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Should I be ashamed of wearing Google Glass?

I’m not proud of my paling geek credentials. I’ve had Glass for several months now, and it’s not to say its been infrequently used: as a hands-free camera it’s incredibly useful, whether you’re documenting smartphones and tablets and want both hands to demonstrate, or if you’re test-driving a car and want the POV from behind the wheel.

Most days, as I’m working at my desk, I’ll be wearing Glass, watching as notifications and alerts pop into my eye-line. The recent XE12 update with Hangouts chat support makes that all the more useful. Even just the hardware itself has a sci-fi appeal to it: just as the iPad mini is probably the closest embodiment to a slim Star Trek PADD we have today, Glass – despite containing similar hardware to a low-spec smartphone – is undeniably futuristic, unusual.

That doesn’t stop me feeling like a fraud

That doesn’t stop me feeling like a fraud. Since before I started writing publicly about wearable technology, I’ve been a loud convert to the concept. I used to look at the outlandish, gawky rigs that wearables pioneers like Professor Steve Mann would don, and say “sure, I’d wear that too, if I could afford it.”

When Glass was first announced, then, it was an immediate “must have” for me. True, Explorer Edition buyers were effectively paying Google – handsomely – for the privilege of being beta-testers, but the geek appeal was off the scale. This was the man-machine crossover we’d been promised, and the prospect of getting in on the ground floor was too much to miss out on.

It could be because I’m British. Now, that might sound flippant, but there’s certainly a difference in how us Brits perceive unusual things like Glass compared to our American cousins. While I love my sarcastic, cynical countryfolk, I can’t help but admire what’s a stereotypically more gung-ho, open-minded, far less jaded approach to things that those in the US often bring to the party.

In fact, whereas some are happy to hold loud – and personal – conversations on their cellphones on the bus, I’m loathe to even have the ringer turned on. Perhaps I’m an extreme example, but I’d wager there are just as many toward my reticent end of the spectrum as there are at the more vocal end.

Ironically, though, it’s in wearables that I hold out hope for a solution to that; it’s just not in gen-1 Glass. Technology that blends more seamlessly with our bodies will help minimize what distraction it presents; better meshing of the digital world with the real world will stop us from inserting phones and tablets between ourselves and instead allow for more natural, free-flowing engagement.

Glass is a precursor but it isn’t there yet

Glass is a precursor but it isn’t there yet. It doesn’t play well with my prescription glasses (and may not even when the official solution comes out), and the battery life is poor, while the functionality – though growing each month with every OS update Google releases – is still limited and, often at the times you’re trying to demonstrate it, can be patchy in its success rate. I’d argue my feedback is just as valuable as that of those who wear it every moment they can, however; Google needs input from the shy and self-conscious too, otherwise it could – mistakenly – assume Glass was ready for release as it is today.

I’m also of a mind that periodic wear, rather than continuous, is just as legitimate a use-case for Glass: the best tool at the correct time. Right now it’s a geek’s toy, and that’s proving insufficient to overcome what social anxiety I obviously feel about wearing it – and explaining it – out in public.

I’m going to be pushing myself to change that, though, not least because the increasing capabilities Glass is gaining are tipping things ever-further in its favor. Google’s challenge – and the challenge of companies pushing wearable tech in general – is that there are plenty of others out there much like me, who need sufficient justification to overcome not only skepticism but self-consciousness, and for whom there’s more than just price standing in the way of sporting a computer on their face.

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Doctors Are Wearing The New Google Glass While Seeing Patients

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You could be forgiven for assuming that Glass, Google’s head-mounted augmented-reality device, had been effectively dead since 2024. But as Google’s sister company X, the Moonshot Factory, announced on Tuesday, the project has been pivoting to a business-to-business model over the past two years. The new, updated version of the device is known as Glass Enterprise Edition, and it’s been put to use at companies like Boeing, DHL—and in your physician’s office.

Going to the doctor today is “a pretty tragic experience,” says Ian Shakil, the CEO and co-founder of a company called Augmedix. Its platform enables physicians to wear Glass Enterprise Edition as they see patients, while remote medical scribes fill out the electronic medical records based on what they hear and see from the visit.

