Tom McDonnell (CEO of monterosalondon, TV & Sports fan interaction specialists), who calls Accra his second home, shares some interesting insights into the city of Accra from nightlife to art, music, football, food, transportation, eduction and more.
In the feature, he also points out 13 things Accra needs to address to win at tech. They include:
- Fast, Cheap, Easy company registration. It is frankly ridiculous that setting up a company takes more than a few hours. Ghana must compete with the best countries for efficiency and make it possible to register a company within a day, ideally for free and done online. This has the added benefit of providing quantified data and tax receipts. Many people simply can’t be bothered and trade informally, reducing tax revenues.
- Fast visas on arrival, and fast visas for talented employees. Not having visa on arrival might be a “tit for tat” measure against western countries, but it’s hindering freedom of doing business. Any tech business who can prove they’re struggling to hire locally should have the right to bring people in when needed.
- Faster, more reliable internet. The fibre capacity is not bad but it needs to be much much better. I understand that various companies including Google, Facebook and Vodafone are all working on this, but it needs to happen fast.
- Reliable power. What a topic for Ghanaians. Dumsor (“On and off”) is the name of chronic electricity outages over the last few years and a major contributor to the downfall of the previous government. Ghana has a lot of gas (burned off at sea), and even more sunshine. Surely Ghana should be solar powered, not relying on coal ships. This needs to be fixed, now, or nobody in their right mind will setup a new business in Accra. Could someone call Elon Musk? There’s a deal to be done.
- More software engineering training facilities and education. Learning to code is not about doing a degree, it’s not about pieces of paper, it’s about actually learning to code. Those of us who code mostly learned from a very young age. My aunty taught me BASIC when I was 8.
- World-class healthcare facilities. Healthcare in Ghana is generally terrible. God forbid you have an accident and need treatment after dark, or have a serious condition and don’t get lucky. We’ve all lost close friends and family due to poor healthcare and the time has come to shake things up. Ghana needs to radically improve its state hospitals, improve the national heath insurance scheme, and to setup a mini version of Dubai’s Healthcare city for private healthcare to attract international staff and returning Ghanaians. Why would I come back home to Ghana with my young family if I can’t trust they will be well looked after? This is key.
- A “returnees” package. China has this locked down — if you’re a highly qualified, talented Chinese scientist or tech person and want to go back and start a business in one of their tech zones, they will make it worth your while. Ghana created some of the smartest minds, but many left Ghana long ago. As I said before, most Ghanaians would love to come home. My uncle is a top US government advisor on silicon chips — he lives in DC and Ghana needs him back. Getting him back means incentives, great housing, healthcare and of course, a well paid rewarding job.
- Modern, fun working environments. There is no reason why Ghana cannot have dynamic, beautiful technology parks like those in Silicon Valley, London, Berlin or Dubai. In fact, Ghana should aim to do them better.
- Leisure and sports facilities. Innovation can be mentally energetic but quite physically static. Providing top class sports and leisure facilities: tennis courts, football pitches and gyms is crucial to attracting the best talent.
- Safe food. Food tastes great in Ghana, but food preparation standards are patchy. They must be enforced so that visiting clients, staff or others can enjoy themselves without the worry.
- Tax incentives. While Ireland’s strategy of offering low corporation tax to American IT companies is flawed, it does attract big businesses and create jobs. Exchanging significant tax reductions for investment in innovation and local training could make a tremendous social and economic impact and speed up relocation or establishing innovation centres. Ultimately it will lead to greater tax receipts, it should be a no-lose situation.
- Access to public and private sector piloting. For new businesses, having real-world reference customers is critical. Through a combination of formal and informal introductions, schemes and workshops, pairing new ideas with businesses and public institutions (e.g. hospitals, tax offices), that need them, can help those that are destined to fail, fail faster; and those that can succeed, succeed quicker. Ultimately Ghana should stop hiring big American or UK businesses to deploy government systems, and hire local. More employment, more knowledge, more taxes, more people to learn and start businesses.
- Access to both capital, and companies to acquire! Informal investment from private “angels” is relatively common already, but seed and growth capital is hard to come by. The UK’s “EIS” scheme allow wealthy individuals to invest their cash with the ability to write-off losses and pay lower rates on gains. Along with R&D tax credits, effectively government hand-outs to companies that invest in building IP, it has significantly stimulated investment in UK businesses. There should be a version of this for Ghana to attract local and foreign high net worth individuals. But to invest in a business, funds want to see an exit; that means stimulating an eco-system of businesses that are ready to buy. So while enticing capital is important, so is enticing the big businesses that can afford to acquire tech companies that they can utilise or scale up globally.
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Meta’s AI AI machine translation research helps break language barriers
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.
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