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Whether you are looking to gain awareness, improve SEO, or increase sales, having great exposure can help you get there. But PR is not a band-aid for an overarching business problem–nor is it a get rich fast technique.
A great PR strategy can take many years to build. Over the years, I’ve seen many companies start their efforts, only to stop before they’ve given the program enough time to develop. I’ve heard dozens of marketers and founders explain that they quit their PR efforts after their pitch didn’t get picked up by enough outlets in the first few week. Gaining great coverage takes time, pitch optimization, and persistence.
Often times, if a brand could have taken a step back after a rejected story to tweak their angle and try again, the second story they pitch could have been widely successful. Here’s why you shouldn’t throw in the towel for your PR outreach just yet:
1. Relationships take time to build.
Imagine you are at a party. You immediately start talking about you, your business, and your news. Very quickly, many people will not want to talk with you.
The same holds true when you’re building relationships with the media. It takes time to get to know a reporter and what they are writing about and then creating relevant pitches that are helpful to them. When you build trust and rapport with reporters, they’ll be more likely to open your emails, which is the first step to gaining great coverage.
You can build a better relationship with reporters by becoming well versed with their past writings and looking for opportunities to tell them stories of interest. Take a look through their Twitter accounts and personal websites to learn more about what they’re covering and the news that is important to them.
When you reach out to a reporter for the first time, show them that you are knowledgeable about their area of coverage and that your story fits their angle. When we reach out to reporters we make sure to spend time reading their past work to ensure our pitch is the right fit for their area of expertise. It can be easy to burn a press bridge simply by not personalizing an email enough–take your time, do your research, and get to know reporters for the long term. Slow and steady wins the race.
2. SEO is a long-term game.
When you receive a press mention, you’ll likely see a spike in traffic on the day it’s published–but don’t discount the future traffic. If you are a mattress company and you get listed as “The Best Mattresses Ever Made,” you’ll benefit from both the spike and also later from people who are searching for mattresses and come across the article. Traffic from press articles should be monitored for months to come, even after publication.
An authoritative link will not only drive traffic, but will also help your website in the search engine rankings. This boost will not happen instantly. With time and relevant inbound links, you’ll see not just your referral traffic grow, but also your organic search traffic from Google.
3. Press takes commitment–and a bit of luck.
It takes a while to learn about the best way to pitch your product. Each time you pitch, you’ll learn more about what copy and message resonates with reporters.
If you’re not seeing any success, it does not mean you don’t have an interesting story. It might mean you are pitching to the wrong reporters, your email subject line needs work, or you simply didn’t follow up.
By tracking your emails with a tool like SideKick or Yesware, you’ll be better able to see who is opening your mails, what they’re clicking on, and how many times they went back to the email. You can use this data to refine your pitch the next time. With the media always changing, it also takes a bit of luck to pitch at the right time to the right reporter with the right story.
Pitching takes a strong backbone and you’ll get a lot of rejections. If you haven’t had success yet, keep trying. And if you’ve been pitching for months with still no results, it might be time to call in a PR pro to help you optimize your pitch and press kit.
If you’re looking to reap the benefits of the press, start early, optimize often, and plan your strategy for the long haul. This time next year, you’ll be glad you stuck with it.
IPsoft is, in many ways, an unusual entrant into the crowded, but burgeoning, artificial intelligence industry. First of all, it is not a startup, but a 20-year-old company and its leader isn’t some millennial savant, but a fashionable former NYU professor named Chetan Dube. It bills its cognitive agent, Amelia, as the “world’s most human AI.”
It got its start building and selling autonomic IT solutions and its years of experience providing business solutions give it a leg up on many of its competitors. It can offer not only technological solutions, but the insights it has gained helping businesses to streamline operations with automation.
Ever since IBM’s Watson defeated human champions on the game show Jeopardy!, the initial excitement has led to inflated expectations and often given way to disappointment. So I recently met with a number of top executives at IPsoft to get a better understanding of how leaders can successfully implement AI solutions. Here are four things you should keep in mind:
1. Match The Technology With The Problem You Need To Solve
AI is not a single technology, but encompasses a variety of different methods. In The Master Algorithm veteran AI researcher Pedro Domingos explains that there are five basic approaches to machine learning, from neural nets that mimic the brain, to support vector machines that classify different types of information to graphical models that use a more statistical approach.