The doctor’s office experience is unpleasant, Shakil claims, thanks to all the time the physician spends looking at a screen and typing, as opposed to just focusing on interacting with the patient at hand. Augmedix’s message to doctors is: “Put on Glass, go have normal conversations with your patients.” Meanwhile, the audio and video streamed from the Glass go to a trained medical scribe, who may be located in a place like California, India, or Bangladesh, and whose job it is to fill in the electronic health records.

The integrated display on Glass can be used to provide the doctor with information about the patient in real time as they perform the examination.

The system is thus a fusion of a high-tech streaming service with a tried-and-true human component on the other end. And while it might seem like AI and voice-recognition software might be well-positioned to do a job like this, Shakil says that what the scribes are doing isn’t transcribing the visits word for word, which would result in a block of text, but instead producing a “structured medical note” from the conversation.

Some people will likely find it creepy that their doctor is beaming audio and video to a remote assistant, especially if they’re in their skivvies. But the final decision about the system’s usage is determined by the patient. It’s not a mandatory part of receiving care.

Glass Enterprise Edition Alphabet’s X

Patients are informed before they see the doctor that the physician will be using Glass, and have the chance to allow it or not—but Shakil says 98 percent do consent. As for that streaming video, it can be switched off at the appropriate times, and when the video is on, a green light clearly indicates that for the patient. The doctor can switch to audio-only mode to continue the note-taking without video, or the system can be shut off completely.

Augmedix first started using Explorer-edition models (that’s what it was called when it was marketed to consumers) of the device in 2013, Shakil says. Today, all their physicians are using the new Enterprise version. Over 1,000 people work at Augmedix around the globe, most of whom are the scribes or apprentice scribes, according to Shakil; nearly 1,000 physicians use it from the likes of healthcare organizations such as Dignity Health, and they’ve partnered with 12 health systems in total.

Google says that the new version of Glass has a better camera and battery, and more processing power. Instead of being marketed to individuals, as it was back in its “Explorer” days, Google is only selling it through partners like Augmedix for industry-specific uses, where they say it’s helping to boost efficiency at companies like DHL.

“Healthcare is increasingly a team sport,” says Shakil. Often there may be others in the room anyway, or specialists looking at your records.

“The era of you and your doctor, that private visit and no one else,” Shakil continues, “is really an antiquated view on healthcare.” In other words: good-bye, Norman Rockwell; hello, Glass Enterprise Edition.

What Should Be The Backbone Of Digital Marketing?

Crucial Digital Marketing Attributes Content Marketing

Getting the most out of your content marketing efforts is not an easy task, especially if it involves keeping your audience engaged. A good content marketing strategy can help you keep them engaged and attract more potential clients.

A well-designed content marketing strategy can help boost your website traffic and build a strong brand. Before you make a purchase decision, it’s important that your potential customers thoroughly research the various features of a product or service to see which one they prefer.

Your product or service’s descriptions are the only way potential customers can see how it’s better. Your descriptions should be clear and contain the necessary information to make informed decisions. In a recent update, Google prioritized high-quality content.

One of the most important factors that you should consider when it comes to content marketing is ensuring that it’s updated. Having the best possible content can help you attract more potential customers and keep them engaged.

One of the most important factors that you should consider when it comes to content marketing is understanding your audience. This will allow you to provide the best possible content to your customers. Having the right understanding of your audience can help you achieve your goals and improve the effectiveness of your marketing efforts.

Getting started with content marketing is very important if you want to improve the effectiveness of your business. It can be done by establishing an audience and focusing on your customers’ needs. According to a survey, 79% of businesses have already started using content marketing, and 10% of them fail because they lack knowledge about how to implement it effectively.

SEO

Search engine optimization is a process that aims to improve the ranking of a website on search engines such as Google and Bing. It involves developing and implementing strategies that will help improve a website’s visibility.

Getting to the top of search engines is very difficult, especially since cheating is not allowed. In order to achieve this, your company should focus on developing and implementing effective SEO techniques.

Organic traffic is generated by customers who are actively looking for a particular solution. This means that if you want to attract and retain their attention, you need to provide them with the necessary information and solutions that they are searching for.

If you haven’t already started using blogging as part of your marketing strategy, it’s time to start. It’s very easy to improve your search engine ranking when it comes to blog content. In addition to being able to provide relevant and timely content, it can also help boost your website’s traffic.

