Parenting in the age of AI (or, at least, ubiquitous technology)

IEEE put out some survey results on Thursday, in the form of this infographic, highlighting the way t
ARCHITECHT
Parenting in the age of AI (or, at least, ubiquitous technology)
By ARCHITECHT • Issue #105
IEEE put out some survey results on Thursday, in the form of this infographic, highlighting the way that Millennial parents of “Generation Alpha” kids think about artificial intelligence as it applies to parenting. (If you’d rather read the results in text, here’s the press release that spells them out.)
Taken for what they are—a handful of data points in a sea of data points about Millennials—the results are interesting to read. Here’s a sampling of the findings:
About two-thirds of Millennial parents (63 percent) would rather have AI help them live independently in their golden years, while just 37 percent prefer to rely on their own children, the study found.
Two in five Millennial parents of Generation Alpha kids (39 percent) have either complete or a great deal of trust in AI to help diagnose and treat their children if they become sick. Almost half (46 percent) have some trust.
According to the IEEE survey, a majority of Millennial parents (80 percent) say AI technology increases their expectations that their Generation Alpha babies will learn faster and more than they did, while for 20 percent, expectations are the same or less. In addition, three quarters (74 percent) of Millennial parents say they would consider an AI-powered tutor for their child. 
Nearly half (48 percent) of Millennial parents of Generation Alpha kids say they would be likely to get a robot pet instead of real pet if their child asked for one, according to the survey. In addition, fathers (55 percent) are more likely than mothers (42 percent) to get a pet robot for their kids.
Perhaps because I’m technically aged out of the Millennial demographic by a few months and spend a lot of time thinking about AI, I’m a little more pessimistic about the promise of AI in the short term (and definitely in the present) than many respondents appear to be. Technology—namely, mobile, cloud and Google—certainly have affected the way I parent compared with parents (and just the way we live, in general) but I honestly can’t think of how AI has materially affected my parenting or even my daughter’s life so far (save for getting used to speaking to Alexa). 
I can state with some certainty that some areas, like medical diagnosis, will be largely AI-driven in the decade to come. Some not-insignificant percentage of cars might be autonomous by the time by daughter gets her driver’s license, and I don’t suspect she’ll get a summer job in a factory. But other areas, including education (I would argue) and nannies (40 percent of Millennial parents say the are likely “to supplement or replace a human nanny with a stay-at-home robonanny), are much further off than that. (For a great reality check on household robots, listen to the ARCHITECHT AI & Robot Show interview with Melonee Wise of Fetch Robotics.)
I also would never buy a robot pet. There are some lessons in life that only a flesh-and-blood thing can teach.

Sponsor: Bonsai
Sponsor: Bonsai
Listen to the latest ARCHITECHT Show podcast
In this episode of the ARCHITECHT Show, co-hosts Barb Darrow and Derrick Harris speak with Cloud Foundry Foundation executive director Abby Kearns about running one of the biggest, and still growing, open source projects in the cloud world. Among other things, Kearns discusses Cloud Foundry’s history and evolution; where it fits into today’s world of containers and Kubernetes; how the foundation works with leading cloud providers; and how she’s been able to manage lots of large enterprise vendors without losing control of the project.
Sponsor: Linux Foundation
Sponsor: Linux Foundation
Artificial intelligence
What I really like about Ford’s approach to the future of transportation is that it encompasses much more than just smarter cars. Per TechCrunch, this new team will “help with work on drones, personal mobility platforms (last-mile, scooter-style transport), automation and ‘aerial robotics.’”
I actually do see a lot of potential use cases for APIs like this, but my podcast interview with Bradford Cross now has me questioning how the economics of these services will work out for users. Will the cost of value-added services eventually race to zero, as well?
Speaking of video and AI, this startup called TwentyBN is working to solve action-recognition in videos, and just released two rather large datasets to help others train their models.
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a16z’s Frank Chen says investors will come to expect startups are using AI, so it won’t be a novel part of pitches anymore. It happened with cloud and data recently, and will happen with AI, too.
From the a16z podcast, featuring Frank as well as authors Andrew McAfee and Erik Brynjolfsson, who wrote “Machine, Platform, Crowd.” There’s some good stuff in here about AI and data in today’s and tomorrow’s economies.
Nick Carr is one of my favorite writers/critics on automation and our current tech-centric culture. Here he is reviewing Garry Kasparov’s book on losing to Deep Blue and how that affected his outlook on computing.
A collection of videos from the O'Reilly conference happening in New York this week, just like the headline says. There are some good speakers here. Speaking of O'Reilly, you can also check out this podcast with Intel AI leader Naveen Rao.
This is a good argument for augmenting the millions of existing cars, or at least the ones that will still be produced for years to come. You have to crawl before you walk, and you have to automate some parts of driving before you automate the whole experience.
OK, on this, China does seem to be far out ahead of the United States. It addresses everything from talent acquisition to R&D to job losses.
This particular research is about finding better materials and designs for superconductive devices. The bigger picture is that we’re possibly within years of commercially viable quantum computers.
Facial recognition techniques are helping marine biologists keep track of fisheries by identifying certain species. Of course, image quality is a problem in the ocean.
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Here’s a detailed writeup on Baidu’s new deep learning hardware benchmarking tool, as well as some comments on which architectures appear best. Hint: they’re mostly GPU ones.
Sponsor: Cloudera
Sponsor: Cloudera
Cloud and infrastructure
An Israeli news site reported this months ago, but Microsoft confirmed it today. Cloudyn monitors users’ cloud consumption in an attempt to optimize spending. It will be interesting to see how it works with other cloud providers once this deal closes.
The new Power Bundle is quite beefy, including “four vCPUs, 16 GiB of memory, and 275 GB of storage.” I honestly don’t know if virtual desktops ever caught on at scale, but AWS makes a compelling case here for data analysis, especially with its other tools and so much data already stored in its cloud.
Even in the ivory towers of large web companies, sometimes the best tools just help with the simplest things. Iris and Oncall don’t remediate problems, but do help automate getting the right info to the right people.
The storage market is a mystery to me. Flash-storage vendor Tintri canceled its Thursday IPO at the last minute, and then reduced its asking price and number of shares it’s offering. Maybe investors weren’t impressed by shrinking gains and mounting losses.
If you still find yourself asking what Docker containers are and why they’re such a big goddamn deal, read this. It’s 101-level content from someone who knows her way around a distributed system.
This is an informative blog post by the team at Segment about how they use Kafka, RocksDB and other tools to ensure the don’t lose data, but also don’t deliver the same message more than once.
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This made me laugh: 
Q: We have a new application that would make sense for SRE to support. Do I just throw it over the wall and tell the SRE team “Here you are; you’re on call for this now, best of luck”?
That’s a great approach — if your goal is failure. 
But this also has really good advice about how the app team and SRE team should work together to get a service into the SRE’s hands. And check out this podcast interview with one of Google Cloud’s CRE (C is for customer) leaders.
Sponsor: DigitalOcean
Sponsor: DigitalOcean
All things data
Kinetica is not the only company in this space, and they’re all raising serious money because GPUs can process certain database operations much faster. What if databases, not machine learning, drive mass GPU adoption?
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This news comes out of legal testimony by a Palantir investor. Looking past the controversy over Palantir and its financials, this could be a decent fit for Oracle in terms of business model and database consumption.
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Executives in the mortgage industry argue that with more data, they can further automate the process and assess risk, then pass the savings onto consumers. In my experience, this is one industry where that might actually be true.
Sponsor: CircleCI
Sponsor: CircleCI
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