AI and Data and Stuff

Image generated using AI (Stable Diffusion)   Since I discovered the GPT-3-based chatGPT , I have become addicted to it and have so far resisted the urge to fill this blog with chatGPT posts but my resistance seems to wane with every successive interaction so I can't say how long I will be able to resist. I have interacted extensively with the model and, like many other people , have been completely blown away, especially when I remember what AI-generated content looked like few years ago when I used GPT-2 to generate a weird version of the 12 days of Christmas .  I have even attempted to hack or sidestep some of the baked in rules and content safeguards of chatGPT and so far my results have been a mix of successes and failures but my greatest win was when I finally got it to actually write code for various computer viruses and trojans (shhh don't tell anyone). This article, though, is not about hacking chatGPT but about another subject with also tickles my fancy: games. I wa...

Natural language processing (or NLP) is a branch of machine learning that deals with the languages spoken by humans. This branch includes things like automatic translation, text and speech generation amongst other things. The thing about most of the current NLP systems is that they require humongous amounts of sample text, speech and/or translations and other samples of the languages in focus to be able to be trained to perform these tasks of translation, generation etc This need for large sample data is the biggest challenge for many African languages because a majority of these languages have very limited amounts of such samples - too little to successfully train an NLP system. Many of these so called "low-resource" languages both in Africa and other parts of the world have been virtually overshadowed by the more popular languages like English, French, German, Spanish, Mandarin etc which have massive amounts of sample language data already available for use in trai...

Here is an exercise for you: Can you spot the fake face (or faces) among the six images below? By fake I mean generated (in other words, the person does not exist and has never existed). See the faces in larger format below (click on the image for an even higher resolution):              If your answer was one (or more) out of A, B, C, D, E or F then you are right. Actually ALL the faces are fake and the people in the images do not exist, have never existed and most likely never will. The faces were "imagined" and created (in high definition) by an Artificial Intelligence algorithm. Specifically it was created by a type of Deep Learning algorithm/model known as a GAN which is short for Generative Adversarial Network. What is a GAN? In concept, a GAN is a combination of two separate neural networks that compete against each other to ultimately produce "fake" data that is as close as possible to real sa...