Getting the most out of your blog is very important in order to improve its search engine ranking. One of the most effective ways to do this is by changing the title, keywords, and media of your blog. This will allow search engines to see that it is fresh and relevant.

One of the most important factors that you should consider when it comes to improving your search engine ranking is working with other people online. This will allow you to build a stronger and more engaging relationship with your target customers. Having other people talk about your brand will also help search engines find your content and provide recommendations.

Social media is very important for businesses, as it can help them reach their target customers and improve their online presence. Having a strong online presence helps search engines find your site and recommend it to others. YouTube is also a great tool for SEO.

Analytics

One of the most critical components of any digital marketing strategy is having the necessary tools and reports to measure and analyze how they are adding to your business’s bottom line.

Having the necessary tools and reports to measure and analyze how they are adding to your business’s bottom line is one of the most critical components of any digital marketing strategy. Before you launch a campaign, it’s important that you identify the key performance indicators and metrics that will help you improve the efficiency of your marketing efforts. Having the right metrics and KPIs can help us make informed decisions and improve the effectiveness of our campaigns.

Getting the proper data to measure and analyze how your campaigns are performing is one of the most important factors that you should consider when it comes to optimizing your digital marketing efforts. Having the proper tools and reports can help you make informed decisions and improve the efficiency of your marketing campaigns.

Getting the proper data is very important in order to monitor and analyze how well your campaigns are performing. Having the right reports can help you learn from your marketing data and improve the efficiency and effectiveness of your campaigns.

Conclusion

A digital marketing campaign is a process that involves using various digital platforms to connect with potential customers. Most businesses utilize websites, social media, email, and search engines to reach their target audience.

Due to the increasing number of people using the internet, offline marketing has become less effective. The goal of marketing is to connect with your audience at the right time and in the right place. Today, this is done through the internet.

One of the most effective ways for businesses to attract and retain customers is through digital marketing. Through SEO-friendly blog posts, a business owner can create content that is focused on the specific niche of his or her business. He or she can also promote the services and products through social media and email campaigns.

Libra Will Be Interoperable. Facebook Should Be Too

Recently, the UK’s Information Commissioner’s Officer published a joint statement which raises questions about Facebook Libra’s potential use and misuse of personal data and disregard for the privacy of Libra network users.

The letter says, “The involvement of Facebook Inc. as a founding member of the Libra Association has the potential to drive rapid uptake by consumers around the globe, including in countries which may not yet have data protection laws in place. Once the Libra Network goes live, it may instantly become the custodian of millions of people’s personal information. This combination of vast reserves of personal information with financial information and cryptocurrency amplifies our privacy concerns about the Libra Network’s design and data sharing arrangements.”

The letter is signed by data and privacy commissioners from the UK, USA, EU, Australia, Albania, Canada, and Burkina Faso. It ends with six questions for Libra to answer about how data and privacy will be ensured: easy to use privacy controls for users; security by design principles; lawful processing of data; consistency across infrastructure and jurisdictions, and so on.

These are sensible and measured questions. However, their fear is misplaced and only shows public authorities in general are still struggling to find the right angle of attack against the Libra project. Their questions ought to be directed towards Facebook, not Libra.

Indeed, it is not Libra itself which is so objectionable, but rather the monopolistic control of the main user network in which Libra would be deployed. In fact, simple solutions exist to rein in the network effects which make Libra so threatening.

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Libra-Facebook relationship

However, the characteristics of Libra took even the most knowledgeable observers by surprise and upped the ante. For in lieu of another invasion of our privacy, it is now no less that the global financial system stability which is threatened. In the wake of the announcement, G7 even felt obliged to appoint a special committee on the topic.

The surprise is that from a free-market and privacy standpoint, Libra’s intentions break away from Facebook usual hegemonic practices. Instead of going it alone, this time they plan to make an alliance with 99 other founding members: leviathans of technology and payment (eBay, Uber, Visa, Mastercard, and PayPal) as well as NGOs who will guarantee Libra’s stability. In fact, Facebook will hold only 1% of the voting rights in the organization which will control Libra’s reserves.

