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Apple Watch timed for April 24

Apple has unveiled the Apple Watch, which will allow users to read and reply to messages, stay fit with the built-in accelerometer and heart rate monitor and even pay for purchases using Apple Pay.

Apple has announced that Apple Watch, the newest addition to Apple’s ecosystem, will be available on Friday, April 24 to customers in Australia, Canada, China, France, Germany, Hong Kong, Japan, the UK and the US.

Apple describes the watch as “an incredibly accurate timepiece, an intimate and immediate communication device and a groundbreaking health and fitness companion”. It says that it is highly customisable for personal expression, and “brings an entirely new way to receive information at a glance and interact with the world through third-party app experiences designed specifically for the wrist”.

“Apple Watch begins a new chapter in the way we relate to technology and we think our customers are going to love it,” said Tim Cook, Apple’s CEO. “We can’t wait for people to start wearing Apple Watch to easily access information that matters, to interact with the world, and to live a better day by being more aware of their daily activity than ever before.”

“Conceived, designed and developed as a singular product, Apple Watch merges hardware and software like never before,” said Jony Ive, Apple’s senior vice president of Design. “In Apple Watch, we’ve created three beautifully curated collections with a software architecture that together enable unparalleled personalisation in a wearable device.”

Apple Watch introduces new technologies, including the Digital Crown, an innovative way to scroll, zoom and navigate fluidly without obstructing the display. The Retina display with Force Touch on Apple Watch senses the difference between a tap and a press, providing a new way to quickly and easily access relevant controls. The new Taptic Engine discreetly delivers a gentle tap on your wrist whenever the user receives a notification or message.

Apple-Watch-logo-main1

Apple provided the following information on the Apple Watch:

An extremely precise timepiece, Apple Watch keeps time to within 50 milliseconds of UTC, the universal time standard. Apple Watch can be personalised with watch faces ranging from traditional analogue such as the Chronograph face, to the information-rich Modular face, or beautifully animated butterflies and jellyfish on the Motion face. Apple Watch goes beyond telling time with specialised functions on the watch face—known in watchmaking as complications—such as the sunrise/sunset, upcoming calendar events or daily activity level. With multiple customisable watch faces and complications, Apple Watch enables millions of possible configurations. Swipe up from the watch face for Glances that quickly show you information you care about, such as the weather forecast, your current location on a map or the music you’re listening to.

Intimate & Immediate Communication Device

Apple Watch enables you to send messages, read email and answer calls to your iPhone right from your wrist. The Taptic Engine alerts you with a gentle tap so you won’t miss important notifications. With Digital Touch, Apple Watch allows you to communicate in all-new ways by sending a sketch, a tap or even the rhythm of your own heartbeat. Interact quickly and conveniently with the world around you with Apple Watch by paying for coffee using Apple Pay, boarding a plane with a Passbook boarding pass, or raising your wrist to ask Siri for turn-by-turn directions in Maps.

Groundbreaking Health & Fitness Companion

Apple Watch encourages you to sit less, move more and get some exercise every day. The Activity app provides a simple visual snapshot of your daily activity with three rings that measure active calories burned, brisk activity and how often you’ve stood up to take a break from sitting during the day. Apple Watch provides the detailed metrics you need during dedicated workout sessions for the most popular activities, such as walking, running and cycling through the Workout app. With an accelerometer, a built-in heart rate sensor, GPS and Wi-Fi from your iPhone, Apple Watch smartly uses the best sensors for different types of motion and provides a comprehensive picture of your all-day activity and workouts. The Activity app on iPhone collects your activity and workout data from Apple Watch so you can see your history in greater detail. Apple Watch uses this history to suggest personalised activity goals, reward fitness milestones and keep you motivated.

