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Why building apps without knowing how to code is increasingly common

(TECH NEWS) No-code app building tools are becoming more available to the everyday user, which could lead to more inventive, and original apps.

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“Learn to code” is a common, frustrating refrain often hurled at job-seekers, entrepreneurs, creative professionals, and others. Depending on who’s saying it, the intent could range from well-meaning to willfully hurtful.

It does, in a way, make sense. Computer programming is the foundational language that modern life is built on. And while many people use technology that they don’t understand every day—from microwaves to cars—there’s something a little different about programming. It’s omnipresent for just about anyone, just about everywhere, whether they use it for work or not. And more people use it for work than ever. It’s the single most sought-after skill in the job market.

But “learn to code” isn’t practical for everyone. Not everyone with an app idea has the time to learn how to build an app from scratch, or the money to hire people to do it for them. That’s where the low-code/no-code movement comes in. It’s all about giving the people the tools they need to execute on an idea without having to learn an entire new skill set. When you bake a cake, you probably don’t grind wheat into flour, and when you build an app, you don’t have to start with Python.

No-code isn’t really a new idea.

The fact that computers have menus and icons is the result of early programmers realizing that non-programmers would have to use a computer sometimes. You could look to tools like RPG Maker that let people build their own video games back in 1992. RPG Maker was like a Lego kit for making a video game. And not only is it still going strong, it proved itself prophetic. It turns out that giving people tools and a sand box is a great way to enable creativity.

This has been the long arc of the Internet, too. There was a time when participating in the World Wide Web in a meaningful way meant learning to program. Places like Geocities gave you real estate to set up a website. But you had to build that site yourself. We’ve moved away from that as the Internet commodified. Sites like Facebook and Twitter remove customization in the name of uniformity.

But creative tools persist. Consider “WYSIWYG,” or “What You See Is What You Get” web editors. These are tools like WordPress that reclaimed some of that Internet customization. They give you assets to build a website, and you plug them in where you want.

It’s a middle ground between building from scratch, and having everything handed to you. It’s the sweet spot of accessible creativity. (If you’ve never heard anyone say “WYSIWYG,” that’s probably because these web development tools are so common that they don’t really need a special name anymore.)

Right now, one of the biggest areas of no-code design is in app development. These app dev tools are similar to building a WordPress site. They give you the raw materials, and you customize and assemble them however you want to. Adalo, a no-code platform for building apps, lets your bring assets and ideas to the table, and gives you a framework to organize those ideas into an app.

They aren’t alone. AppOnboard, a no-code software development suite, recently purchased Buildbox, a leading no-code game development platform. Their combined resources represent a stunning library of assets, full of potential.

What does this mean for coders? Probably not much. Specialized skills are still in high demand. But for the rest of us, a slow democratization of development is taking place, and it’s exciting to watch it take shape.

Staff Writer, Garrett Steele is your friend. He writes lyrics, critique, and copy for ads, schools, health organizations, and more. He’s also a composer for film and video games, when he’s lucky. (One of his songs is an Xbox achievement!)

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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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