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Tag Archives: than

Researchers claim that AI-translated text is less ‘lexically’ rich than human translations

February 3, 2021   Big Data
 Researchers claim that AI translated text is less ‘lexically’ rich than human translations

Human interpreters make choices unique to them, consciously or unconsciously, when translating one language into another. They might explicate, normalize, or condense and summarize, creating fingerprints known informally as “translationese.” In machine learning, generating accurate translations has been the main objective thus far. But this might be coming at the expense of translation richness and diversity.

In a new study, researchers at Tilburg University and the University of Maryland attempt to quantify the lexical and grammatical diversity of “machine translationese” — i.e., the fingerprints made by AI translation algorithms. They claim to have found a “quantitatively measurable” difference between the linguistic richness of machine translation systems’ training data and their translations, which could be a product of statistical bias.

The researchers looked a range of different machine learning model architectures including Transformer, neural machine translation, long short-term memory networks, and phrase-based statistical machine translation. In experiments, they tasked each with translating between English, French, and Spanish and compared the original text with the translations using 9 different metrics.

The researchers report that in experiments, the original training data — a collection of reference translations — always had a higher lexical diversity than the machine translations regardless of the type of model used. In other words, the reference translations were consistently more diverse in terms of vocabulary and synonym usage than the translations from the models.

The coauthors point out that while the loss of lexical diversity could be a desirable side effect of machine translation systems (in terms of simplification or consistency), the loss of morphological richness is problematic as it can prevent systems from making grammatically correct choices. Bias can emerge, too, with machine translation systems having a stronger negative impact in terms of diversity and richness on morphologically richer languages like Spanish and French.

“As [machine translation] systems have reached a quality that is (arguably) close to that of human translations and as such are being used widely on a daily basis, we believe it is time to look into the potential effects of [machine translation] algorithms on language itself,” the researchers wrote in a paper describing their work. “All [of our] metrics indicate that the original training data has more lexical and morphological diversity compared to translations produced by the [machine translation] systems … If machine translationese (and other types of ‘NLPese’) is a simplified version of the training data, what does that imply from a sociolinguistic perspective and how could this affect language on a longer term?”

The coauthors propose no solutions to the machine translation problems they claim to have uncovered. However, they believe their metrics could drive future research on the subject.

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like conservative humor, is there conservative theory other than the usual fascism

January 7, 2021   Humor
 like conservative humor, is there conservative theory other than the usual fascism


There’s an article that tries to identify contemporary conservative thoughtthat isn’t the usual amalgam of artistic or literary formalism, Whig history, neoclassical economics, scientism, or logical positivism. It doesn’t succeed, but it remains an interesting project to find something that could rationalize Trumpism. You may find it interesting if only to have something to talk about when convincing Trumpists with college degrees why they shouldn’t support Josh Hawley.

It may be that there is no such thing as a conservative humor other than those which are sexist, misogynist, homophobic, transphobic, lookist, ableist, and racist. This would leave us with observational, self-deprecating, ironic humor of an infantile sort. Think Dennis Miller without the intellectual references ceteris paribus. Or maybe Bill Cosby without the crimes.

That’s clearly not what would define as humor of a liberal sort, but it is similar to the relatively circular and often disinformational logic of what might be conservative theory. Such a theory would have some strange idealist libertarianism constructed on racial privilege that scapegoats some classic liberalism with what seems a self-centered, reactionary thought and behavior in a world without imperialism and colonialism, and capitalism is ubiquitous and canonical. Think William F. Buckley’s National Review without the closeted gayness.

This article by Geoff Shullenberger tries to deconstruct whatever conservative theory might be shared by Trumpists who graduated from college and have some position in its political structure. YMMV. It even soft-pedals Heidegger’s Nazism, because math. This is like Trump’s speech to his special, “very fine people” yesterday, except with smaller words.

The career of our next subject points to a similar conclusion. Just prior to becoming a Trump speechwriter and policy adviser, Darrien J. Beattie completed a Ph.D. in Political Theory at Duke, with a dissertation on “Martin Heidegger’s Mathematical Dialectic.” Beattie’s dissertation, the abstract tells us, “attempts to elucidate Martin Heidegger’s diagnosis of modernity, and, by extension, his thought as a whole, from the neglected standpoint of his understanding of mathematics, which he explicitly identifies as the essence of modernity.” Heidegger was not a postmodernist or a critical theorist, but he was a key influence on French post-structuralists like Foucault and Derrida, and on the Frankfurt School, especially Marcuse.