Apple Watch is available in two different sizes, 38 mm and 42 mm, and in three distinct collections—Apple Watch Sport, Apple Watch and Apple Watch Edition. Apple Watch Sport features a lightweight anodised aluminium case in silver and space grey with a Retina display protected by strengthened Ion-X glass and matching high-performance fluoroelastomer Sport Band in five colours. The Apple Watch collection features highly polished stainless steel and space black stainless steel cases with a Retina display protected by sapphire crystal. The Apple Watch collection comes with a choice of three different leather straps, a stainless steel link bracelet and Milanese loop, and a black or white Sport Band. Apple Watch Edition features cases specially crafted from custom rose or yellow 18-carat gold alloys developed to be twice as hard as standard gold, a Retina display protected by polished sapphire crystal and a choice of uniquely designed straps and bands with 18-carat gold clasps, buckles or pins.

The world’s most vibrant and innovative developer community has been creating all-new experiences specifically designed for Apple Watch. From requesting an Uber, checking in to your American Airlines flight, booking a bike for your Equinox class to remotely controlling your Honeywell Lyric thermostat while away, the possibilities for Apple Watch apps are endless. These experiences extend the functionality of your favourite iPhone apps, while delivering an innovative way to interact—right from your wrist. Popular apps such as Instagram, MLB.com At Bat, Nike+ Running, OpenTable, Shazam, Twitter, WeChat and more will also be available on Apple Watch. The new Apple Watch app that comes with iOS 8.2 on iPhone lets you browse, buy and download apps from the Apple Watch App Store.

Designed to be worn throughout your day, Apple Watch delivers up to 18-hour all-day battery life*** and comes with a unique charging solution that combines Apple’s MagSafe technology with inductive charging for a quick connection that simply snaps into place.

By design, the shopping experience for Apple Watch will be the most personalized Apple has ever offered. When Apple Watch becomes available for pre-order from the Apple Online Store on Friday, April 10, Apple retail stores and department store shop-in-shops will begin offering customers the chance to preview their choice of Apple Watch and try it on in-store.

Availability

Beginning April 10 in Australia, Canada, China, France, Germany, Hong Kong, Japan, the UK and the US, Apple Watch will be available for preview, try-on by appointment at Apple’s retail stores, and available for pre-order through the Apple Online Store. On April 24, Apple Watch will be available online or by reservation in Apple’s retail stores and select Apple Authorised Resellers in China and Japan. Customers who purchase online or in-store from Apple will be offered Personal Setup to customise and pair Apple Watch with their iPhone.

Apple Watch is available in three collections, Apple Watch Sport, Apple Watch, and Apple Watch Edition, crafted from custom rose or yellow 18-karat gold alloys.

Apple Watch will also be available to preview or try on at Galeries Lafayette in Paris, Isetan in Tokyo and Selfridges in London on April 10. Apple Watch will be for sale on April 24 at these select department store shop-in-shops, and at boutiques in major cities across the world including colette in Paris, Dover Street Market in London and Tokyo, Maxfield in Los Angeles and The Corner in Berlin.

Starting today customers can explore and choose their favourite Apple Watch in the Apple Online Store or through the Apple Store app for iPhone and iPad.

Apple Watch requires iPhone 5, iPhone 5c, iPhone 5s, iPhone 6 or iPhone 6 Plus running iOS 8.2. or later. iOS 8.2 will be available for download today.

* Follow Gadget on Twitter on @GadgetZA

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What’s left after the machines take over?

KIERAN FROST, research manager for software in sub-Saharan Africa for International Data Corporation, discusses the AI’s impact on the workforce.

One of the questions that we at the International Data Corporation are asked is what impact technologies like Artificial Intelligence (AI) will have on jobs. Where are there likely to be job opportunities in the future? Which jobs (or job functions) are most ripe for automation? What sectors are likely to be impacted first? The problem with these questions is that they misunderstand the size of the barriers in the way of system-wide automation: the question isn’t only about what’s technically feasible. It’s just as much a question of what’s legally, ethically, financially and politically possible.

That said, there are some guidelines that can be put in place. An obvious career path exists in being on the ‘other side of the code’, as it were – being the one who writes the code, who trains the machine, who cleans the data. But no serious commentator can leave the discussion there – too many people are simply not able to or have the desire to code. Put another way: where do the legal, financial, ethical, political and technical constraints on AI leave the most opportunity?

