When it comes down to it, the Internet is all about memes and people constantly getting mad about one thing or another. I’m usually playing on the side of memes, but I joined the other group when I stumbled upon a CB list of the 25 Most Absurd Titles in Tech.
Absurd doesn’t even begin to cut it.
This list is a perpetual head-shaker and there’s clearly some stuff going on in the world of tech that needs to get a reality check.
All 25 of these titles are terrible, but I challenged myself to narrow it down to the 10 worst. Let’s work our way backwards.
10. Full Stack Magician – First of all, a small typo in the second word could really change your profession. Second of all, my concept of a Full Stack Magician is the guy walking around Denny’s playing card tricks for a few extra bucks on a Saturday night. How in the world am I supposed to know that “magician” is shorthand for “engineer”? Two very different things, friends.
9. Humbly Confident Product Designer – I don’t know about you, but humble and confident are often times two traits that don’t sit at the same table, let alone work together to describe a job title. As you might guess, it’s someone in product design who is self-assured. And humble about it. To me, this is something that should be determined in an interview personality test and a reason behind why one gets the job of product designer. It should just be included without having to be part of your LinkedIn title.
8. Chief Heart Officer – What comes to mind here is Dr. Webber on Grey’s Anatomy. This title was developed for Claude Silver of VaynerMedia in 2014. “Being Chief Heart Officer means being in touch with the heartbeat of every single person at this agency,” she later wrote. A nice concept, but, come on.
7. Galactic Viceroy of Research Excellence – This one, developed by Microsoft (really, y’all?), has Star Trek written all over it. Apparently it was developed for Microsoft’s researcher, James Mickens, due to his personality. Should your personality really influence your job title? This Staff Writer votes “nope.”
6. Meme Librarian – I put this on here because I’m both jealous and confused. Getting paid to archive memes? Sign me up! But, also, what the hell? According to CB, this title was invented at Tumblr to describe the role occupied by Amanda Brennan, who researches fandoms and trends. The Tumblr team uses the data collected by Brennan’s team to better understand the unique communities, languages, and relationships that emerge on the platform.
5. Remote Funnel Marketing Ninja – Am I supposed to be going to work with this title or mastering a game on Super Nintendo? Responsibilities apparently include “architect[ing] funnels based on customer goals” and “creat[ing] & connect[ing] ActiveCampaign lists to Gravity Forms in landing pages.” Neat job description, but the job title is trying too hard.
4. Tax Wrangler – This is funny to me because I’m picturing getting audited by John Wayne. What it actually means, according to Automattic is, the in-house tax wrangler is in charge of “researching multi-state sales and use tax regulations” and working on “sales, property, excise and VAT taxes” for a company of 600+ people. Ok, sure.
3. Security Princess – Okay, but do I get to wear a beautiful gown and crown? Why the gendering of a role!? This title was designated to Parisa Tabriz at Google where she was formerly a security engineer. Her job was to find holes in the Chrome browser. I’m confused where Cinderella comes into play, but, whatever.
2. Weekend Happiness Concierge – In my travels, this title belongs to whoever owns the couch I’m crashing on any given weekend (I kid). This is simply a customer support agent, with concierge derived from the powerful role in 18th century European courts. To me, it just sounds like someone who brings you an extra pillow at a hotel.
1. SVG Badass – It was hard to pick number one, but I had to go with this. You mean to tell me that you’re going to walk into a networking event filled with other professionals and hand out business cards that say “badass”? In tech events, that will fly, but not outside of that bubble. Change the ‘bad’ to ‘dumb’ and we’ll be on the same page.
In order of #1-25, the original list consisted of: Innovation Evangelist, Dream Alchemist, Weekend Happiness Concierge, Happiness Engineer, SVG Badass, Time Ninja, Innovation Alchemist, Security Princess, Retail Jedi, Software Ninjaneer, Tax Wrangler, Remote Funnel Marketing Ninja, Content Hero, Meme Librarian, Happiness Manager, Conversion Optimization Wrangler, Galactic Viceroy of Research Excellence, Innovation Sherpa, Digital Prophet, Chief Heart Officer, Brand Warrior, Wizard of Light Bulb Moments, Direct-Mail Demigod, Full Stack Magician, Humbly Confident Product Designer.
4 ways startups prove their investment in upcoming technology trends
(TECH NEWS) Want to see into the future? Just take a look at what technology the tech field is exploring and investing in today — that’s the stuff that will make up the world of tomorrow.
Big companies scout like for small ones that have proven ideas and prototypes, rather than take the initial risk on themselves. So startups have to stay ahead of technology by their very nature, in order to be stand-out candidates when selling their ideas to investors.
Innovation Leader, in partnership with KPMG LLP, recently conducted a study that sheds light onto the bleeding edge of tech: The technologies that the biggest companies are most interested in building right now.
The study asked its respondents to group 16 technologies into four categorical buckets, which Innovation Leader CEO Scott Kirsner refers to as “commitment level.”
The highest commitment level, “in-market or accelerating investment,” basically means that technology is already mainstream. For optimum tech-clairvoyance, keep your eyes on the technologies which land in the middle of the ranking.
“Investing or piloting” represents the second-highest commitment level – that means they have offerings that are approaching market-readiness.
