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How smart technology gets you to continue paying long after point of sale

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A common criticism of virtual assistants like Siri, Alexa, and Google Assistant is that they are always on, always listening, and always connected to the internet. It’s the only way they work.

For consumers who are rightfully skeptical of how tech companies big and small are collecting, analyzing, and making money off their data — even in anonymized form — the sudden proliferation of these always-connected smart devices is concerning. But there’s a reason that everything from televisions to cars are suddenly getting smarter.

For consumers wondering why it might feel increasingly harder to buy something dumb or disconnected, the reason is partly technical. Some of the products users enjoy today wouldn’t be possible — or, as good — without a connection to the internet.

But it’s also about money. With product margins thinner than ever, more companies are either re-building their old hardware businesses around online subscriptions, or monetizing data from people who are using their products for free.

In other words: giving every dishwasher, thermostat, and SUV an internet connection is one way for companies to keep making money after someone buys their product — whether through regular subscriptions, data collection, or some combination of the two.

As long as people believe they’re getting value — say, the convenience that smart speakers promise — they’re more willing to accept this new reality, according to Adam Wright, a senior analyst at the market research firm IDC who focuses on connected devices for consumers.

“People are increasingly becoming more comfortable with relinquishing a certain degree of privacy in favour of cheaper devices, cheaper services, better services, personalization, recommendations, things like that,” said Wright.

While it’s unlikely that every toaster or doorknob will eventually be smart, given the opportunity to make more money, it’s not hard to understand why companies are giving so many previously dumb products a tiny computer brain and an IP.

Knowledge in the cloud

Smart speakers and virtual assistants are a good example of this dichotomy in action.

Anytime you ask Google Assistant to set a timer, or Amazon Alexa to play one of your favourite songs, a recording of your voice is transmitted to a server in the cloud. The recording is analyzed to determine what you said, and the assistant figures out how to respond.

It’s technically possible to build a voice assistant that is able to recognize your voice and respond to basic queries offline — or, at the very least, without sending your recordings to a server in the cloud. But Allan Black, a professor at Carnegie Mellon University’s Language Technologies Institute, said it’s harder to offer a cutting-edge experience this way.

Some smart appliance makers will share information about how you use their products with third party businesses, who might then send you offers for things like detergent. (Rick Bowmer/The Associated Press)

For one, a connected voice assistant has access to all of the latest news, sports, weather, and other frequently updated information that would be impractical to store offline.

Recordings from millions of users of all different ages, genders, languages, and dialects can be used to make the voice recognition more accurate than from one person’s data alone. And all that data can help the assistant’s maintainers identify popular questions that haven’t been answered yet — or personalize answers to particular users.

Black acknowledged the “non-trivial privacy issue” of sending everyone’s data to the cloud. But “it would be much harder to get that benefit of these improvements if you only have it local and it’s never shared,” he explained.

Of course, doing all that work in the cloud doesn’t just make the experience better for users. It also gives the likes of Amazon and Google valuable insight into their users’ preferences and behaviours — data that can be monetized one way or another. Other companies have realized this, too.

Recurring revenue

U.S. manufacturer Vizio sells inexpensive televisions. How does it afford to do this? By sharing information about how people use their TVs — and what they watch — with other companies, essentially subsidizing the product’s cost.

“It’s not just about data collection,” said the company’s chief technology officer, Bill Baxter, in an interview with The Verge earlier this month. “It’s about post-purchase monetization of the TV.”

Most people don’t upgrade their TVs very often — Baxter said the average lifetime of a Vizio TV is 6.9 years — and Vizio only makes a slim margin on each sale. But those TVs keep getting new features and updates for free. So (opt-in) data collection is one way for Vizio to keep generating revenue in lieu of new sales.

“Margins are getting thinner and thinner, and they have been for a long time. And that’s applicable to, obviously, auto manufacturers, TV manufacturers, and everything in between,” said Wright.

“They don’t make a lot of money off the devices, so they rely on volume and other ways to make their money.”

U.S. TV maker Vizio sells inexpensive products. To make more money, it also collects and sells anonymized data on how people use their TVs and what they watch. Users have to opt-in first, however. (Rich Pedroncelli/Associated Press)

Already, car companies are collecting data on people’s driving behaviour and location in order to send them special offers and discounts — a market worth up to $750 billion US by 2030, according to a recent Wall Street Journal article citing McKinsey & Co. data.