“The first question to ask is what problem you are trying to solve.” Chetan Dube, CEO of IPsoft told me. “Is it analytical, process automation, data retrieval or serving customers? Choosing the right a technology is supremely important.” For example, with Watson, IBM has focused on highly analytical tasks, like helping doctors to diagnose a rare case of cancer.
With Amelia, IPsoft has chosen to target customer service, which is extraordinarily difficult. Humans tend not to think linearly. They might call about a lost credit card and then immediately realize that they wanted to ask about paperless billing or how to close an account. Sometimes the shift can happen mid-sentence, which can be maddening even for trained professionals.
So IPsoft relies on a method called spreading activation, which helps Amelia to engage or disengage different parts of the system. For example, when a bank customer asks how much money she has in her account, it is a simple data retrieval task. However, if a customer asks how she can earn more interest on her savings, logical and analytical functions come into play.
2. Train Your AI As You Would A New Employee
Most people by now have become used to using consumer facing cognitive agents like Google voice search or Apple’s Siri. These work well for some tasks, such as locating the address for your next meeting or telling you how many points the Eagles beat Vikings by in the 2018 NFC Championship (exactly 31, if you’re interested).
However, for enterprise level applications, simple data retrieval will not suffice, because systems need domain specific knowledge, which often has to be related to other information. For example, if a customer asks which credit card is right for her, that requires not only deep understanding of what’s offered, but also some knowledge about the customer’s spending habits, average balance and so on.
One of the problems that many companies run into with cognitive applications is that they expect them to work much like installing an email system — you just plug it in and it works. But you would never do that with a human agent. You would expect them to need training, to make mistakes and to learn as they gained experience.
“Train your algorithms as you would your employees” says Ergun Ekici, a Principal and Vice President at IPsoft. “Don’t try to get AI to do things your organization doesn’t understand. You have to be able to teach and evaluate performance. Start with the employee manual and ask the system questions.” From there you can see what it is doing well, what it’s doing poorly and adapt your training strategy accordingly.
3. Apply Intelligent Governance
No one calls a customer service line and asks a human to talk to a machine. However, we often prefer to use automated systems for convenience. For example, when most people go to their local bank branch they just use the ATM machine outside without giving a thought to the fact that there are real humans inside ready to give them personalized service.
Nevertheless, there are far more bank tellers today than there were in before ATMs, ironically due to the fact that each branch needs far fewer tellers. Because ATMs drastically reduced the costs to open and run branches, banks began opening up more of them and still needed tellers to do higher level tasks, like opening accounts, giving advice and solving problems.
Yet because cognitive agents tend to be so much cheaper than human ones, many firms do everything they can to discourage a customer talking to a human. To stretch the bank teller analogy a little further, that’s almost like walking into a branch with a problem and being told to go back outside and wrestle with the ATM some more. Customers find it incredibly frustrating.
So IPsoft stresses to its enterprise customers that it’s essential that humans stay involved with the process and make it easy to disengage Amelia when a customer should be rerouted to a human agent. It also uses sentiment analysis to track how the system is doing. Once it becomes clear that the customer’s mood is deteriorating, a real person can step in.
Training a cognitive agent for enterprise applications is far different than, say, Google training an algorithm to play Go. When Google’s AI makes a mistake, it only loses a game, but when an enterprise application screws up, you can lose a customer.
4. Prepare Your Culture For AI As You Would For Any Major Shift
There are certain things robots will never do. They will never strike out in a little league game. They will never have their heart broken or get married and raise a family. That means that they will never be able to relate to humans as humans do. So you can’t simply inject AI into your organizational culture and expect a successful integration.
“Integration with organizational culture as well as appetite for change and mindset are major factors in how successful an AI program will be. The drive has to come from the top and permeate through the ranks,” says Edwin Van Bommel, Chief Cognitive Officer at IPsoft.
In many ways, the shift to cognitive is much like a merger or acquisition — which are notoriously prone to failure. What may look good on paper rarely pans out when humans get involved, because we have all sorts of biases and preferences that don’t fit into neat little strategic boxes.
The one constant in the history of technology is that the future is always more human. So if you expect to cognitive applications simply to reduce labor, you will likely be disappointed. However, if you want to leverage and empower the capabilities of your organization, then the cognitive future may be very bright for you.
