And so we need to probably look further down and understand that. Its changing. I speak to International Investors particularly here in the u. S. , and the Success Stories are speaking for themselves. Strive has a very successful business in zimbabwe. We are running a very successful business. If youd invested in my company two years ago, it was worth about 1. 6 billion, today its worth about 6 billion two years later. Investors are happy to come. My shares are, happily, oversubscribed. And people are going past the african risk thing. Absolutely. Thank you, sir. We are active in some 17 african countries. 17 . Yes. We have people, we have offices, we have boots on the ground. Were africans. We dont see a lot of these problems. Maybe thats not to say theyre not there, but i think the way we look at it is is it easier for me to invest in knew year ya that nigeria than russia . Knew year ya any day, any day of the week. [laughter] and, you know, its a perspective. Its a perspective on ri
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Chris Yang | unsplash
Five years ago, Microsoft released its infamous bot, Tay, into the world of Twitter. Tay used a machine learning algorithm to learn from interactions on the platform, to then echo novel responses back based on that learning. Within short time it became obvious that Twitter is not ideal ground for unsupervised learning. It turns out that the people who scream the loudest arenât always the best teachers.
Without a filtering mechanism, Tay started parroting back all kinds of racist, bigoted and misogynistic tweets. So naturally a question arose: how can we expect AI to learn on its own by engaging the world without letting the world corrupt it with its worst demons?