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Could SuperLocal be the local recommendation app that breaks through?

(SOCIAL MEDIA NEWS) The app combines the authentic, user-generated answers of Jelly or Quora with the local expertise of AirBnB or Couchsurfing. Could it be “the one”?

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Get better recommendations

No more searching through guide books, Googling broad terms or relying on your concierge for recommendations, says SuperLocal. The Dutch app, founded in 2016 (and set to launch any day now) aims to connect travelers directly with locals for recommendations, meetups, and/or advice while traveling.

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It’s got the goods

The app combines the authentic, user-generated answers of Jelly or Quora with the local expertise of AirBnB or Couchsurfing. With a focus just on travel recommendations, you can hope to get more knowledgeable and reliable responders. Locals on the site can also put their availability to meet with travelers for a cup of coffee or even a wild night out of drinking.

If the new app can scale as hoped, it could become a go-to for reliable recommendations while abroad from likeminded people.

It is in a tough spot though, with travelers currently going to a number of different apps for similar services.

Localeur offers a network of locals providing recommendations, as does HeyLets. You’ll also find people using apps like Tinder or even Uber to get recommendations while traveling. And of course, hotel concierges still tend to be a primary resource for travelers.

Beating the competition

The crowded space of recommendation apps was discussed in an interesting Quora post from 2011, where one user asked why “social recommendation services for local businesses” never really took off. Five years later, several of the answers still seem applicable, while none of the example services listed in the original question became household names.

The first hurdle is of course attracting users and capturing consumer attention. Some apps have tried to pay users for recommendations, others like SuperLocal hope the appeal to help a tourist in need (or connect socially) will be enough. Next, there’s the fact that not all recommenders are equal, and even though the idea of locals providing recommendations makes sense, we still sometimes like expert opinions.

In recent years, while platforms like Yelp and Facebook have continued to build their recommendation bases, other smaller networks have missed the mark.

Can SuperLocal rise?

SuperLocal is not actually a social recommendation app, but rather the travel guide, although it will still face some of the same challenges moving forward. The best part of SuperLocal is the ability to get instant recommendations and have realtime conversations with locals, although that means a huge user network will have to join the app.

One lone message left unanswered by a local could drive a traveling user to a different platform.

So, how does an app like SuperLocal find it’s way? Maybe it’s implementing rewards for locals, adding a verification feature to ensure only quality recommendations are listed, or focusing just on a few select cities at the start.

There’s a long and tough road ahead, but in a crowded space that no single app has managed to breakthrough, SuperLocal could be the one.Click To Tweet

#SuperLocal

Brian is a staff writer at The American Genius who lives in Brooklyn, New York. He is a graduate of Washington University in St. Louis, and majored in American Culture Studies and Writing. Originally from California, Brian has a podcast, "Revolves Around Me," and enjoys public transportation, bicycles, the beach.

Tech News

Career consultants help job seekers beat AI robot interviews

(TECH NEWS) With the growth of artificial intelligence conducting the job screening, consultants in South Korea have come up with an innovative response.

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When it comes to resume screenings, women and people of color are regularly passed over, even if they have the exact same resume as a man. In order to give everyone a fair try, we need a system that’s less biased. With the cool, calculating depictions of artificial intelligence in modern media, it’s tempting to say that AI could help us solve our resume screening woes. After all, nothing says unbiased like a machine…right?

Wrong.

I mean, if you need an example of what can go wrong with AI, look no further than Microsoft’s Tay, which went from making banal conversation to spouting racist and misogynistic nonsense in less than 24 hours. Not exactly the ideal.

Sure, Tay was learning from Twitter, which is a hotbed of cruelty and conflict, but the thing is, professional software isn’t always much better. Google’s software has been caught offering biased translations (assuming, for example, if you wrote “engineer” you were referring to a man) and Amazon has been called out for using job screening software that was biased against women.

And that’s just part of what could go wrong with AI scanning your resume. After all, even if gender and race are accounted for (which, again, all bets are off), you’d better bet there are other things – like specific phrases – that these machines are on the lookout for.

So, how do you stand out when it’s a machine, not a human, judging your work? Consultants in South Korea have a solution: teach people how to work around the bots. This includes anything from resume work to learning what facial expressions are ideal for filmed interviews.