Firstly, AI (driven by machine learning techniques) is getting better at accomplishing a whole range of things – from recognising (and even creating) images, to processing and communicating natural language, completing forms and automating processes, fighting parking tickets, being better than the best Dota 2 players in the world and aiding in diagnosing diseases. Machines are exceptionally good at completing tasks in a repeatable manner, given enough data and/or enough training. Adding more tasks to the process, or attempting system-wide automation, requires more data and more training. This creates two constraints on the ability of machines to perform work:

  1. machine learning requires large amounts of (quality) data and;
  2. training machines requires a lot of time and effort (and therefore cost).

Let’s look at each of these in turn – and we’ll discuss how other considerations come into play along the way.

Speaking in the broadest possible terms, machines require large amounts of data to be trained to a level to meet or exceed human performance in a given task. This data enables the bot to learn how best to perform that task. Essentially, the data pool determines the output.

However, there are certain job categories which require knowledge of, and then subversion of, the data set – jobs where producing the same ‘best’ outcome would not be optimal. Particularly, these are jobs that are typically referred to as creative pursuits – design, brand, look and feel. To use a simple example: if pre-Apple, we trained a machine to design a computer, we would not have arrived at the iMac, and the look and feel of iOS would not become the predominant mobile interface. 

This is not to say that machines cannot create things. We’ve recently seen several ML-trained machines on the internet that produce pictures of people (that don’t exist) – that is undoubtedly creation (of a particularly unnerving variety). The same is true of the AI that can produce music. But those models are trained to produce more of what we recognise as good. Because art is no science, a machine would likely have no better chance of producing a masterpiece than a human. And true innovation, in many instances, requires subverting the data set, not conforming to it.

Secondly, and perhaps more importantly, training AI requires time and money. Some actions are simply too expensive to automate. These tasks are either incredibly specialised, and therefore do not have enough data to support the development of a model, or very broad, which would require so much data that it will render the training of the machine economically unviable. There are also other challenges which may arise. At the IDC, we refer to the Scope of AI-Based Automation. In this scope:

  • A task is the smallest possible unit of work performed on behalf of an activity.
  • An activity is a collection of related tasks to be completed to achieve the objective.
  • A process is a series of related activities that produce a specific output.
  • A system (or an ecosystem) is a set of connected processes.

As we move up the stack from task to system, we find different obstacles. Let’s use the medical industry as an example to show how these constraints interact. Medical image interpretation bots, powered by neural networks, exhibit exceptionally high levels of accuracy in interpreting medical images. This is used to inform decisions which are ultimately made by a human – an outcome that is dictated by regulation. Here, even if we removed the regulation, those machines cannot automate the entire process of treating the patient. Activity reminders (such as when a patient should return for a check-up, or reminders to follow a drug schedule) can in part be automated, with ML applications checking patient past adherence patterns, but with ultimate decision-making by a doctor. Diagnosis and treatment are a process that is ultimately still the purview of humans. Doctors are expected to synthesize information from a variety of sources – from image interpretation machines to the patient’s adherence to the drug schedule – in order to deliver a diagnosis. This relationship is not only a result of a technicality – there are ethical, legal and trust reasons that dictate this outcome.

There is also an economic reason that dictates this outcome. The investment required to train a bot to synthesize all the required data for proper diagnosis and treatment is considerable. On the other end of the spectrum, when a patient’s circumstance requires a largely new, highly specialised or experimental surgery, a bot will unlikely have the data required to be sufficiently trained to perform the operation and even then, it would certainly require human oversight.

The economic point is a particularly important one. To automate the activity in a mine, for example, would require massive investment into what would conceivably be an army of robots. While this may be technically feasible, the costs of such automation likely outweigh the benefits, with replacement costs of robots running into the billions. As such, these jobs are unlikely to disappear in the medium term. 
Thus, based on technical feasibility alone our medium-term jobs market seems to hold opportunity in the following areas: the hyper-specialised (for whom not enough data exists to automate), the jack-of-all-trades (for whom the data set is too large to economically automate), the true creative (who exists to subvert the data set) and finally, those whose job it is to use the data. However, it is not only technical feasibility that we should consider. Too often, the rhetoric would have you believe that the only thing stopping large scale automation is the sophistication of the models we have at our disposal, when in fact financial, regulatory, ethical, legal and political barriers are of equal if not greater importance. Understanding the interplay of each of these for a role in a company is the only way to divine the future of that role.

