Latest Japan campaigns highlight outdoors, anime

Inbound Marketing, Digital Marketing
Image source: Travel Weekly

By Eric Moya | Travel Weekly

The Japan National Tourism Organization (JNTO) recently launched two campaigns that take vastly different approaches to target different audiences, yet have the same ultimate goal: to attract more visitors from the U.S. and other inbound markets.


The Containerization of Artificial Intelligence

Artificial Intelligence
Image source:
Hamid Karimi
Hamid Karimi
Commentary | Dark Reading


Artificial intelligence (AI) holds the promise of transforming both static and dynamic security measures to drastically reduce organizational risk exposure. Turning security policies into operational code is a daunting challenge facing agile DevOps today. In the face of constantly evolving attack tools, building a preventative defense requires a large set of contextual data such as historic actuals as well as predictive analytics and advanced modeling. Even if such feat is accomplished, SecOps still needs a reactive, near real-time response based on live threat intelligence to augment it.

While AI is more hype than reality today, machine intelligence — also referred to as predictive machine learning — driven by a meta-analysis of large data sets that uses correlations and statistics, provides practical measures to reduce the need for human interference in policy decision-making.

A typical by-product of such application is the creation of models of behavior that can be shared across policy stores for baselining or policy modifications. The impact goes beyond SecOps and can provide the impetus for integration within broader DevOps. Adoption of AI can be disruptive to organizational processes and must sometimes be weighed in the context of dismantling analytics and rule-based models.

The application of AI must be constructed on the principle of shared security responsibility; based on this model, both technologists and organizational leaders (CSOs, CTOs, CIOs) will accept joint responsibility for securing the data and corporate assets because security is no longer strictly the domain of specialists and affects both operational and business fundamentals. The specter of draconian regulatory compliance such as fines articulated by the EU’s General Data Protection Regulation provides an evocative forcing function.

Focus on Specifics
Instead of perceiving AI as a cure-all remedy, organizations should focus on specific areas where AI holds the promise of greater effectiveness. There are specific use cases that provide a more fertile ground for the deployment and evolution of AI: rapid expansion of cloud computing, microsegmentation, and containers offer good examples. Even in these categories, shared owners must balance the promises and perils of deploying AI by recognizing the complexity of technology while avoiding the cost of totally ignoring it.

East-west and north-south architecture of data flow has its perils as we witnessed in the recent near-meltdown of public cloud services. The historic emphasis on capacity and scaling has brought us to clever model of computing which involves many layers of abstraction. With abstraction, we have essentially removed the classic stack model and therefore adding security to it presents a serious challenge.

Furthermore, the focus away from the nuts and bolts of infrastructure to application development in isolation and insulation has given birth to the expectation that even geo-scale applications inside containers and Web-scale micro services can be independently secured while maintaining an automated and scalable middleware. Hyperscale computing, relying on millisecond availability in distributed zones, is more than an infrastructure play and increasingly relies on microsegmentation and container-based application services — a phenomenon whose long-term success depends on AI.

In the ’90s, VLANs were supposed to give us protective isolation and the ability to offer a productive computing space based on roles and responsibilities. That promise had fallen far short of expectations. Microsegmentation and containers are in a way a post-computing evolution of VLANs. They have brought other benefits such as reducing pressure on firewall rules; no longer there is a need to keep track of exponentially growing rules with little visibility in situations that lead to false positives and false negatives. Although the overall attack surface is reduced, and collateral damage is partially abated, the potential for more persistent breaches are not reduced. AI tools can zero in on a smaller subset of data and create better mapping without affecting the user productivity or undermining the overlay concept of segmented computing.

It is pretty much a one-two-three punch: the organization can look at all available metadata, feed that to the AI, and then take the output of AI to predictive analytics engines and create advanced modeling of potential attacks that are either in progress or will soon commence. We are still a few years away from the implementation of another potential step: machine-to-machine learning and security measures whereby machines can observe and absorb relevant data and modify their posture to protect themselves from predicted attacks.

AI can also provide substantial value in other emerging areas such as autonomous driving. Cars are increasingly resembling computing machines with direct cloud command and control. From offline modeling based on fuzzing to real-time analysis of sensor data, we may rely on AI to reduce risks and liabilities.

Artificial intelligence is not a panacea; however, it automates repetitive tasks and alleviates mundane functions that often haunt security decision makers. Like other innovations in security, it will go through its evolutionary cycle and eventually finds its rightful place. In the meantime, there is still no sure substitute for security best practices.