1. Don’t complain.
Instead, model the ability to pick yourself up in the face of setbacks. According to Stephanie Marston, psychotherapist, consultant and co-author of Type R: Transformative Resilience for Thriving in a Turbulent World, children learn resilience when they see their parents being agents of change instead of passive complainers.
2. Let kids climb trees and handle sharp objects.
According to a study published in Evolutionary Psychology, risky play–the kind where someone actually could get hurt–is good for kids. Researchers suggest that the fear kids experience when climbing at great heights, being near a cliff or handling a knife keeps them alert and careful and teaches them how to cope with potentially dangerous situations. And over time, mastering such scary situations has an “anti-phobic” effect which results in lower levels of anxiety overall.
3. Limit the use of electronic media, especially in the evening.
Researchers analyzed the sleep quality of 530 German three-year-olds and found that the kids who consumed higher amounts of electronic media had more problems with sleep, including resistance going to sleep, sleep anxiety and sleepiness during the day. Plus, other researchers have found that the brains of little kids can be permanently altered when they spend too much time using tablets and smartphones. Specifically, the development of certain abilities is impeded, including focus and attention, vocabulary, and social skills.The American Academy of Pediatrics (AAP) says children younger than 18 months should have no screen time at all, other than video-chatting. For kids ages two to five, it recommends limiting screen time to one hour a day. For older kids, it’s a matter of making sure media doesn’t take the place of adequate sleep, exercise, and social interaction. The AAP also says parents should make the dinner table, the car, and bedrooms media-free zones.
4. Read to them.
Researchers at the New York University School of Medicine have found that babies whose parents read to them have better language, literacy, and early reading skills four years later before starting elementary school. And kids who like books when they’re little grow into people who read for fun later on, which has its own set of benefits. That’s according to Dr. Alice Sullivan, who uses the British Cohort Study to track various aspects of 17,000 people in the U.K. “We compared children from the same social backgrounds who achieved similar tested abilities at ages five and 10, and discovered that those who frequently read books at age 10 and more than once a week when they were 16 had higher test results than those who read less,” she writes for The Guardian. “In other words, reading for pleasure was linked to greater intellectual progress, in vocabulary, spelling, and mathematics.”
5. Make them work.
In a 2015 TED Talk, Julie Lythcott-Haims, author of How to Raise an Adult and the former dean of freshman at Stanford University, cites the Harvard Grant Study, which found that the participants who achieved the greatest professional success did chores as a child.
6. Let them fail.
According to Dr. Stephanie O’Leary, a clinical psychologist specializing in neuropsychology and author of Parenting in the Real World: The Rules Have Changed, failure is good for kids on several levels. First, experiencing failure helps your kids learn to cope, a valuable life skill. It also provides them with the experience which helps them to relate to peers in a genuine way. Being challenged also instills the need for hard work and sustained efforts, and also demonstrates that these traits are valuable even without the blue ribbon, gold star, or top score. Over time, children who have experienced defeat build resilience and are more willing to attempt difficult tasks and activities because they are not afraid to fail. And, rescuing children sends the message that you don’t trust them. “Your willingness to see your child struggle communicates that you believe they are capable and that they can handle any outcome, even a negative one,” she says.
7. Be a role model for fitness.
High achieving adults consistently make exercise a priority and if you want your children to grow up fit and active, you need to practice doing it yourself. Researchers at the University of California conducted a study which found that girls who perceived their parents exercised at least three times a week were about 50 percent more active than girls with sedentary parents.
8. Don’t tell them they can grow up to be anything they want.
According a survey of 400 teenagers, conducted by market research agency C+R Research, young Americans aren’t interested in doing the work that will need to be done in the years to come. Instead, they aspire to be musicians, athletes, or video game designers, even though these kinds of jobs only comprise 1 percent of American occupations. In reality, jobs in health care or in construction trades will be golden in future decades. Why not steer them into well-paying professions in which there will be a huge shortage of workers?
It’s not so much that Android 8.1 is a big jump forward for most end-users. It’s not. Google’s major 2017 Android improvements came with Android 8.0. With a smartphone containing a Pixel Visual Core chip, it’s a dramatically different story.