Beattie’s dissertation overlaps thematically with the bodies of theory brought up in relation to Breitbart and Hahn. The theorists discussed by both of them, as we have seen, shared a preoccupation with the way that power is exercised in the modern era by means ostensibly neutral institutions and ostensibly objective scientific techniques. Heidegger’s famous account of technology as an intrinsically violent “enframing” of nature influenced the way thinkers like Marcuse and Foucault challenged the nominal objectivity and neutrality of scientific expertise and technological control. Beattie’s investigation of Heidegger’s account of mathematics – broadly seen as the epistemological basis of this objectivity and neutrality – as the “essence of modernity” fits in well with this set of concerns.

Beattie’s trajectory has certain parallels with Hahn’s. After a successful career as a student of theory at an elite institution, he went on to become part of the Trump White House communications team. Whereas Hahn preceded this with her stint at Breitbart, Beattie is now involved in revolver.news, a pro-Trump news aggregation site. He is also currently writing a book “in defense of Trumpist nationalism.”

Along with Hahn, Beattie has been heavily criticized by organizations like the SPLC for his associations with extreme anti-immigration groups. An exposé of his participation in a 2016 gathering that also included white nationalists let to his firing from the White House. Recently, he again attracted additional criticism when Trump appointed him to a commission that “helps preserve sites related to the Holocaust.” Beattie, like Hahn and Breitbart, is Jewish, but all have been faulted for excessive proximity to white nationalism.

In Beattie’s case, these controversies are something of an echo of the one that once surrounded his dissertation subject, Heidegger, who notoriously became a member of the Nazi Party in the early 1930s. Beattie addresses this fact in a prefatory remark to his dissertation, in which he states that there are “important cautionary lessons to be learned from a careful study of Heidegger’s monumental political blunder,” but also explains that he will not be addressing these lessons at length in his own work. He writes that “out of respect for the magnitude of scholarly literature devoted to this question . . . one must conclude that sheer limitations of space and scope simply prohibit an adequate treatment of Heidegger’s political involvement with National Socialism within the context of a study that intends to explore seriously and comprehensively any separate feature of Heidegger’s thought.” However, he also states the following:

“[T}o study Heidegger’s disastrous political involvement to the exclusion of other aspects of his thought would not only be damaging philosophically, such a stance would also run the risk of unwittingly inviting the repetition of new political misjudgments in the future. To put the matter in more general yet more concrete terms, just as it is important to understand the extent and nature of the philosophical errors behind the 20th century’s most brutal and illiberal totalitarian regimes, it is equally important—indeed, perhaps more so—not to allow an exclusive or inordinate attention to such blunders detract from a deep and critical attention to the dangers that might be lurking within the seemingly more benign political expressions of modernity that have survived the downfall of fascism and communism.”

In other words, Beattie seems to say, an emphasis on Heidegger’s complicity with Nazism risks sidelining the insights his work offers into the “seemingly more benign political expressions of modernity” that shape our reality. It seems safe to infer that Beattie is referring here to the technocratic liberal consensus ascendant today.

In a more overtly polemical piece of writing, in which he attacks neoconservative interventionism and defends an “America First” foreign policy, Beattie states that “the chief threat to America, and indeed the West, is not an overseas regime like the Soviet Union or a foreign-born movement like radical Islam. To the contrary, it is a home-grown threat: the corruption and de-legitimization of our domestic institutions and the elite entrusted with the custody of the American way of life.” Again, these institutions, as has been evident during the pandemic, rest their assertions of authority on assertions of their own expertise, objectivity, and neutrality – claims that are increasingly in disrepute. Heidegger, as well as a number of the later theorists he influenced, have provided their followers with the means to critique of this form of power. It should be no surprise that such an approach is of interest to some adherents of a political movement that aims to exploit and accelerate the crisis of these institutions.

outsidertheory.com/…

x

Almost exactly four years ago, 217 people were arrested and prosecuted for protesting when Trump was inaugurated. They faced 60-year prison terms.