Similarly, appliance maker Whirlpool said in its privacy policy that the company “may send you a notification when your Smart Appliance needs to be replenished with a refill or replacement item and offer to direct you to a third-party business partner from which you can purchase that item.”

Subscriptions are another way companies continue to profit from sales of smart technologies. Wright points to camera companies that now make money selling photo storage in the cloud, and wireless router companies that sell protection against threats like malware — both subscription based, of course.

Increasingly, buying a product seems to come with an ongoing relationship with that product’s manufacturer  — one that sometimes turns our data exhaust into a product of its own — but none of this seems to have fazed consumers much, according to Wright.

“Consumers are sort of like frogs in the boiling pot, right?” said Wright. “It’s amazing what we increasingly find comfortable when the initial shock has worn off.”

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Top 5 Analytics Trends That Are Shaping The Future

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Digital transformation is increasingly becoming the focus for many CIOs around the world today—with analytics playing a fundamental role in driving the future of the digital economy.

While data is important to every business, it is necessary for businesses to have a firm grip on data analytics to allow them transform raw pieces of data into important insights. However, unlike the current trends in business intelligence—which is centred around data visualization—the future of data analytics would encompass a more contextual experience.

“The known data analytics development cycle is described in stages: from descriptive (what happened) to diagnostic (why did it happen), to discovery (what can we learn from it), to predictive (what is likely to happen), and, finally, to prescriptive analytics (what action is the best to take),” said Maurice op het Veld is a partner at KPMG Advisory in a report.

“Another way of looking at this is that data analytics initially “supported” the decision-making process but is now enabling “better” decisions than we can make on our own.”

Here are some of the current trends that arealready shaping the future of data analytics in individuals and businesses.

  1. Growth in mobile devices

With the number of mobile devices expanding to include watches, digital personal assistants, smartphones, smart glasses, in-car displays, to even video gaming systems, the final consumption plays a key role on the level of impact analytics can deliver.

Previously, most information consumers accessed were on a computer with sufficient room to view tables, charts and graphs filled with data, now, most consumers require information delivered in a format well optimized for whatever device they are currently viewing it on.

Therefore, the content must be personalized to fit the features of the user’s device and not just the user alone.

  1. Continuous Analytics

More and more businesses are relying on the Internet of Things (IoT) and their respective streaming data—which in turn shortens the time it takes to capture, analyze and react to the information gathered. Therefore, while analytics programspreviously were termed successful when results were delivered within days or weeks of processing, the future of analytics is bound to drastically reduce this benchmark to hours, minutes, seconds—and even milliseconds.

“All devices will be connected and exchange data within the “Internet of Things” and deliver enormous sets of data. Sensor data like location, weather, health, error messages, machine data, etc. will enable diagnostic and predictive analytics capabilities,” noted Maurice.

“We will be able to predict when machines will break down and plan maintenance repairs before it happens. Not only will this be cheaper, as you do not have to exchange supplies when it is not yet needed, but you can also increase uptime.”

  1. Augmented Data Preparation

During the process of data preparation, machine learning automation will begin to augment data profiling and data quality, enrichment, modelling, cataloguing and metadata development.

Newer techniques would include supervised, unsupervised and reinforcement learning which is bound to enhance the entire data preparation process. In contrast to previous processes—which depended on rule-based approach to data transformation—this current trend would involve advanced machine learning processes that would evolve based on recent data to become more precise at responding to changes in data.

  1. Augmented Data Discovery

Combined with the advancement in data preparation, a lot of these newer algorithms now allow information consumers to visualize and obtain relevant information within the data with more ease. Enhancements such as automatically revealing clusters, links, exceptions, correlation and predictions with pieces of data, eliminate the need for end users to build data models or write algorithms themselves.

This new form of augmented data discovery will lead to an increase in the number of citizen data scientist—which include information users who, with the aid of augmented assistance can now identify and respond to various patterns in data faster and a more distributed model.

  1. AugmentedData Science

It is important to note that the rise of citizen data scientist will not in any way eliminate the need for a data scientist who gathers and analyze data to discover profitable opportunities for the growth of a business. However, as these data scientists give room for citizen data scientists to perform the easier tasks, their overall analysis becomes more challenging and equally valuable to the business.

