you stay in Wonderland, and I show you how deep the rabbit hole goes." It is implied that the blue pill is a sedative that would cause Neo to think that all his most recent experiences were a hallucination, so that he can go back to living in the Matrix's simulated reality. the story ends, you wake up in your bed and believe whatever you want to believe. In the film The Matrix, the main character Neo (played by Keanu Reeves) is offered the choice between a red pill and a blue pill by rebel leader Morpheus (played by Laurence Fishburne).
The terms originate from the 1999 film The Matrix. The red pill and blue pill represent a choice between the willingness to learn a potentially unsettling or life-changing truth by taking the red pill or remaining in the contented experience of ordinary reality with the blue pill. Red and blue capsule pills, like the ones shown in The Matrix (1999) For other uses, see Red pill (disambiguation). And you don’t have to have a one-player-takes-it-all mentality."Red pill" redirects here. We don’t have to repeat what Silicon Valley does for our languages. We’re actually meeting every other week with other language technology startups, discussing how we can come together and solve this problem our own way. I absolutely belong to a tribe, or whatever we want to call it - a kind of pan-African AI movement. Do you have kinship with other developers and companies that are working on making products in low-resource languages? So it makes it even more urgent to create language-specific technologies. Most of the data that powers them is basically internet data, and there is not enough data online for these languages. Chatbots like ChatGPT are utterly broken or useless for these languages. If you ask ChatGPT in Tigrinya or Amharic the simplest and most frequently asked questions, it gives you gibberish, a mix of Tigrinya and Amharic, or even made-up words.
How is your work relevant to the boom in conversational artificial intelligence tools, such as ChatGPT, in terms of building original training data sets for low-resource languages? If your native language is one of these African languages, if you have the technical know-how around machine learning, and you care about your community and the kind of problems they want to solve, that unique advantage and connection to the community can carry you further. So at Lesan, we don’t believe that you can create just one model that solves these problems. If you put it on its face and compare it with smaller startups, like Lesan or Ghana NLP, the quality is actually low. Google and Facebook overhype that they have built one single giant model to solve machine translation for hundreds of languages. What can smaller shops like Lesan bring to the table?
As an automated translation service, you’re competing with the biggest and most advanced tech companies in the world. This interview has been edited for length and clarity.
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The startup’s use of offline print resources to create a new benchmark data set for languages from the Horn of Africa has been key to its success. Founded in 2019, Lesan has launched translation tools for Amharic and Tigrinya, which it says outperform Google Translate in terms of quality. Asmelash Teka Hadgu is the co-founder and chief technology officer of Lesan, a Berlin-based startup developing machine translation products for Ethiopian languages.
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