Today, after a mob seized the Capitol building for hours in an insurrection that killed someone, the DC Police have made 13 arrests. https://t.co/7CMpIK1hzH

— Andrew Crespo (@AndrewMCrespo) January 7, 2021

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Accessing Kafka’s Real-Time Analytics Is Easier Than Ever

December 28, 2020   TIBCO Spotfire
TIBCO Kafka RealTimeAnalytics 696x497 Accessing Kafka’s Real Time Analytics Is Easier Than Ever

Reading Time: 2 minutes

More and more major companies are realizing the full value of having real-time data-driven analytics at their fingertips. Everything from temperature sensor tracking and machinery wear-and-tear to social media metrics and targeted online searches to fraud and forecast trends can be critical information to a successful modern business.  

In light of this, organizations have been turning en masse to Apache Kafka, and with good reason, as it’s just about the perfect tool for integrating these wildly diverse streams of real-time data across multiple, connected applications to improve decision-making.

However, many businesses still have not been able to take advantage of the benefits of the “real-time” aspect of these analytics.  

The Problem with Kafka: Accessing Real-Time Information

Whether it’s an analyst doing reports or a data scientist applying machine learning methods to the data, they’re usually viewing it in aggregate from a traditional database, and typically don’t get to interact with it in its natural and most useful form—real-time.

The issue behind accessing real-time data is that most business intelligence, data science, and data management tools do not natively connect to Kafka. This means that getting useful analytical insights from Kafka usually requires custom coding as well as several complex components that are expensive, difficult, and time-consuming to implement. 

Introducing TIBCO Cloud Data Streams for Kafka

But now, with TIBCO Cloud™ Data Streams, we’ve taken the expensive, custom-coding headache out of making that Kafka connection. Business users can just connect TIBCO Spotfire® software to Kafka messages and go. 

With a native low-code, or, in most cases, no-code Kafka connection from TIBCO, analytics agility can be achieved in just minutes. Now, there’s nothing to stop you from taking advantage of what Kafka’s real-time analytics has to offer.

When TIBCO and Kafka Work Together, Businesses Win

As Kafka adoption becomes more widespread, the massive advantage in the practical application of real-time analytics continues to grow increasingly evident. Some recent use cases include:

  • Real-time Monitoring of Sporting Events: TXODDS, a real-time aggregator and distributor of sports betting information, absorbs data from systems monitoring thousands of live sporting events in real-time, using a network of Kafka messages. The messages carry real-time inputs, such as which players are on the field, the score, and even the weather. These messages are fed to the TIBCO-powered TXODDS “brain,” which can compare current game conditions to history, execute sophisticated artificial intelligence (AI) learning models to predict which way the game is likely to go based on in-game data, and transmit a stream of data and predictions to their subscribers.
  • Predictive Global Bank Operations: A top-tier financial institution uses TIBCO to monitor global trading activity and get a real-time view of the impact of client orders, trading activity, and IT infrastructure all at once. Based on Kafka messages, the bank has predictive operations that can spot and stop problems before they happen, increasing agility and requiring fewer resources for citizen developers.
  • Near-Instant Fraud Detection: Another well-known bank is using Kafka and TIBCO to detect credit risk in real-time without any human intervention. Credit card scans are captured as real-time triggered events that stream through Kafka. The system learns what a fraud-like transaction looks like and makes an autonomous decision based on its learnings. 

With a native low-code, or, in most cases, no-code Kafka connection from TIBCO, analytics agility can be achieved in just minutes. Now, there’s nothing to stop you from taking advantage of what Kafka’s real-time analytics has to offer. Click To Tweet

By building a bridge between open-source developers and business users, TIBCO helps you come together as a team to manage Kafka-powered business systems.

To learn how to analyze Kafka data in minutes, download this ebook “How to Easily Get Real-time Analytics from Kafka.”

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New framework can train a robotic arm on 6 grasping tasks in less than an hour

December 17, 2020   Big Data

Advances in machine learning have given rise to a range of robotics capabilities including grasping, pushing, pulling, and other object manipulation skills. However, general-purpose algorithms to date have been extremely sample-inefficient, limiting their applicability to the real world. Spurred on by this, researchers at the University of California, Berkely developed a framework — Framework for Efficient Robotic Manipulation (FERM) — that leverages cutting-edge techniques to achieve what they claim is “extremely” sample-efficient robotic manipulation algorithm training. The coauthors say that, given only 10 demonstration amounting to 15 to 50 minutes of real-world training time, a single robotic arm can learn to reach, pick, move, and pull large objects or flip a switch and open a drawer using FERM.

