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Taxify Partners with Vivo Energy to Reduce the Cost of Doing Business for Drivers in Ghana

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IMG 2489International ride hailing app, Taxify, in partnership with Vivo Energy Ghana, the marketers and distributors of Shell branded products and services in Ghana, has introduced its latest initiative to reduce the cost of drivers doing business on their platform in Accra, Ghana.

The tech company, which takes only 15% in driver commissions, has initiated a partnership that will offer eligible Taxify drivers minimum savings of 3 pesewas per litre when filling up using the Ezypass fuel card at Shell service stations, starting this month.

Under the partnership, Taxify drivers who achieve set targets will be rewarded with Vivo Energy’s Ezypass Visa-enabled fuel card, which can be used across the over103 Shell service stations nationwide. Taxify has also said that up to 400 eligible drivers each week would have access to fuel vouchers worth 70GHC.

According to Taxify’s City Manager, Nonso Onwuzulike, the rising cost of fuel is one of the key challenges that drivers face and the partnership will enable drivers to cut-down on their fuel spend and reduce their cost of being in business.

“One of the biggest costs for our drivers in Accra is the cost of fuel. Our focus as a company has always been to provide bespoke business solutions that reduces their cost of doing business on our platform. It is in fulfillment of this commitment that we have partnered with Vivo Energy Ghana to ensure that our drivers are able to make some cost savings where it truly matters to them”, he said.

“The ripple effects of this is more money to cater for their families and the people they love and a better, more reliable service to the people of Accra. We’ve seen that the happier drivers are, the better the experience they provide to their passengers,” Onwuzulike added.

The Marketing Manager of Vivo Energy Ghana, Jerry Boachie Danquah, said the partnership with Taxify fulfills Vivo Energy’s commitment of providing more convenient and cost effective solutions for commercial customers, providing them with longer lasting Shell FuelSave fuels,improving efficiency, and getting them a little further on each tank.

A client of Taxify Ghana, Kwesi Twum, commended Taxify for the initiative, which he believes will go a long way to help drivers on the platform reduce their high cost of operation and enable them to make extra savings on their fuel cost to cater to other socio-economic needs.

 

Taxify is the leading European ride-hailing platform, connecting millions of passengers and drivers around the world to make travel easier, quicker and more reliable. Taxify’s efficient and tech-enabled business model benefits both drivers who have to pay a smaller commission as well as passengers who end up paying less for their ride.

Founded by Markus Villig, Taxify launched in 2013. It’s one of the fastest-growing ride-hailing platform in Europe and Africa with investors including Daimler, Didi Chuxing and Korelya Capital.

Taxify has more than 15 million users in over 25 countries and 60 cities globally. www.taxify.eu

 

 

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How to Be More Confident on Camera as a Youtuber

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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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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.

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“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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Ludwig Nii Jr urges information sharing in the creative space

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