singularity

Today, while I was writing a casual AI application I suddenly realized I was using a machine learning model to help me code it. For a while I have been testing out an autocomplete tool called Tabnine which is based on the GPT-2 model trained with millions of source files from Github hosted open source projects.

While the application I was writing won't probably change the world it still made me think. Was I using the AI to write the application, or was the AI using me to write a better version of itself.

Self driving cars is s hard problem. Not least due to their reception and popular opinions against them. There is a lot of discussion and debating how safe or competent and adaptable they need to be to be generally accepted.

Ever since the advent of computers people have waited for those machines to start thinking. To become equals to us. Despite the incredible advancements made since and how much it can feel like they do, a real thinking machine is still far away. Or is it even possible in the end.

Today's state of the art machine learning models might yield impressive results. But at the core, there is no real intelligence in play. It's just layers upon layers of clever programming. The end results are mere manifestations of what we have told the machine to do.

Generative adversarial networks are a machine learning method where two neural networks are competing against each other. The generative network tries to create an output based on the initial data and the discriminator network tries to detect if given input is real or generated by it's adversary. Repeating this process while feeding the results back to the network keeps improving both networks and in turn improving the quality of generated content.