McKinsey pegs the robotics automation potential for production occupations at around 80%, and the pandemic is likely to accelerate this shift. A report by the Manufacturing Institute and Deloitte found that 4.6 million manufacturing jobs will need to be filled over the next decade, and challenges brought on by physical distancing measures and a sustained uptick in ecommerce activity have stretched some logistics operations to the limit. The National Association of Manufacturers says 53.1% of manufacturers anticipate a change in operations due to the health crisis, with 35.5% saying they’re already facing supply chain disruptions.

FERM could help accelerate the shift toward automation by making “pixel-based” reinforcement learning — a type of machine learning in which algorithms learn to complete tasks from recorded demonstrations — more data-efficient. As the researchers explain in a paper, FERM first collects a small number of demonstrations and stores them in a “replay buffer.” An encoder machine learning algorithm pretrains on the demonstration data contained within the replay buffer. Then, a reinforcement learning algorithm in FERM trains on images “augmented” with data generated both by the encoder and the initial demonstrations.

According to the researchers, FERM is easy to assemble in that it only requires a robot, a graphics card, two cameras, a handful of demonstrations, and a reward function that guides the reinforcement learning algorithm toward a goal. In experiments, they say that FERM enabled an xArm to learn six tasks within 25 minutes of training time (corresponding to 20 to 80 episodes of training) with an average success rate of 96.7%. The arm could even generalize to objects not seen during training or demonstrations and deal with obstacles blocking its way to goal positions.

 New framework can train a robotic arm on 6 grasping tasks in less than an hour

“To the best of our knowledge, FERM is the first method to solve a diverse set of sparse-reward robotic manipulation tasks directly from pixels in less than one hour,” the researchers wrote. “Due to the limited amount of supervision required, our work presents exciting avenues for applying reinforcement learning to real robots in a quick and efficient manner.”

Open source frameworks like FERM promise to advance the state of the art in robotic manipulation, but there remain questions about how to measure progress. As my colleague Khari Johnson writes, metrics used to measure progress in robotic grasping can vary based on the task. For example, for robots operating in a mission-critical environment like space, accuracy matters above all.

“Under certain circumstances, if we have nice objects and you have a very fast robot, you can get there [human picking rates],” roboticist Ken Goldberg told VentureBeat in a previous interview. “But they say humans are like 650 per hour; that’s an amazing level. It’s very hard to beat humans. We’re very good. We’ve evolved over millions of years.”

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How would we extract elements of a list greater than a certain value?

November 6, 2020   BI News and Info

 How would we extract elements of a list greater than a certain value?

1 Answer

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Part::partd Part specification is longer than depth of object

October 19, 2020   BI News and Info

 Part::partd Part specification is longer than depth of object

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AI analysis finds that in-app ad issues are fixed faster on Android than iOS

August 28, 2020   Big Data
 AI analysis finds that in app ad issues are fixed faster on Android than iOS

Automation and Jobs

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A new study finds evidence that in-app ad issues with popular Android apps on Google Play are addressed more quickly than their iOS counterparts on the App Store. In what the authors claim is a first-of-its-kind survey, a team investigated the ads in 32 cross-platform apps that rank in the App Store’s and Google Play’s respective top 100 lists. They say the results imply developers should pay attention to platform differences during ad design and consider ways to automatically customize and test apps to improve ad experiences.

The study is noteworthy for its use of supervised multi-label classification, an AI technique that predicts the labels of unseen instances (in this case ads) by analyzing labeled training data. The researchers say it enabled them to canvass and categorize far more information than in previous studies, laying the groundwork for automated analysis tools. Large-scale perceptual studies on mobile ads could help developers prioritize their work, for example by choosing to spend more time fixing problems on iOS than Android.

In-app ads are massive revenue drivers on mobile. For instance, in 2016, mobile ad revenue accounted for 76% of Facebook’s total sales in the first quarter. Many free apps, which make up more than 68% of the over two million apps in Google Play, leverage some form of in-app advertising for monetization. But previous research suggests that users find these ads intrusive. Growth Tower reports that almost 50% of users said they’d uninstall apps just because of mobile ads.

