Welcome!

Mobile IoT Authors: Pat Romanski, Elizabeth White, Yeshim Deniz, Liz McMillan, Kevin Benedict

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.

IoT & Smart Cities Stories
The challenges of aggregating data from consumer-oriented devices, such as wearable technologies and smart thermostats, are fairly well-understood. However, there are a new set of challenges for IoT devices that generate megabytes or gigabytes of data per second. Certainly, the infrastructure will have to change, as those volumes of data will likely overwhelm the available bandwidth for aggregating the data into a central repository. Ochandarena discusses a whole new way to think about your next...
Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...
DXWorldEXPO LLC announced today that Big Data Federation to Exhibit at the 22nd International CloudEXPO, colocated with DevOpsSUMMIT and DXWorldEXPO, November 12-13, 2018 in New York City. Big Data Federation, Inc. develops and applies artificial intelligence to predict financial and economic events that matter. The company uncovers patterns and precise drivers of performance and outcomes with the aid of machine-learning algorithms, big data, and fundamental analysis. Their products are deployed...
All in Mobile is a place where we continually maximize their impact by fostering understanding, empathy, insights, creativity and joy. They believe that a truly useful and desirable mobile app doesn't need the brightest idea or the most advanced technology. A great product begins with understanding people. It's easy to think that customers will love your app, but can you justify it? They make sure your final app is something that users truly want and need. The only way to do this is by ...
CloudEXPO | DevOpsSUMMIT | DXWorldEXPO are the world's most influential, independent events where Cloud Computing was coined and where technology buyers and vendors meet to experience and discuss the big picture of Digital Transformation and all of the strategies, tactics, and tools they need to realize their goals. Sponsors of DXWorldEXPO | CloudEXPO benefit from unmatched branding, profile building and lead generation opportunities.
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
Cell networks have the advantage of long-range communications, reaching an estimated 90% of the world. But cell networks such as 2G, 3G and LTE consume lots of power and were designed for connecting people. They are not optimized for low- or battery-powered devices or for IoT applications with infrequently transmitted data. Cell IoT modules that support narrow-band IoT and 4G cell networks will enable cell connectivity, device management, and app enablement for low-power wide-area network IoT. B...
The hierarchical architecture that distributes "compute" within the network specially at the edge can enable new services by harnessing emerging technologies. But Edge-Compute comes at increased cost that needs to be managed and potentially augmented by creative architecture solutions as there will always a catching-up with the capacity demands. Processing power in smartphones has enhanced YoY and there is increasingly spare compute capacity that can be potentially pooled. Uber has successfully ...
SYS-CON Events announced today that CrowdReviews.com has been named “Media Sponsor” of SYS-CON's 22nd International Cloud Expo, which will take place on June 5–7, 2018, at the Javits Center in New York City, NY. CrowdReviews.com is a transparent online platform for determining which products and services are the best based on the opinion of the crowd. The crowd consists of Internet users that have experienced products and services first-hand and have an interest in letting other potential buye...
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...