Global concerns

The white paper plans to transform Libra into a fully decentralized currency after 5 years – ie not controlled by the sole 100 funding members anymore – could actually be the biggest threat of all: who could the authorities subpoena then ? Just like Bitcoin, the Libra will have become faceless…

No wonder that public authorities in many countries see this as an outright attack on their national sovereignty, one essential attribute of which is issuing currency.

But, a month after the release of the Libra white paper, they are still looking for the right angle to stop the toothpaste from going out of the proverbial tube.

Libra wants regulatory body approval

As far as financial regulation is concerned, Mr Marcus pledged he would comply with all applicable laws such as anti-money laundering, and claimed that Libra would not launch until it had obtained all the necessary approvals from regulatory bodies. From the public authorities’ point of view, this is obviously a much better situation than with Bitcoin which remains nonetheless legal in most countries.

From the anti-trust angle, it is difficult to see how the diversity of origins of the founding members and the open-source philosophy behind Libra could make them vulnerable. On the contrary, they claim, not without reasons, that Libra is bringing long-awaited innovations to the payment and banking industry that will benefits consumers globally as well as bring financial inclusion to the underbanked people of the world.

So Libra is not in itself a credible target for governments and hides the real issue, the absolute need to regulate social networks.

For Libra would be just another interesting cryptocurrency with limited prospects if Facebook had not been able to onboard a third of all human beings on its closed network.

A data monopoly

In the real economy, whether we are considering physical transport, energy or telecom infrastructures, there is (in principle) a clear distinction between the network, and those authorized to use it. In no case may any one party gain sole control of the infrastructure for their own use.

Related: Facebook will not Launch Libra Cryptocurrency until the Official Permissions of the USA

Facebook, however, is both the exclusive operator of the social network and the operator of the services using the network, including the future Libra.

Given these issues, a classic antitrust approach cannot work. Breaking up Facebook, as the US once did with Standard Oil or the Bell System, amounts to treating the symptoms and not the causes. The same market conditions would simply produce a new monopoly.

The solution revealed: Inter-operability

In fact, ways of protecting fair competition in the world of data networks are not different from those in the real economy. Liberalization of the telecom industry in the early 90’s is a good example. A principle of inter-operability was established so that no dominant party could interfere with competition. For instance, today’s UK mobile phone market is split among different operators. Just as a subscriber to one network can call or be called by subscribers from one of the other networks, so I should be able to move freely from one social network to another. Quitting Facebook should not have to mean giving up communication with my Facebook contacts and their personal data (as long as they don’t “unfriend” me of course).

Another example: under the second European Directive on payment services, I can now access my bank accounts from other financial institutions. If we were to apply this principle to the online economy, I would be able to authorize the service providers of my choice to access my personal data, regardless of which organization initially collected this information.

Inter-operability would put an end to the unfettered domination of Facebook and similar companies. It would significantly reduce the number of their users, which would benefit new players on the market. There would be a more level playing field in terms of access to data and companies would compete on the quality of their services to users and AI algorithms instead.

Ironically enough, during his hearing, Mr. Marcus himself stressed as a benefit that the Calibra application will itself be fully interoperable, meaning users will make and receive payments in Libras to and from users of competing for wallet applications. But when asked by Senator Warner from Virginia if Facebook would be willing to apply this same principle to its traditional social network applications, Mr. Marcus smiled and replied: ‘I cannot commit for other parts of the company’.

Redirecting public scrutiny from the woes caused by Facebook centralized social network to the ones a decentralized managed currency could unleash might after all be a clever way for Mr. Zuckerberg to confuse the critics. But Libra is only as strong as the Facebook network is large. If the government want to control the former, they must first deal with the latter.

Jean-Cyril Schütterlé

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Should Police Scanners Be Public?

The past week has seen a torrent of information, the majority inaccurate, gushing from the faucets of Twitter and Facebook and Reddit and cable news and tabloids and blog posts. The story has become not so much what happened as what didn’t happen; as BuzzFeed notes, the most valuable service a respectable publication can perform right now is not to be the first but to act as Virgil, guiding the public through the morass of information they already have.