In selecting which apps to analyze, the researchers, who hail from the Harbin Institute of Technology (Shenzhen, China), The Chinese University of Hong Kong, Singapore Management University, and Melbourne’s Monash University, looked at apps across 15 categories with over 100,000 reviews on both app stores. They built a simple web crawler to automatically scrape user reviews, downloading 1,840,349 reviews from the App Store and 3,243,450 from Google Play published between September 2014 and March 2019. Using a filter and several post-processing steps, they isolated reviews containing keywords related to ads (e.g., “ad,” “ads,” “advert”), extracting 18,302 ad-related reviews in total.

To determine how quickly (or slowly) developers addressed in-app ad complaints, the researchers recorded the number of versions of apps released between the time issues were reported and the time they were fixed. The coauthors report it took an average of 1.23 updates per app before problems were addressed on Google Play, while it took nearly two updates (1.78) per app on the App Store. But certain issues were fixed faster on iOS compared with Android. For instance, iOS developers were quick to address orientation, auto-play, and notification complaints. Android developers responded more quickly to orientation, volume, and non-skippable ad issues.

The researchers categorized each review into one or more ad issue type, using a combination of keyword matching and AI classifier models. They found that:

  • 8.81% (1,613) of the reviews mentioned ad content as an issue.
  • 25.02% (4,580) of the reviews mentioned ad frequency, or how often the ads appeared, as an issue.
  • 13.52% (2,475) of the reviews took issue with the way the ads suddenly “popped up.”
  • 45.51% (8,329) of the reviews mentioned there were too many ads.
  • 3.84% (703) of the reviews complained about non-skippable ads.
  • 12.11% (2,216) of the reviews said ads were too lengthy.
  • 2.10% (385) of the reviews said the ads were too large.
  • 6.47% (1,233) of the reviews complained about ad placement and position.
  • 1.96% (359) of the reviews complained about auto-playing ads.
  • 0.87% (159) of the reviews were frustrated about ad volume.

Interestingly, complaints weren’t the same across Google Play and the App Store. Security (i.e., unauthorized data collection or permission usage), orientation (the orientation of app screens impacted by ads), timing, and auto-play complaints were more common among iOS users, while Android users reported obtrusive notifications in the status bar, volume, and app slowdowns as top sources of consternation.

The study coauthors propose developers prioritize ad issues on platforms differently and optimize ad display settings like the number of ads, display frequency, and display style. They also suggest designing strategies to manage ads with long display period. “Inappropriate ad design could adversely impact app reliability and ad revenue,” the coauthors wrote. “Understanding common in-app advertising issues can provide developers practical guidance on ad incorporation.”

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Innovation: It’s More Than Just A Nice-To-Have

June 7, 2020   SAP
 Innovation: It’s More Than Just A Nice To Have

Our day-to-day lifestyle has significantly changed in this new reality created by the COVID-19 pandemic. Regardless of how tech-savvy you were before, you – like everyone else – now depend on digital tools to manage both your personal and professional life.

A lot of these products, services, and platforms did not exist or were only available to a select audience before the pandemic. Many were considered too innovative or “nice to have” but not necessary. But think about all of the elderly people staying connected to their loved ones through video platforms, the average families using delivery apps for groceries, or the companies hosting large conferences in virtual setups – the list goes on and on. In most cases, there was no (or little) need for those tools before, so they were scarcely used. And yet organizations still invested in and brought them to market. Looking at the demand now, we can see some organizations were a step ahead of the others. What’s their secret to knowing what will be needed in the future? The answer: their drive for innovation.

Innovation: what does it mean?

How many times have you heard or seen the word “innovation” just today? Well, at least four times in this article so far. And beyond? Yes, it’s everywhere, but it is still an abstract idea for many people – just a buzzword. Let’s dig deeper into what innovation is. Here is how several online sources (linked in the References below) define it:

  • Innovation is the process of doing things differently and discovering new ways of doing things.
  • Innovation is adapting to change to better meet demands of products or services.
  • Innovation is improving business processes and models, developing new products or services, adding value to existing products, services, or markets.
  • Innovation’s aim is to provide something original or unique that can have an impact on society.

Understanding and living innovation, especially in times of change

One point that is missing from this list: Innovation spares no one. It is essential for individuals and organizations, for the CEO of a company just as much as the entrepreneur who is just getting started. That said, you do not need to aim be the next Amazon or Airbnb. Small changes can help you foster an innovation mindset to proactively respond to potential disruptions.