The standout in this category is Advanced Analytics. That’s a pretty vague title, but it generally refers to the automated interpretation and prediction on data sets, and has overlap with Machine learning.
Wearables, on the other hand, are self explanatory. From smart watches to location trackers for children, these devices often pick up on input from the body, such heart rate.
The “Internet of Things” is finding new and improved ways to embed sensor and network capabilities into objects within the home, the workplace, and the world at large. (Hopefully that doesn’t mean anyone’s out there trying to reinvent Juicero, though.)
Collaboration tools and cloud computing also land on this list. That’s no shock, given the continuous pandemic.
The next tier is “learning and exploring”— that represents lower commitment, but a high level of curiosity. These technologies will take a longer time to become common, but only because they have an abundance of unexplored potential.
Blockchain was the highest ranked under this category. Not surprising, considering it’s the OG of making people go “wait, what?”
Augmented & virtual reality has been hyped up particularly hard recently and is in high demand (again, due to the pandemic forcing us to seek new ways to interact without human contact.)
And notably, AI & machine learning appears on rankings for both second and third commitment levels, indicating it’s possibly in transition between these categories.
The lowest level is “not exploring or investing,” which represents little to no interest.
Quantum computing is the standout selection for this category of technology. But there’s reason to believe that it, too, is just waiting for the right breakthroughs to happen.
Internet of Things and deep learning: How your devices are getting smarter
(TECH NEWS) The latest neural network from Massachusetts Institute of Technology shows a great bound forward for deep learning and the “Internet of Things.”
The deep learning that modifies your social media and gives you Google search results is coming to your thermostat.
Researchers at the Massachusetts Institute of Technology (MIT) have developed a deep learning system of neural networks that can be used in the “Internet of Things” (IoT). Named MCUNet, the system designs small neural networks that allow for previously unseen speed and accuracy for deep learning on IoT devices. Benefits of the system include energy savings and improved data security for devices.
Created in the early 1980s, the IoT is essentially a large group of everyday household objects that have become increasingly connected through the internet. They include smart fridges, wearable heart monitors, thermostats, and other “smart” devices. These gadgets run on microcontrollers, or computer chips with no processing system, that have very little processing power and memory. This has traditionally made it hard for deep learning to occur on IoT devices.
“How do we deploy neural nets directly on these tiny devices? It’s a new research area that’s getting very hot,” said Song Han, Assistant Professor of Computer Science at MIT who is a part of the project, “Companies like Google and ARM are all working in this direction.”
In order to achieve deep learning for IoT connected machines, Han’s group designed two specific components. The first is TinyEngine, an inference engine that directs resource management similar to an operating system would. The other is Tiny NAS, a neural architecture search algorithm. For those not well-versed in such technical terms, think of these things like a mini Windows 10 and machine learning for that smart fridge you own.
The results of these new components are promising. According to Han, MCUNet could become the new industry standard, stating that “It has huge potential.” He envisions the system has one that could help smartwatches not just monitor heartbeat and blood pressure but help analyze and explain to users what that means. It could also lead to making IoT devices far more secure than they are currently.
“A key advantage is preserving privacy,” says Han. “You don’t need to transmit the data to the cloud.”
It will still be a while until we see smart devices with deep learning capabilities, but it is all but inevitable at this point—the future we’ve all heard about is definitely on the horizon.
Google is giving back some privacy control? (You read that right)
(TECH NEWS) In a bizarre twist, Google is giving you the option to opt out of data collection – for real this time.
It’s strange to hear “Google” and “privacy” in the same sentence without “concerns” following along, yet here we are. In a twist that’s definitely not related to various controversies involving the tech company, Google is giving back some control over data sharing—even if it isn’t much.
Starting soon, you will be able to opt out of Google’s data-reliant “smart” features (Smart Compose and Smart Reply) across the G-Suite of pertinent products: Gmail, Chat, and Meet. Opting out would, in this case, prevent Google from using your data to formulate responses based on your previous activity; it would also turn off the “smart” features.
One might observe that users have had the option to turn off “smart” features before, but doing so didn’t disable Google’s data collection—just the features themselves. For Google to include the option to opt out of data collection completely is relatively unprecedented—and perhaps exactly what people have been clamoring for on the heels of recent lawsuits against the tech giant.
In addition to being able to close off “smart” features, Google will also allow you to opt out of data collection for things like the Google Assistant, Google Maps, and other Google-related services that lean into your Gmail Inbox, Meet, and Chat activity. Since Google knowing what your favorite restaurant is or when to recommend tickets to you can be unnerving, this is a welcome change of pace.
Keep in mind that opting out of data collection for “smart” features will automatically disable other “smart” options from Google, including those Assistant reminders and customized Maps. At the time of this writing, Google has made it clear that you can’t opt out of one and keep the other—while you can go back and toggle on data collection again, you won’t be able to use these features without Google analyzing your Meet, Chat, and Gmail contents and behavior.
It will be interesting to see what the short-term ramifications of this decision are. If Google stops collecting data for a small period of time at your request and then you turn back on the “smart” features that use said data, will the predictive text and suggestions suffer? Only time will tell. For now, keep an eye out for this updated privacy option—it should be rolling out in the next few weeks.
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