1) Visual Core
The Visual Core is Google’s first custom-designed consumer processor. It’s a dedicated image processing chip. Today, it’s only in the new Pixel 2 and Pixel 2 XL. Tomorrow, it may be appearing in other smartphones.
With Android 8.1, the Visual Core chip has been activated and the results are dramatically better photos. First, it takes much faster High Dynamic Range (HDR) photos. By taking a series of photographs in micro-seconds, HDR-enhanced cameras do a much better job of capturing the full range of darkest blacks and lightest whites than older digital cameras.
With Google’s HDR+, your smartphone camera takes a rapid burst of pictures. The Visual Core chip then combines them five times faster than previous generation of processors into one superior picture. You may not notice the speed, but what you will notice is how much more detail you’ll get from low-light photographs.
You used to only be able to take HDR+ photos using the Google photo app. Now, third-party camera apps, which use the Android Camera application programming interface (API), such as Instagram and Snapchat, can also take advantage of HDR+’s superior processing for better photos.
2) Neural Network API
Any device which can upgrade to Android 8.1, which for now are the Pixel 2 and 2 XL, the Pixel 1 and 1 XL, the Pixel C tablet, and the Nexus 6P and 5X, can make use of Google’s Neural Networks API (NNAPI). While as a user you won’t notice anything immediately from this improvement, Android developers will. NNAPI is designed to make it possible to run machine-learning (ML) on mobile devices. This API provides a base layer, higher-level, ML framework. This, in turn, can be used by Google’s TensorFlow Lite.
What this means for you as a user is you can expect to see some very interesting smart applications coming your way soon. For example, by this time next year, you can expect speech recognition and language translation apps, which will approach Star Trek-levels of coolness.
3) Bluetooth battery levels measurements
Do you get sick and tired of not knowing if your Bluetooth earphones or headset are about to die on you? I know I do. With Android 8.1, you’ll find a Bluetooth battery display in the Bluetooth settings. I’d still rather have it on the top status bar, but this is a lot better than fumbling with my Bluetooth gadgets.
4) Better screen management
On some smartphones, notably the Pixel 2 XL, some people were seeing screen burn-in. If you don’t recall this ugly blast from old style CRT display’s past, screen burn happens when the same screen elements — such as the navigation icons or the clock — are always on. After time, these elements are “burned” into the display so their ghostly presence remains even when they should be gone.
With Android 8.1, smartphones now vary how these are displayed. The result? The end of screen burn.
5) New look
There aren’t any major changes to the interface, but there are some useful ones. These include the Pixel Launcher. This makes it easier than ever to access Google search functions and installed apps. Android’s quick settings are transparent now so you can still see a hint of the main screen beneath it. There are also new launcher themes.
All-in-all, Android 8.1 is a good step forward. What I’m really looking forward to though is seeing more smartphone vendors bringing it to their flagship phones. Thanks to Google’s Project Treble.
Before Treble, which first appears in Android 8.0, when Google launched a new Android version, the chip OEMs, such as Mediatek and Qualcomm, had to add drivers so their silicon could run it. Then the device vendors added their customizations. Finally, the carriers had to bless the update. Then, and only then, could you get a new version of Android on your old phone. What a mess!
Project Treble has redesigned Android to make it easier, faster, and cheaper for manufacturers to update devices to a new version of Android. It does this by separating the device-specific, lower-level software — written mostly by the silicon manufacturers — from the Android OS Framework.
By working with the chipset OEMs, the vendor interface is validated by a Vendor Test Suite (VTS). In short, Google is cutting out some of the fat, which makes Android updates so slow.
If the phone vendors cooperate by not adding too much of their own spice to the stew, many of you may finally see Android 8 and 8.1 on your phones before I’m writing about the release of Android 9.
Your passwords are a first line of defense against many internet ills, but few people actually treat them that way: Whether it’s leaning on lazy Star Wars references or repeating across all of your accounts—or both—everyone is guilty of multiple password sins. But while they’re an imperfect security solution to begin with, putting in your best effort will provide an immediate security boost.
Don’t think of the following tips as suggestions. Think of them as essentials, as important to your daily life as brushing your teeth or eating your vegetables. (Also, eat more vegetables.)