Imagine the current pandemic a decade ago: no virtual office meetings, no video calls with family and friends, no 24/7 food delivery to your doorstep. Think about the economic and emotional impact it would have had. By all means, the economic impact today is enormous, but imagine how much worse it could have been in the past. Companies would have stopped operating with no alternatives; there would no e-commerce, no IT infrastructure, and no availability. If there wasn’t an innovative mindset and driven teams that created these products, services, and platforms, we would be in an even less fortunate scenario now.

Write (innovation) history!

“It is only the farmer who faithfully plants seeds in the Spring, who reaps a harvest in the Autumn.”
— B.C. Forbes

At this moment, we are writing history. We are living through the most disruptive period we have ever seen, a time when innovations are needed more than ever. We need to think one step ahead and take this opportunity to reinvent ourselves. We also need to make this an ongoing practice – all of us, from small and midsize businesses to big corporations. Whether you are producing something like face masks and need to rethink your supply chain management due to high demand, or you’re an events company that needs to go fully virtual in a single day, this applies to you.

I strongly believe that we will rise from this crisis with a new appreciation for innovation and change. Innovation should be a mandatory component of your daily experience and strategy instead of being regarded as a luxury – especially now.

References

For more on thriving through today’s disruption and certainty, see the “Navigating Disruption Today, Planning for Tomorrow” series.

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Digitalist Magazine

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Innovation: It’s More Than Just A Nice-To-Have

May 31, 2020   SAP
 Innovation: It’s More Than Just A Nice To Have

Our day-to-day lifestyle has significantly changed in this new reality created by the COVID-19 pandemic. Regardless of how tech-savvy you were before, you – like everyone else – now depend on digital tools to manage both your personal and professional life.

A lot of these products, services, and platforms did not exist or were only available to a select audience before the pandemic. Many were considered too innovative or “nice to have” but not necessary. But think about all of the elderly people staying connected to their loved ones through video platforms, the average families using delivery apps for groceries, or the companies hosting large conferences in virtual setups – the list goes on and on. In most cases, there was no (or little) need for those tools before, so they were scarcely used. And yet organizations still invested in and brought them to market. Looking at the demand now, we can see some organizations were a step ahead of the others. What’s their secret to knowing what will be needed in the future? The answer: their drive for innovation.

Innovation: what does it mean?

How many times have you heard or seen the word “innovation” just today? Well, at least four times in this article so far. And beyond? Yes, it’s everywhere, but it is still an abstract idea for many people – just a buzzword. Let’s dig deeper into what innovation is. Here is how several online sources (linked in the References below) define it:

  • Innovation is the process of doing things differently and discovering new ways of doing things.
  • Innovation is adapting to change to better meet demands of products or services.
  • Innovation is improving business processes and models, developing new products or services, adding value to existing products, services, or markets.
  • Innovation’s aim is to provide something original or unique that can have an impact on society.

Understanding and living innovation, especially in times of change

One point that is missing from this list: Innovation spares no one. It is essential for individuals and organizations, for the CEO of a company just as much as the entrepreneur who is just getting started. That said, you do not need to aim be the next Amazon or Airbnb. Small changes can help you foster an innovation mindset to proactively respond to potential disruptions.

Imagine the current pandemic a decade ago: no virtual office meetings, no video calls with family and friends, no 24/7 food delivery to your doorstep. Think about the economic and emotional impact it would have had. By all means, the economic impact today is enormous, but imagine how much worse it could have been in the past. Companies would have stopped operating with no alternatives; there would no e-commerce, no IT infrastructure, and no availability. If there wasn’t an innovative mindset and driven teams that created these products, services, and platforms, we would be in an even less fortunate scenario now.

Write (innovation) history!

“It is only the farmer who faithfully plants seeds in the Spring, who reaps a harvest in the Autumn.”
— B.C. Forbes

At this moment, we are writing history. We are living through the most disruptive period we have ever seen, a time when innovations are needed more than ever. We need to think one step ahead and take this opportunity to reinvent ourselves. We also need to make this an ongoing practice – all of us, from small and midsize businesses to big corporations. Whether you are producing something like face masks and need to rethink your supply chain management due to high demand, or you’re an events company that needs to go fully virtual in a single day, this applies to you.