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Hamid Karimi has extensive knowledge about cybersecurity, and for the past 15 years his focus has been exclusively in the security space, covering diverse areas of cryptography, strong authentication, vulnerability management, and malware threats, as well as cloud and network … View Full Bio

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How Kate Spade is building an entertainment-driven content strategy

Kate Spade, Video, Social Media, Influencer
An image from Kate Spade’s ‘Make Yourself a Home’ YouTube series

By  |The Drum

About five years ago, Kate Spade found itself facing many of the same issues as other fashion brands. With glossy two-page magazine ads continuing to lose their luster, the handbag maker was struggling to shed its more traditional, print-oriented ways and create a digital strategy that worked.

Speaking at SXSW, Kate Spade’s chief marketing officer Mary Beech explained that at the time, the brand was employing a hollow one-size-fits-all approach to social by posting the same content on each platform. Additionally, the company was struggling to glean any real insights from the data it had on hand.

“We created content for all of the various mediums in which we were on, but we created one piece of content and just pushed it across all the mediums, not taking into any account what was specific about those distribution techniques,” said Beech. “We had lots of data, but we didn’t have insights, and so we weren’t using those insights to leverage them against the content we created and deployed.”

Fast forward to 2018, and the brand – which was acquired by Coach last year for $2.4bn – is doing things a bit differently. Through creating content that’s both platform-specific and entertainment-driven, the New York-based company has managed to create a digital strategy that it says is helping it connect and engage with fans.

Finding a story to tell

Getting into a “video-first” mindset is something that Kristen Naiman, senior vice president of brand creative at Kate Spade’s in-house agency, wanted to prioritize when she joined the company four years ago. At the time, Naiman said her team was “very stuck in thinking about the photograph” as the main form of communication.

To move away from that, her team began looking at what sorts of shows and series were popular to see if the brand could take any cues from the entertainment world.

“A lot of what was happening out there that felt really exciting was this renaissance of serialized narrative storytelling content,” she said, pointing to shows like HBO’s High Maintenance and the rising popularly of Netflix. It was around that same time that female comedians like Lena Dunham and Amy Schumer were beginning to see their careers skyrocket, something she said the brand also took note of since she believed they were helping to usher in a new era of comedy.

“We thought both of those things were amazing and really interesting,” said Naiman.

Those two insights led to the birth of Kate Spade’s #MissAdventure, a short-form YouTube show starring actress and singer Anna Kendrick that kicked off in 2014. In the series, Kendrick plays a slightly ditzy, quirky woman who spends her days exploring New York.

“Our principles were twofold: we were going to make something that behaved in a way that was digital-first, and we were going to make something that while it was meant to be a piece of marketing to a certain degree, was interesting first,” said Naiman.

Kate Spade’s products were tied into the series via a concept Naiman calls “product as character,” which essentially involves making a product an integral part of the story rather than something a character is simply wearing or using.

For instance, in an episode of #MissAdventure called ‘The Waiting Game,’ Kendrick realizes she’s lost her apartment keys once she arrives at her doorstep. To get in, she decides to create a makeshift rope using the Kate Spade clothes and shoes she’s just bought so she can climb in via the fire escape.

Naiman said making the brand’s products a “distinct element” in the stories it tells helps the brand become part of the narrative, a strategy she believes is more effective than simply sticking a logo at the end of a video.

“We are a materialist culture. We all live with a lot of stuff in our lives, and those elements in our lives are part of our story,” she said.

Choosing a platform

While some brands strive to be early adopters and try out every new platform, Kate Spade has taken a more cautious approach to social.

Krista Neuhaus, Kate Spade’s senior director of digital brand marketing, said the brand was on every single social channel when she joined a few years back. Upon joining, she made it her job to figure out not only which channels the brand should be on and which ones it shouldn’t, but also how it should approach each individual platform…Read more 

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Tech’s sexist algorithms and how to fix them

Technology, Artificial Intelligence
Image credit: © Getty Images

By  | Financial Times

Are whisks innately womanly? Do grills have girlish associations? A study has revealed how an artificial intelligence (AI) algorithm learnt to associate women with pictures of the kitchen, based on a set of photos where the people in the kitchen were more likely to be women. As it reviewed more than 100,000 labeled images from around the internet, its biased association became stronger than that shown by the data set — amplifying rather than simply replicating bias.

The work by the University of Virginia was one of several studies showing that machine-learning systems can easily pick up biases if their design and data sets are not carefully considered.

Another study by researchers from Boston University and Microsoft using Google News data created an algorithm that carried through biases to label women as homemakers and men as software developers. Other experiments have examined the bias of translation software, which always describes doctors as men.