In the midst of all this, one of the most difficult sources of information to parse has been one of the oldest: the police scanner. Until this morning, feeds from the Boston Police Department, broadcast over the web and through apps, were publicly available to anyone. Broadcastify, which calls itself “the radio communications industry’s largest platform for streaming live audio for public safety, aircraft, rail, and marine related communications,” had tens of thousands of listeners. Many of those listeners relayed the chatter they heard to Twitter or Reddit, if members of the public, or through news outlets, if members of the media.

Police scanners seem like reliable sources of information, a direct line to those who know more than anyone else about what’s going on on the ground. News reporters and organizations are posting direct quotes from scanners without any equivocation. You could almost see them thinking, “this stuff originates from the police themselves! It must be real!” Some of these channels, which are essentially just like any AM/FM station, are available to the public, or at least any member of the public with a computer (or, in the past, a $100 scanner). Those are mostly calls from dispatch, according to a detective from the Radnor, Pennsylvania police department who chatted with me about how scanners work. “You can hear police calls, fire calls, EMS calls, public works calls,” he said. (Radnor is the hometown of Sunil Tripathi, a Brown student who became a prime suspect in the minds of the public for a few hours last night.) Lindsay Blanton, CEO of the company that owns Broadcastify, confirmed that, saying “Our feed provider terms of service restrict the broadcast of any law enforcement communications that are not routine dispatch frequencies and talkgroups.”

The police doesn’t much care that these are available to the public. They’re not provided as a service to the public or out of any kind of desire to transparency; many police forces just don’t bother encrypting these radio feeds because they’re not seen as sensitive. This isn’t the only way they communicate; on-duty officers have secure, encrypted lines as well, the detective from Radnor tells me. It’s important to note that there’s no law requiring police dispatch lines to be public; in fact, many departments, like the Pasadena Police Department, have decided to encrypt all of their frequencies. Pasadena cites concern for victims, whose names and locations are often broadcast over the channel, as the reason for the change.

What you hear on the scanner is what the dispatcher or communications center hears: a call that something is happening that requires investigation, and conversation that comes from addressing that call. That doesn’t make it true, of course, nor does the dispatcher or any police officer make any claim to that effect. When somebody calls the police station and says they see a suspicious person lurking in an alley, what the public hears through the scanner is “possible suspicious person lurking in an alley.” If it turns out to be a chair with a coat on it, that’s no big deal for the police; they investigated and resolved the call. But if a member of the media hears that, and the call happens to take place in a city in which a recent bombing has killed three and injured hundreds, that chair with a coat can turn into a terrorist with one tweet.

Early this morning, the Boston Police Department tweeted this:

In response, Broadcastify shut down its scanner feeds, saying “MA State PD and Boston Police have requested via social media to not post search locations for the Boston bombing suspects – the Boston PD feed is temporarily offline due to this request.” This is an indirect request, and a respectful response from Broadcastify; the scanner feed isn’t “offline,” it’s merely harder to find, to try to tamp down the flow of misinformation. Lindsay Blanton, from Broadcastify, told me via email that “we did not receive any formal request – we’re just making the temporary decision for now in light of the extraordinary events.”

An academic paper from a doctoral student at the Indiana University School of Journalism examines the legality and ethics of tweeting information from police scanners more closely. Here’s the conclusion, with the important part emphasized by me:

Tweeting public safety radio traffic – while probably legal and often beneficial – should be done sparingly and under pre-set guidelines designed to minimize the spread of flawed information and avoid compromising the safety of emergency personnel, the public, and media. If followed, such precautions should lessen the need – if not the likelihood – for an aggrieved party to seek legal recourse for alleged defamation.

Broadcastify is a perfect example of why the most important element of the debate is the need for specific rules. Though Broadcastify did eventually cut off the flow of scanner information to Twitterers, it was only done after several innocents had already suffered the consequences of false accusation.

* * *

It generally doesn’t hurt that scanners are public. The law states that any criminal in possession of a scanner during the commission of a crime has an increased punishment, to stop them from using dispatch information to make their illegal activities easier, and the most sensitive information isn’t exchanged via these channels. But scanners are assumed to be at best a vital part of law enforcement transparency, and at worst harmless, or even funny. They’re for people like these guys to get their “personal safety, neighborhood crime awareness, emergency preparedness, and excitement!” It’s only now, with the unholy combination of a massive crime story and a relentless need for new information, that police scan dispatches are elevated to the status of unimpeachable, insider fact.