1. Use a password manager. A good password manager, like 1Password or LastPass, creates strong, unique passwords for all of your accounts. That means that if one of your passwords does get caught up in a data breach, criminals won’t have the keys to the rest of your online services. The best ones sync across desktop and mobile, and have autocomplete powers. Now, rather than having to memorize dozens of meticulously crafted passwords, you just have to remember one master key. How do you make it as robust as possible? Read on.
2. Go long. Despite what all those prompts for unique characters and uppercase letters might have you believe, length matters more than complexity. Once you get into the 12-15 character range, it becomes way harder for a hacker to brute force, much less guess, your password. One caveat: Don’t just string together pop culture references or use simple patterns. Mix it up! Live a little! A quick for instance: “g0be@r$ ” does you way less favors than “chitown banana skinnydip.”
3. Keep ’em separated. If and when you do deploy those special characters—which, if you opt against a password manager, lots of input fields will force you to—try not to bunch them all together at the beginning or end. That’s what everyone else does, which means that’s what bad guys are looking for. Instead, space them out throughout your password to make the guesswork extra tricky.
4. Don’t change a thing. You know how your corporate IT manager keeps making you change your password every three months? Your corporate IT manager is wrong. The less often you change your password, the less likely you are to forget it, or to fall into patterns—like just changing a number at the end each time—that make them easier to crack.
5. Single-serve only. If you’re on the password manager train, you’re already all over this. But if you can’t be bothered, at the very least make sure that you don’t reuse passwords across different accounts. If you do, a retailer breach you have no control over could end up costing your banking password. See for yourself: The website Have I Been Pwned has nearly 5 billion compromised accounts on file—if yours is one of them, there’s a chance your favorite password might already be toast.
6. Don’t trust your browser. A convenient shortcut to remembering all those passwords, or getting a paid password manager account, is letting your browser remember them for you. You’ve seen the option yourself. You probably even use it on at least one site. Don’t! The option is convenient, but the underpinning security is often undocumented, and it doesn’t require that your password actually be, you know, good. If you need a free and easy option, go with a password manager like Dashlane instead of trusting everything to Chrome.
7. Add two-factor too. Hate to say it, but these days not even a password is enough. Many of the services you use today—social networks, banks, Google, and so on—offer an added layer of protection. It can come in the form of a code sent to your phone via SMS, or if you want to step it up, through software solutions like Google Authenticator or hardware like a YubiKey. SMS should be enough for most people; just know that like many entry level security precautions, it’s not perfect.
Activist? Journalist? Politician? Consider Yourself a Target: Start by encrypting everything, sign up for Google Advanced Protection, take a tour of Tor, and deploy physical measures to increase your digital security.
Late in 2015, Gilberto Titericz, an electrical engineer at Brazil’s state oil company Petrobras, told his boss he planned to resign, after seven years maintaining sensors and other hardware in oil plants. By devoting hundreds of hours of leisure time to the obscure world of competitive data analysis, Titericz had recently become the world’s top-ranked data scientist, by one reckoning. Silicon Valley was calling. “Only when I wanted to quit did they realize they had the number-one data scientist,” he says.
Petrobras held on to its champ for a time by moving Titericz into a position that used his data skills. But since topping the rankings that October he’d received a stream of emails from recruiters around the globe, including representatives of Tesla and Google. This past February, another well-known tech company hired him, and moved his family to the Bay Area this summer. Titericz described his unlikely journey recently over colorful plates of Nigerian food at the headquarters of his new employer, Airbnb.
Titericz earned, and holds, his number-one rank on a website called Kaggle that has turned data analysis into a kind of sport, and transformed the lives of some competitors. Companies, government agencies, and researchers post datasets on the platform and invite Kaggle’s more than one million members to discern patterns and solve problems. Winners get glory, points toward Kaggle’s rankings of its top 66,000 data scientists, and sometimes cash prizes.
Alone and in small teams with fellow Kagglers, Titericz estimates he has won around $ 100,000 in contests that included predicting seizures from brainwaves for the National Institutes of Health, the price of metal tubes for Caterpillar, and rental property values for Deloitte. The TSA and real-estate site Zillow are each running competitions offering prize money in excess of $ 1 million.
Veteran Kagglers say the opportunities that flow from a good ranking are generally more bankable than the prizes. Participants say they learn new data-analysis and machine-learning skills. Plus, the best performers like the 95 “grandmasters” that top Kaggle’s rankings are highly sought talents in an occupation crucial to today’s data-centric economy. Glassdoor has declared data scientist the best job in America for the past two years, based on the thousands of vacancies, good salaries, and high job satisfaction. Companies large and small recruit from Kaggle’s fertile field of problem solvers.
