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The role of Stablecoins in Africa’s Crypto Market

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For many new and seasoned cryptocurrency investors, it is important to note that the ecosystem is characterized by bulls and bears – trending upwards or downwards depending on several market factors such as public hype, supply, demand, and investor sentiments, among others. Therefore, to sustain the community of users who aim to build wealth and enjoy the freedom of money through investments in cryptocurrency, niche digital currencies have been developed by exchange platforms to hedge against such volatility, known as Stablecoins.

Stablecoins play a vital role in the crypto economy by introducing more liquidity into the ecosystem, allowing more digital asset trading on cryptocurrency exchanges. The different types of stablecoins are pegged based on their underlying collateral structure: fiat-backed, commodity-backed, crypto-backed, or algorithmic. For instance, on Binance, the  Binance USD (BUSD), USD Tether (USDT), and USD Coin (USDC) are secured to the US dollar on a 1:1 basis, which means that the value of one BUSD for instance, is the same as one US dollar. As its name implies, its purpose is to provide price stability and serve as an alternative to the volatility of other cryptocurrencies, limiting their use cases for possible transactions.

For new investors and expert traders, the certainty of stablecoins makes them a good asset to invest in and hold on to, especially during bear markets. In the same way that traditional investors might choose to keep portions of their assets in low-risk instruments like treasury bonds or mutual funds, crypto investors also have the option of utilizing stablecoins; this provides a long-term store of value for players in the crypto space, especially when the market takes a prolonged downward turn.

For instance, Binance USD (BUSD), a U.S dollar-backed stable coin approved by the New York State Department of Financial Services (NYSDF) is one of the most trusted stablecoins available in the ecosystem. It has continued to maintain its position because it is backed and regulated by reserves contingent on regular attestation. With BUSD, investors are protected by a regulatory body that has painstakingly assessed the underlying foundation of the asset offered to new and experienced investors. In other words, investors can rely on coins like BUSD as low-risk instruments because of the strength of the regulation that goes into establishing the fiat-back reserve of each stablecoin.

Another key benefit of having a regulated stablecoin is that much like in the traditional market where investors can earn a fixed interest from a variety of investment products, crypto investors can also earn interest with stablecoins through lending. Investors can earn at a set interest rate from borrowers when they lend out their stablecoins. Also, a user can earn interest with stablecoins through staking, which involves holding funds in a cryptocurrency wallet to support the security and operations of a blockchain network for which they receive rewards.

A crucial role stablecoins have been able to play, due to their highly predictable stability, is the building out of some of the more recent applications in the crypto space, namely non-fungible tokens (NFTs) and decentralized finance (DeFi). Stablecoins have enabled investors to generate returns on their crypto assets in the DeFi market while alleviating the potential adverse effects of market volatility. Dollar-backed stablecoins like Binance USD (BUSD) are one of the preferred currencies of NFT marketplaces and storefronts. These digital currencies offer a convenient funding source for NFT enthusiasts. Thus, stablecoins are creating the foundations for blockchain and crypto applications.

As more people in Africa aim to take control of their finances and achieve financial freedom, stablecoins will remain a suitable alternative to fiat currencies, serving as an essential part of the crypto ecosystem. In addition, even though stablecoins are currently considered a niche crypto asset, they are well on their way to becoming a store of value and means of payment outside the crypto ecosystem. This is because to function effectively as a currency alternative, cryptocurrencies need to possess certain qualities such as liquidity, relatively low-price volatility, and the ability to be integrated with established financial institutions; all qualities the stablecoins currently possess.

Future regulation and compliance coupled with the collaboration with other fintech companies focusing on digital payments could potentially make stablecoins an option for retail payments as well as cross-border payments and remittances.

Interested in purchasing and investing in stablecoins? Get started today by downloading the Binance app hereand trade from anywhere in the world. There are different options available for buying cryptocurrencies at Binance; through a fiat deposit or by using a Binance P2P.

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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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