It helps that many companies use the same software to do screening. Instead of trying to prepare to impress a wide variety of humans, if someone knew the right tricks for handling an AI system, they could potentially put in much less work. For example, maybe one human interviewer likes big smiles, while the other is put off by them. The AI system, on the other hand, won’t waver from company to company.

Granted, this solution isn’t foolproof either. Not every business uses the same program to scan applicants, for instance. Plus, this tech is still in its relative infancy – a program could easily be in flux as requirements are tweaked. Who knows, maybe someday we’ll actually have application software that can more accurately serve as a judge of applicant quality.

In the meantime, there’s always AI interview classes.

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Google chrome: The anti-cookie monster in 2022

(TECH NEWS) If you are tired of third party cookies trying to grab every bit of data about you, google has heard and responded with their new updates.

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Google has announced the end of third-party tracking cookies on its Chrome browser within the next two years in an effort to grant users better means of security and privacy. With third-party cookies having been relied upon by advertising and social media networks, this move will undoubtedly have ramifications on the digital ad sector.

Google’s announcement was made in a blog post by Chrome engineering director, Justin Schuh. This follows Google’s Privacy Sandbox launch back in August, an initiative meant to brainstorm ideas concerning behavioral advertising online without using third-party cookies.

Chrome is currently the most popular browser, comprising of 64% of the global browser market. Additionally, Google has staked out its role as the world’s largest online ad company with countless partners and intermediaries. This change and any others made by Google will affect this army of partnerships.

This comes in the wake of rising popularity for anti-tracking features on web browsers across the board. Safari and Firefox have both launched updates (Intelligent Tracking Prevention for Safari and the Enhanced Tracking Prevention for Firefox) with Microsoft having recently released the new Edge browser which automatically utilizes tracking prevention. These changes have rocked share prices for ad tech companies since last year.

The two-year grace period before Chrome goes cookie-less has given the ad and media industries time to absorb the shock and develop plans of action. The transition has soften the blow, demonstrating Google’s willingness to keep positive working relations with ad partnerships. Although users can look forward to better privacy protection and choice over how their data is used, Google has made it clear it’s trying to keep balance in the web ecosystems which will likely mean compromises for everyone involved.

Chrome’s SameSite cookie update will launch in February, requiring publishers and ad tech vendors to label third-party cookies that can be used elsewhere on the web.

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Tech News

Computer vision helps AI create a recipe from just a photo

(TECH NEWS) It’s so hard to find the right recipe for that beautiful meal you saw on tv or online. Well computer vision helps AI recreate it from a picture!

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Ever seen at a photo of a delicious looking meal on Instagram and wondered how the heck to make that? Now there’s an AI for that, kind of.

Facebook’s AI research lab has been developing a system that can analyze a photo of food and then create a recipe. So, is Facebook trying to take on all the food bloggers of the world now too?

Well, not exactly, the AI is part of an ongoing effort to teach AI how to see and then understand the visual world. Food is just a fun and challenging training exercise. They have been referring to it as “inverse cooking.”

According to Facebook, “The “inverse cooking” system uses computer vision, technology that extracts information from digital images and videos to give computers a high level of understanding of the visual world,”

The concept of computer vision isn’t new. Computer vision is the guiding force behind mobile apps that can identify something just by snapping a picture. If you’ve ever taken a photo of your credit card on an app instead of typing out all the numbers, then you’ve seen computer vision in action.

Facebook researchers insist that this is no ordinary computer vision because their system uses two networks to arrive at the solution, therefore increasing accuracy. According to Facebook research scientist Michal Drozdzal, the system works by dividing the problem into two parts. A neutral network works to identify ingredients that are visible in the image, while the second network pulls a recipe from a kind of database.

These two networks have been the key to researcher’s success with more complicated dishes where you can’t necessarily see every ingredient. Of course, the tech team hasn’t stepped foot in the kitchen yet, so the jury is still out.

This sounds neat and all, but why should you care if the computer is learning how to cook?

Research projects like this one carry AI technology a long way. As the AI gets smarter and expands its limits, researchers are able to conceptualize new ways to put the technology to use in our everyday lives. For now, AI like this is saving you the trouble of typing out your entire credit card number, but someday it could analyze images on a much grander scale.

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