In March, Google came calling and acquired Kaggle itself. It has been integrated into the company’s cloud-computing division, and begun to emphasize features that let people and companies share and test data and code outside of competitions, too. Google hopes other companies will come to Kaggle for the people, code, and data they need for new projects involving machine learning—and run them in Google’s cloud.
Kaggle grandmasters say they’re driven as much by a compulsion to learn as to win. The best take extreme lengths to do both. Marios Michailidis, a previous number one now ranked third, got the data-science bug after hearing a talk on entrepreneurship from a man who got rich analyzing trends in horseraces. To Michailidis, the money was not the most interesting part. “This ability to explore and predict the future seemed like a superpower to me,” he says. Michailidis taught himself to code, joined Kaggle, and before long was spending what he estimates was 60 hours a week on contests—in addition to a day job. “It was very enjoyable because I was learning a lot,” he says.
Michailidis has since cut back to roughly 30 hours a week, in part due to the toll on his body. Titericz says his own push to top the Kaggle rankings, made not long after the birth of his second daughter, caused some friction with his wife. “She’d get mad with me every time I touched the computer,” he says.
Entrepreneur SriSatish Ambati has made Kagglers a core strategy of his startup, H2O, which makes data-science tools for customers including eBay and Capital One. Ambati hired Michailidis and three other grandmasters after he noticed a surge in downloads when H2O’s software was used to win a Kaggle contest. Victors typically share their methods in the site’s busy forums to help others improve their technique.
H2O’s data celebrities work on the company’s products, providing both expertise and a marketing boost akin to a sports star endorsing a sneaker. “When we send a grandmaster to a customer call their entire data-science team wants to be there,” Ambati says. “Steve Jobs had a gut feel for products; grandmasters have that for data.” Jeremy Achin, cofounder of startup DataRobot, which competes with H2O and also has hired grandmasters, says high Kaggle rankings also help weed out poseurs trying to exploit the data-skills shortage. “There are many people calling themselves data scientists who are not capable of delivering actual work,” he says.
Competition between people like Ambati and Achin helps make it lucrative to earn the rank of grandmaster. Michailidis, who works for Mountain View, California-based H2O from his home in London, says his salary has tripled in three years. Before joining H2O, he worked for customer analytics company Dunnhumby, a subsidiary of supermarket Tesco.
Large companies like Kaggle champs, too. An Intel job ad posted this month seeking a machine-learning researcher lists experience winning Kaggle contests as a requirement. Yelp and Facebook have run Kaggle contests that dangle a chance to interview for a job as a prize for a good finish. The winner of Facebook’s most recent contest last summer was Tom Van de Wiele, an engineer for Eastman Chemical in Ghent, Belgium, who was seeking a career change. Six months later, he started a job at Alphabet’s artificial-intelligence research group DeepMind.
H2O is trying to bottle some of the lightning that sparks from Kaggle grandmasters. Select customers are testing a service called Driverless AI that automates some of a data scientist’s work, probing a dataset and developing models to predict trends. More than 6,000 companies and people are on the waitlist to try Driverless. Ambati says that reflects the demand for data-science skills, as information piles up faster than companies can analyze it. But no one at H2O expects Driverless to challenge Titericz or other Kaggle leaders anytime soon. For all the data-crunching power of computers, they lack the creative spark that makes a true grandmaster.
“If you work on a data problem in a company you need to talk with managers, and clients,” says Stanislav Semenov, a grandmaster and former number one in Moscow, who is now ranked second. He likes to celebrate Kaggle wins with a good steak. “Competitions are only about building the best models, it’s pure and I love it.” On Kaggle, data analysis is not just a sport, but an art.
Given these tumultuous times, there’s a real comfort in knowing that WB/DC somehow managed to get a live-action Wonder Woman movie right while hilariously flubbing Batman and Superman. We should all be immensely looking forward to the film, which is why I very recommend you don’t watch these new, completely amazing…
Traveling in a foreign country and using Google Translate or a dictionary to help you communicate with locals? Waverly Labs has developed a real-time earbud translator so you can put that dictionary down: the Pilot earpiece.