As time goes by, machine learning would be applied in other areas such as feature and model selection. This would free up some of the tasks performed by data scientist and allow them focus on the most important part of their job, which is to identify specific patterns in the data that can potentially transform business operations and ultimately increase revenue.

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Waterloo drone-maker Aeryon Labs bought by U.S. company for $265M

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Waterloo’s Aeryon Labs has been bought by Oregon-based FLIR Systems Inc. for $256 million, or $200 million US.

The acquisition was announced Monday. 

Dave Kroetsch, co-founder and chief technology officer of Aeryon Labs, says not much will change in the foreseeable future.

“The Waterloo operations of Aeryon Labs will actually continue as they did yesterday with manufacturing, engineering and all the functions staying intact in Waterloo and ultimately, we see growing,” he said.

“The business here is very valuable to FLIR and our ability to sell internationally is a key piece of keeping these components of the business here in Canada.”

Aeroyn Labs builds high-performance drones that are sold to a variety of customers including military, police services and commercial businesses. The drones can provide high-resolution images for surveillance and reconnaissance.

The drones already include cameras and thermal technology from FLIR. Jim Cannon, president and CEO of FLIR Systems, said acquiring Aeryon Labs is part of the company’s strategy to move beyond sensors “to the development of complete solutions that save lives and livelihoods.”

‘A piece of a bigger solution’

Kroetsch said this is a good way for the company to grow into something bigger.

“We see the business evolving in much the direction our business has been headed over the last couple of years. And that’s moving beyond the drone as a product in and of itself as a drone as a piece of a bigger solution,” he said.

For example, FLIR bought a drone company that builds smaller drones that look like little helicopters.

“We can imagine integrating those with our drones, perhaps having ours carry their drones and drop them off,” he said.

FLIR also does border security systems, which Kroetsch says could use the drones to allow border agents to look over a hill where there have been issues.

“We see the opportunity there as something that we never could have done on our own but being involved with and part of a larger company that’s already providing these solutions today gives us access not only to these great applications, but also to some fantastic technologies,” he said.

Aeryon Labs has done a lot of work during emergency disasters, including in Philippines after Typhoon Hagupit in 2014, Ecuador after an earthquake in 2016 and the Fort McMurray wildfire in 2016.

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Inuvik infrastructure may not be ready for climate change, says study

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The Arctic is expected to get warmer and wetter by the end of this century and new research says that could mean trouble for infrastructure in Inuvik.

The study from Global Water Futures looked at how climate change could impact Havipak Creek — which crosses the Dempster Highway in Inuvik, N.W.T. — and it predicts some major water changes.

“They were quite distressing,” John Pomeroy, director of Global Water Futures and the study’s lead author, said of the findings.

Researchers used a climate model and a hydrological model to predict future weather and climate patterns in the region. They also looked at data gathered from 1960 to the present. 

If greenhouse gas emissions continue at their current rate — which Pomeroy said they are on track to do — the study projects the region will be 6.1 C warmer by 2099 and precipitation, particularly rain, will increase by almost 40 per cent.

The study also found that the spring flood will be earlier and twice as large, and the permafrost will thaw an additional 25 centimetres. While the soil is expected to be wetter early in the summer, the study said it will be drier in late summer, meaning a higher risk of wildfires.

John Pomeroy is the director of Global Water Futures. (Erin Collins/CBC)

“The model’s painting kind of a different world than we’re living in right now for the Mackenzie Delta region,” Pomeroy said.

He noted these changes are not only expected for Havipak Creek, but also for “many, many creeks along the northern part of the Dempster [Highway].”

Pomeroy said the deeper permafrost thaw and a bigger spring flood could pose challenges for buildings, roads, culverts and crossings in the area that were designed with the 20th century climate in mind.

He said the projected growth of the snowpack and the spring flood are “of grave concern because that’s what washes out the Dempster [Highway] and damages infrastructure in the area.”

Culverts and bridges may have to be adjusted to allow room for greater stream flows, Pomeroy said. And building foundations that are dependent upon the ground staying frozen will have to be reinforced or redesigned.

Pomeroy said the ultimate solution is for humans to reduce greenhouse gas emissions.

“This study is the future we’re heading for, but it’s not the future we necessarily have if we can find a way to reduce those gases,” he said.  

“It’d be far smarter to get those emissions under control than to pay the terrible expenses for infrastructure and endangered safety of humans and destroyed ecosystems.”

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