Given that algorithms are rapidly becoming responsible for more decisions about our lives, deployed by banks, healthcare companies and governments, built-in gender bias is a concern. The AI industry, however, employs an even lower proportion of women than the rest of the tech sector, and there are concerns that there are not enough female voices influencing machine learning.

Sara Wachter-Boettcher is the author of Technically Wrong, about how a white male technology industry has created products that neglect the needs of women and people of colour. She believes the focus on increasing diversity in technology should not just be for tech employees but for users, too.

“I think we don’t often talk about how it is bad for the technology itself, we talk about how it is bad for women’s careers,” Ms. Wachter-Boettcher says. “Does it matter that the things that are profoundly changing and shaping our society are only being created by a small sliver of people with a small sliver of experiences?”

Technologists specialising in AI need to look very carefully at where their data sets come from and what biases exist, she argues. They should also examine failure rates — sometimes AI practitioners will be pleased with a low failure rate, but this is not good enough if it consistently fails the same group of people, Ms Wachter-Boettcher says.

“What is particularly dangerous is that we are moving all of this responsibility to a system and then just trusting the system will be unbiased,” she says, adding that it could be even “more dangerous” because it is hard to know why a machine has made a decision, and because it can get more and more biased over time.

Tess Posner is executive director of AI4ALL, a non-profit that aims to get more women and under-represented minorities interested in careers in AI. The organisation, started last year, runs summer camps for school students to learn more about AI at US universities.

Last summer’s students are teaching what they learnt to others, spreading the word about how to influence AI. One high-school student who had been through the summer programme won best paper at a conference on neural information-processing systems, where all of the other entrants were adults.

“One of the things that is most effective at engaging girls and under-represented populations is how this… Read more of article

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The 10 I’s of Innovation

Ideas, Innovation, Inspiration

When you are inspired, an idea can promote imagination, with resources that provide information to identify factors for inventing and inviting creative minds to the table to integrate their insights for implementing innovation.

There is not one single ingredient that brings innovation to fruition, but all of the components that formulate innovation should not be underestimated or devalued.

Celebrating Women Around the World

International Women's Day, Celebrating Women, Pre

Today is International Women’s Day. As we press for progress on leveling the playing field in the workforce, politics, athletics, art, literature, academia, mathematics, science, technology, agriculture, innovation and entertainment just to name a few, we celebrate the important contributions women around the world make to benefit their family, their community, and the general public. These contributions are not restricted by race, socioeconomic status, religious standing or IQ.

Once we realize that we occupy one world, made up of an amazing tapestry of talent, humanity, and cultures then we will understand the scope of contributions made to the success, sustainability, and progress of our lives. Don’t underestimate the power within based on its exterior package.

A woman who walks in purpose doesn’t have to chase people or opportunities. Her light causes people and opportunities to pursue her. -Unknown

#PressForProgress as we celebrate International Women’s Day during National Women’s History Month!

Is She a Superhero for Artificial Intelligence?

Artificial Intelligence, Terah Lyons, Technology
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By  | OZY

When Terah Lyons arrives at the Flywheel Coffee Roasters in San Francisco’s Haight-Ashbury, she is greeted so enthusiastically that she laughs with surprise. But this can’t have been the first such welcome. Even if you don’t know who she is, the ease and poise with which she walks and the warmth of her smile make it hard not to be struck by her presence. And as if on cue, from the speaker overhead comes Alicia Keys’ hit song “You Don’t Know My Name.”

In October 2017, Lyons was appointed founding executive director of the Partnership on Artificial Intelligence, a nonprofit started by the world’s leading AI companies with the goal of ensuring AI is applied in ways that benefit people and society. The partners are among the largest companies shaping society today: Apple, Amazon, DeepMind, Google, Facebook, Microsoft and IBM. Its board of directors, with whom Lyons works closely, reads like a who’s who of AI pioneers: Tom Gruber (co-inventor of Siri), Eric Horvitz (director of Microsoft Research), Yann LeCun (director of AI research at Facebook), Greg Corrado (co-founder of Google Brain) and Mustafa Suleyman (co-founder of DeepMind and founding co-chair of the Partnership on AI). But it’s not solely a group of tech titans — board members also include representatives of universities, foundations and even the American Civil Liberties Union.



What was it that helped Lyons win such an important job? The fact that she chooses to “live her values in practice,” says Suleyman. That’s what most impressed him when he met her during the interview process. “She’s got phenomenal energy, good technical understanding, good instincts and she’s massively driven,” he says. “She could do anything. She could work anywhere. She could run any organization.”

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