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LG unveils NanoCell TV range

At the recent LG Electronics annual Innofest innovation celebration in Seoul, Korea, the company unveiled its new NanoCell range: 14 TVs featuring ThinQ AI technology. It also showcased a new range of OLED units.

The new TV models deliver upgraded AI picture and sound quality, underpinned by the company’s second-generation α (Alpha) 9 Gen 2 intelligent processor and deep learning algorithm. As a result, the TVs promise optimised picture and sound by analysing source content and recognising ambient conditions.

LG’s premium range for the MEA market is headlined by the flagship OLED TV line-up, which offers a variety of screen sizes: W9 (model 77/65W9), E9 (model 65E9), C9 (model 77/65/55C9) and B9 (model 65/55B9).

NanoCell is LG’s new premier LED brand, the name intended to highlight outstanding picture quality enabled by NanoCell technology. Ensuring a wider colour gamut and enhanced contrast, says LG, “NanoColor employs a Full Array Local Dimming (FALD) backlight unit. NanoAccuracy guarantees precise colours and contrast over a wide viewing angle while NanoBezel helps to create the ultimate immersive experiences via ultra-thin bezels and the sleek, minimalist design of the TV.”

The NanoCell series comprises fourteen AI-enabled models, available in sizes varying from 49 to 77 inches (model 65SM95, 7565/55SM90, 65/55/49SM86 and 65/55/49SM81).

The LG C9 OLED TV and the company’s 86-inch 4K NanoCell TV model (model 86SM90) were recently honoured with CES 2019 Innovation Awards. The 65-inch E9 and C9 OLED TVs also picked up accolades from Dealerscope, Reviewed.com, and Engadget.

The α9 Gen 2 intelligent processor used in LG’s W9, E9 and C9 series OLED TVs elevates picture and sound quality via a deep learning algorithm (which leverages an extensive database of visual information), recognising content source quality and optimising visual output.

The α9 Gen 2 intelligent processor is able to understand how the human eye perceives images in different lighting and finely adjusts the tone mapping curve in accordance with ambient conditions to achieve the optimal level of screen brightness. The processor uses the TV’s ambient light sensor to measure external light, automatically changing brightness to compensate as required. With its advanced AI, the α9 Gen 2 intelligent processor can refine High Dynamic Range (HDR) content through altering brightness levels. In brightly lit settings, it can transform dark, shadow-filled scenes into easily discernible images, without sacrificing depth or making colours seem unnatural or oversaturated. LG’s 2019 TVs also leverage Dolby’s latest innovation, which intelligently adjusts Dolby Vision content to ensure an outstanding HDR experience, even in brightly lit conditions.

LG’s audio algorithm can up-mix two-channel stereo to replicate 5.1 surround sound. The α9 Gen 2 intelligent processor fine-tunes output according to content type, making voices easier to hear in movies and TV shows, and delivering crisp, clear vocals in songs. LG TVs intelligently set levels based on their positioning within a room, while users can also adjust sound settings manually if they choose. LG’s flagship TVs offer the realistic sound of Dolby Atmos for an immersive entertainment experience.

LG’s 2019 premium TV range comes with a new conversational voice recognition feature that makes it easier to take control and ask a range of questions. The TVs can understand context, which allows for more complex requests, meaning users won’t have to make a series of repetitive commands to get the desired results. Conversational voice recognition will be available on LG TVs with ThinQ AI in over a hundred countries.

LG’s 2019 AI TVs support HDMI 2.1 specifications, allowing the new 4K OLED and NanoCell TV models to display 4K content at a remarkable 120 frames per second. Select 2019 models offer 4K high frame rate (4K HFR), automatic low latency mode (ALLM), variable refresh rate (VRR) and enhanced audio return channel (eARC).

To find out more about LG’s latest TVs and home entertainment systems, visit https://www.lg.com/ae.

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