So now we’re reduced to the Boston Police Department having to issue a tweet with the hashtag #MediaAlert to tell us what a police scanner is and when to shut up about it. There’s no law that says Broadcastify had to stop broadcasting the feed that led to an innocent kid from Pennsylvania, among many others, becoming national terrorist suspects. We need some sort of guidance to respond to the increased desire and outlets for information.

What Should Be Done To Make The Best Of Data?

Every possible organization that one can think of relies on data to achieve the set objectives. On that note, having access to data that isn’t smart enough to get goals accomplished poses a hurdle. It is thus important to have data that is transformed in a manner that can cater to the needs and objectives of the organization. With most organizations relying on

Outline the Steps of the Process

First things first, no goal is achieved unless you have a clearer picture of what needs to be done. It is for this purpose that the organizations need to have a clear plan in mind with equal attention laid on each of the steps to follow.

Catching hold of the right data

With humungous data available, it is not possible to screen every bit of it to derive meaningful insights for the organizations. Thus, finding out what data is reliable and would serve the purpose is the need of the hour. Rather than aiming for the maximum number of observables, the focus should rather be on creating a high-quality dataset.  

Working on the model

An AI model revolves around a set of inputs and outputs. The number of outputs must greatly exceed the number of inputs to yield a generalized model. End of the day, the aim should be to reduce the dimensionality of and introduce relationships in the data, which minimizes the number of outputs required to adequately train a model.  

Machine learning

The reason why machine learning should be applied is that the machine-learning models aim at capturing the statistical portion of the data.  

Implementing and validating the model

After ensuring that everything is in place, it is now time to implement your model followed by proper validation. As a team, your role doesn’t just end here. You need to ensure that the models are continuously reviewed to live up to the expectations.  

Every possible organization that one can think of relies on data to achieve the set objectives. On that note, having access to data that isn’t smart enough to get goals accomplished poses a hurdle. It is thus important to have data that is transformed in a manner that can cater to the needs and objectives of the organization. With most organizations relying on Artificial Intelligence (AI) and machine learning , the necessity of dealing with the right data is all the more important for the sole reason that the models employed aim at obtaining meaningful insights. No wonder data is vast and one shouldn’t ideally fall short of it while aiming at the objectives. However, what is worth noting is that not all the data that one has access to is important. As an organization, it is essential to have a fair knowledge about what data is reliable and would fetch the desired results. Since a majority of the companies rely on AI, one of the key mantras to success is having an automation environment with reliable historian data. Additionally, the companies must be able to adapt their big data into a form that is amenable to AI. What has been a common observation and the reason why certain companies tend to fail is – poor integration of operational expertise into the data science process. Yet another point that is worth making a note of is the fact that applying machine learning only after processed data has been analyzed, enriched, and transformed with expert-driven data engineering holds the potential to yield fruitful results. As far as making the best of data is concerned, one can always follow the below steps and see how all of this works wonders –First things first, no goal is achieved unless you have a clearer picture of what needs to be done. It is for this purpose that the organizations need to have a clear plan in mind with equal attention laid on each of the steps to chúng tôi humungous data available, it is not possible to screen every bit of it to derive meaningful insights for the organizations. Thus, finding out what data is reliable and would serve the purpose is the need of the hour. Rather than aiming for the maximum number of observables, the focus should rather be on creating a high-quality chúng tôi AI model revolves around a set of inputs and outputs. The number of outputs must greatly exceed the number of inputs to yield a generalized model. End of the day, the aim should be to reduce the dimensionality of and introduce relationships in the data, which minimizes the number of outputs required to adequately train a chúng tôi reason why machine learning should be applied is that the machine-learning models aim at capturing the statistical portion of the data.After ensuring that everything is in place, it is now time to implement your model followed by proper validation. As a team, your role doesn’t just end here. You need to ensure that the models are continuously reviewed to live up to the expectations. Needless to say, deploying AI and machine learning is a little tough but with the right teams in place, it is worth it. Companies should now focus on upskilling their existing process experts in analytics tools and agile ways of working. Companies engineering their big data to include knowledge of the operations and forming cross-functional data science teams that include employees who are capable of bridging the gap between machine-learning approaches and process knowledge would yield fruitful results.

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