT solutions. We provide the most compatible solutions for many applications. Our solutions are industry agnostic and also protocol agnostic," explained Richard Han, Head of Sales and Marketing and Engineering at Systena America, in this SYS-CON.tv interview at @ThingsExpo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We are focused on SAP running in the clouds, to make this super easy because we believe in the tremendous value of those powerful worlds - SAP and the cloud," explained Frank Stienhans, CTO of Ocean9, Inc., in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"Peak 10 is a hybrid infrastructure provider across the nation. We are in the thick of things when it comes to hybrid IT," explained , Chief Technology Officer at Peak 10, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"I think DevOps is now a rambunctious teenager – it’s starting to get a mind of its own, wanting to get its own things but it still needs some adult supervision," explained Thomas Hooker, VP of marketing at CollabNet, in this SYS-CON.tv interview at DevOps Summit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We are still a relatively small software house and we are focusing on certain industries like FinTech, med tech, energy and utilities. We help our customers with their digital transformation," noted Piotr Stawinski, Founder and CEO of EARP Integration, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We've been engaging with a lot of customers including Panasonic, we've been involved with Cisco and now we're working with the U.S. government - the Department of Homeland Security," explained Peter Jung, Chief Product Officer at Pulzze Systems, in this SYS-CON.tv interview at @ThingsExpo, held June 6-8, 2017, at the Javits Center in New York City, NY.
Everything run by electricity will eventually be connected to the Internet. Get ahead of the Internet of Things revolution and join Akvelon expert and IoT industry leader, Sergey Grebnov, in his session at @ThingsExpo, for an educational dive into the world of managing your home, workplace and all the devices they contain with the power of machine-based AI and intelligent Bot services for a completely streamlined experience.
Any startup has to have a clear go –to-market strategy from the beginning. Similarly, any data science project has to have a go to production strategy from its first days, so it could go beyond proof-of-concept. Machine learning and artificial intelligence in production would result in hundreds of training pipelines and machine learning models that are continuously revised by teams of data scientists and seamlessly connected with web applications for tenants and users.
"We're here to tell the world about our cloud-scale infrastructure that we have at Juniper combined with the world-class security that we put into the cloud," explained Lisa Guess, VP of Systems Engineering at Juniper Networks, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"I will be talking about ChatOps and ChatOps as a way to solve some problems in the DevOps space," explained Himanshu Chhetri, CTO of Addteq, in this SYS-CON.tv interview at @DevOpsSummit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We are an IT services solution provider and we sell software to support those solutions. Our focus and key areas are around security, enterprise monitoring, and continuous delivery optimization," noted John Balsavage, President of A&I Solutions, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
Your homes and cars can be automated and self-serviced. Why can't your storage? From simply asking questions to analyze and troubleshoot your infrastructure, to provisioning storage with snapshots, recovery and replication, your wildest sci-fi dream has come true. In his session at @DevOpsSummit at 20th Cloud Expo, Dan Florea, Director of Product Management at Tintri, provided a ChatOps demo where you can talk to your storage and manage it from anywhere, through Slack and similar services with...