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3 Things Every Online Video Creator Can Learn From BuzzFeed

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BuzzFeed is home to many of the viral stories and trending topics that take social media by storm. Over on YouTube, BuzzFeed often dominates the trending page. It’s hard to go on YouTube without having at least one BuzzFeed video in your recommendations.

Here’s what every video creator can learn from BuzzFeed.

Series maximize on the viral success of a great idea.

Whenever you see a BuzzFeed video on the trending page, it’s often similar to one you’ve seen before. This is because BuzzFeed turns its viral hits into popular video series. These series are divided into seasons and episodes as if they were airing on television.

One of BuzzFeed’s most popular video series is “Worth It.” This is the series that started the “cheap vs. expensive” video trend. The series has found so much success that the team behind it has been able to film across the world.

Amazing videos are the product of an amazing team.

BuzzFeed wouldn’t have such successful videos without the extremely talented team behind them. A viral BuzzFeed video isn’t likely to be solely the product of the onscreen talent. These videos are a collaboration between writers, editors, producers, and crew.

BuzzFeed is a great place for creatives to grow before launching their own independent careers. For example, before launching their incredibly successful channel, the Try Guys were a part of BuzzFeed. Now, they have a team of their own to support their ambitious content creation.

Concentrating in a niche can help grow your audience exponentially.

While BuzzFeed’s main channel videos experience a lot of success, their secondary channels have become so successful that entire fanbases have sprung up around them. Most notably, BuzzFeed Unsolved and BuzzFeed Multiplayer have become fan favorites.

Most of BuzzFeed’s secondary channels were created specifically to house series that became popular on the main channel. For example, “Ladylike” was on a different BuzzFeed channel before its success earned the show a channel of its own.

BuzzFeed consistently produces viral videos by allowing its team members to focus on specific series. By focusing on series with proven track records for success, BuzzFeed reaches millions of viewers across its multiple channels every week.

Interested in getting your YouTube video discovered by masses of targeted fans? Click this link: www.promolta.com

About the author:

Kristen Harris enjoys listening to a wide range of music, from Taylor Swift to, on occasion, Celtic instrumental. She also spends her time writing, reading, and baking.

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How to Be More Confident on Camera as a Youtuber

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CONFIDENCE is very important. The more confident you appear, the more viewers will listen to you. (more…)

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Graduate who went viral for begging for a job with a placard says he’s received 50 offers since

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Isaac Kwame Addae, a young unemployed graduate who took to the streets with a placard, looking for a job, says he  has been offered opportunities by at least  50 different firms. (more…)

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Meta’s AI AI machine translation research helps break language barriers

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Today, Meta announced that it has built and open sourced ‘No Language Left Behind’ NLLB-200, a single AI model that is the first to translate across 200 different languages, including 55 African languages with state-of-the-art results. Meta is using the modelling techniques and learnings from the project to improve and extend translations on Facebook, Instagram, and Wikipedia.

 

In an effort to develop high-quality machine translation capabilities for most of the world’s low-resource languages, this single AI model was designed with a focus on African languages. They are challenging from a machine translation perspective. AI models require lots and lots of data to help them learn, and there’s not a lot of human translated training data for these languages. For example, there’s more than 20M people who speak and write in Luganda but examples of this written language are extremely difficult to find on the internet.

 

We worked with professional translators for each of these languages to develop a reliable benchmark which can automatically assess translation quality for many low-resource languages. We also work with professional translators to do human evaluation too, meaning people who speak the languages natively evaluate what the AI produced. The reality is that a handful of languages dominate the web, so only a fraction of the world can access content and contribute to the web in their own language. We want to change this by creating more inclusive machine translations systems – ones that unlock access to the web for the more than 4B people around the world that are currently excluded because they do not speak one of the few languages content is available in.

Read Also: Impressive! Ghanaian Rapper Dr. Pushkin Releases New App & Book ahead of “Outlandish” Album

“It’s impressive how much AI is improving all of our services. We just open-sourced an AI model we built that can translate across 200 different languages — many of which aren’t supported by current translation systems. We call this project No Language Left Behind, and the AI modelling techniques we used are helping make high quality translations for languages spoken by billions of people around the world. To give a sense of the scale, the 200-language model has over 50 billion parameters, and we trained it using our new Research SuperCluster, which is one of the world’s fastest AI supercomputers. The advances here will enable more than 25 billion translations every day across our apps. Communicating across languages is one superpower that AI provides, but as we keep advancing our AI work it’s improving everything we do — from showing the most interesting content on Facebook and Instagram, to recommending more relevant ads, to keeping our services safe for everyone,” said Meta CEO Mark Zuckerberg in a post on his Facebook profile.

 

Language is our culture, identity, and lifeline to the world. However, as high-quality translation tools don’t exist for hundreds of languages, billions of people today can’t access digital content or participate fully in conversations and communities online in their preferred or native languages. This is especially true for hundreds of millions of people who speak the many languages of Africa.

 

“Africa is a continent with very high linguistic diversity, and language barriers exist day to day. We are pleased to announce that 55 African languages will be included in this machine translation research, making it a major breakthrough for our continent,” Balkissa Ide Siddo, Public Policy Director for Africa said while speaking about the launch of the AI model. “In the future, imagine visiting your favourite Facebook group, coming across a post in Igbo or Luganda, and being able to understand it in your own language with just a click of a button – that’s where we hope research like this leads us. Highly accurate translations in more languages could also help to spot harmful content and misinformation, protect election integrity, and curb instances of online sexual exploitation and human trafficking.”

 

While commenting on accessibility and inclusion in the pursuit of building an equitable metaverse, Ide Siddo added “At Meta, we are working today to ensure that as many people as possible will be able to access the new educational, social and economic opportunities that the next evolution of the internet will bring to future technology and an everyday living experience tomorrow.”

 

To confirm that the translations are high quality, Meta also created a new evaluation dataset, FLORES-200, and measured NLLB-200’s performance in each language. Results revealed that NLLB-200 exceeds the previous state of the art by an average of 44 percent.

 

Meta is also open-sourcing the NLLB-200 model and publishing a slew of research tools to enable other researchers to extend this work to more languages and build more inclusive technologies. Meta AI is also providing up to $200,000 of grants to non-profit organizations for real world applications for NLLB-200.

 

There are versions of Wikipedia in more than 300 languages, but most have far fewer articles than the 6+ million available in English. Following Meta’s partnership with the Wikimedia Foundation, the non-profit organization that hosts Wikipedia and other free knowledge projects, modelling  techniques and learnings from the NLLB research are now also being applied to translation systems used by Wikipedia editors. Using the Wikimedia Foundation’s Content Translation Tool, articles can now be easily translated in more than 20 low-resource languages (those that don’t have extensive datasets to train AI systems), including 10 that previously were not supported by any machine translation tools on the platform.

 

To explore a demo of NLLB-200 showing how the model can translate stories from around the world, visit here. You can also read the research paper here.

 

 

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I single-handedly popularized Shea Butter in the United States – Margaret Andega

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According to Margaret Andega, a Kenyan entrepreneur in Atlanta, she was the driving force behind the commercialization of Shea Butter in the US during the late 90s. (more…)

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Ludwig Nii Jr urges information sharing in the creative space

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Ludwig Nii Jr urges information sharing in the creative space. (more…)

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How are CBD Flowers and CBG Flowers Different?

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CBG flower and CBD flower are two types of flowers that are used for their respective health benefits. CBD flowers are known for their calming and relaxing effects, while CBG flowers are known for relieving pain and inflammation.  (more…)

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