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Huawei Announces $54 billion revenue and 23% increase for first half of 2019

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Huawei announced its business results for the first half of 2019:  USD $58.34 billion in revenue, a 23.2% increase over the same period last year. The company’s net profit margin for H1 2019 was 8.7%.

According to Huawei’s Chairman, Liang Hua, operations are smooth and the organization is as sound as ever. With effective management and an excellent performance across all financial indicators, Huawei’s business has remained robust in the first half of 2019.

 

In Huawei’s carrier business, H1 sales revenue reached USD $21.29 billion, with steady growth in production and shipment of equipment for wireless networks, optical transmission, data communications, IT, and related product domains. To date, Huawei has secured 50 commercial 5G contracts and has shipped more than 150,000 base stations to markets around the world.

In Huawei’s enterprise business, H1 sales revenue was USD $4.59 billion. Huawei continues to enhance its ICT portfolio across multiple domains, including cloud, artificial intelligence, campus networks, data centers, Internet of Things, and intelligent computing. It remains a trusted supplier for government and utility customers, as well as customers in commercial sectors like finance, transportation, energy, and automobile.

 

In Huawei’s consumer business, H1 sales revenue hit USD $32.1 billion. Huawei’s smartphone shipments (including Honor phones) reached 118 million units, up 24% YoY. The company also saw rapid growth in its shipments of tablets, PCs, and wearables. Huawei is beginning to scale its device ecosystem to deliver a more seamless intelligent experience across all major user scenarios. To date, the Huawei Mobile Services ecosystem has more than 800,000 registered developers, and 500 million users worldwide.

 

“Revenue grew fast up through May,” said Liang. “Given the foundation we laid in the first half of the year, we continue to see growth even after we were added to the entity list. That’s not to say we don’t have difficulties ahead. We do, and they may affect the pace of our growth in the short term.”

 

He added, “But we will stay the course. We are fully confident in what the future holds, and we will continue investing as planned – including a total of USD $17.44 billion in R&D this year. We’ll get through these challenges, and we’re confident that Huawei will enter a new stage of growth after the worst of this is behind us.”

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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.

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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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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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