I strongly believe that we will rise from this crisis with a new appreciation for innovation and change. Innovation should be a mandatory component of your daily experience and strategy instead of being regarded as a luxury – especially now.

References

For more on thriving through today’s disruption and certainty, see the “Navigating Disruption Today, Planning for Tomorrow” series.

Let’s block ads! (Why?)

Digitalist Magazine

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“Presidency is about a lot more than tweeting from your golf cart” as Trump says “much very good”

May 25, 2020   Humor
 Presidency is about a lot more than tweeting from your golf cart as Trump says much very good


“As the death toll in the coronavirus pandemic neared 100,000 Americans this Memorial Day weekend, President Trump derided & insulted perceived enemies & promoted a baseless conspiracy theory, in between rounds of golf.”

x

#MuchVeryGood is not an “English as a 1st language” construct.

Further, we’re 1 week past most graduations & heading into summer break.

Whomever wrote this tweet isn’t familiar with the schedule of our educational system.

I’m grading the operative behind this propaganda 2/10. pic.twitter.com/9OsjkbA2UV

— Lincoln’s Bible (@LincolnsBible) May 25, 2020

x

“Can you believe that, with all of the problems and difficulties facing the US, President Obama spent the day playing golf” Mr. Trump wrote in 2014. He was criticizing Mr. Obama for golfing after just 2 cases of Ebola were confirmed in the United Stateshttps://t.co/77eZjU94tZ

— Richard Dawkins (@RichardDawkins) May 25, 2020

Perhaps Howard Stern, of all people, said it best: “The oddity in all of this is the people Trump despises most, love him the most. The people who are voting for Trump for the most part … He’d be disgusted by them.” The tragedy is that they are not disgusted by him in return.

x

Donald Trump – a vain, cowardly, lying, vulgar, jabbering blowhard – is not a real “man” your father and grandfather would have respected. Nor should any man, but as I write in @TheAtlantic: especially not the ones who claim to support him the most.https://t.co/xRdplS9czc

— Tom Nichols (@RadioFreeTom) May 25, 2020

In order to think about why these men support Trump, one must first to grasp how deeply they are betraying their own definition of masculinity by looking more closely at the flaws they should, in principle, find revolting.

Is Trump honorable? This is a man who routinely refused to pay working people their due wages, and then lawyered them into the ground when they objected to being exploited. Trump is a rich downtown bully, the sort most working men usually hate.

Is Trump courageous? Courtiers like Victor Davis Hanson have compared Trump to the great heroes of the past, including George Patton, Ajax, and the Western gunslingers of the American cinema. Trump himself has mused about how he would have been a good general. He even fantasized about how he would have charged into the middle of the school shooting in Parkland, Florida, without a weapon. “You don’t know until you test it,” he said at a meeting with state governors just a couple of weeks after the massacre, “but I really believe I’d run in there, even if I didn’t have a weapon, and I think most of the people in this room would have done that too.” Truly brave people never tell you how brave they are. I have known many combat veterans, and none of them extols his or her own courage. What saved them, they will tell you, was their training and their teamwork. Some—perhaps the bravest—lament that they were not able to do more for their comrades.

But even if we excuse Trump for the occasional hyperbole, the fact of the matter is that Trump is an obvious coward. He has two particular phobias: powerful men and intelligent women.

www.theatlantic.com/…

x

100,000 dead on your watch and you have the fucking nerve to go golfing and accuse Joe Scarborough of committing murder. You despicable piece of shit.

— Rob Reiner (@robreiner) May 24, 2020

The attacks from Trump come as the country’s death toll from the virus nears the 100,000 mark and the ensuing economic devastation worsens. As criticism of Trump’s handling of the crisis has mounted, he has turned to his Twitter feed to air grievances and settle scores. He has baselessly accused a stream of perceived opponents of committing crimes, including illegal espionage and election rigging.

[…]

Trump, a president with a penchant for fanning the conspiratorial flames with fabricated allegations, seemed eager for something to use against Scarborough.

In a November 2017 tweet, the president asked when NBC would “terminate low ratings Joe Scarborough based on the ‘unsolved mystery’ that took place in Florida years ago? Investigate!”

x

President Obama has a personal responsibility to visit & embrace all people in the US who contract Ebola!

— Donald J. Trump (@realDonaldTrump) October 15, 2014

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