Algorology Newsletter #1 ⭐

Artificial Universe; Music Created by Robots; 3D Worlds and Machine-Brain interfaces

🏰 “The hope is that Universe can drive the development of machines with general intelligence — the same kind of flexible brain power that humans have”, which is why researchers at OpenAI lab backed by Elon Musk created Artificial Universe where computers learn to use apps/games like humans do.

🎄 We are not far from a future where all entertainment content we consume is generated by… machines. The ones that know how Christmas song should sound, which lyrics it should have and the ones that can sing it for us, like this algorithm called Neural Karaoke did with a Christmas song generated from just seeing a picture of a decorated tree.

🤖 All major computer vision techniques are based on transforming real world into 2D pixels but seems like those days are over and we are finally getting something much more complex, the artificial intelligence capable of truly feeling and understanding 3D world around us.

⛄ Despite plenty of hype and rushing venture capital a leading artificial intelligence expert Andrew Ng says hardware advances will keep AI breakthroughs coming.

“There are multiple experiments I’d love to run if only we had a 10-x increase in performance,” Ng adds. For instance, he says, instead of having various different image-processing algorithms, greater computer power might make it possible to build a single algorithm capable of doing all sorts of image-related tasks.

🤕 “It’s not artificial intelligence I’m worried about, it’s human stupidity.” says Bryan Johnson that is tackling the notion of Human Intelligence which can be interpreted as a technological merge of human brains and artificial intelligence. Because who doesn’t want to become superhuman from the Limitless TV show? Though the societal risks coming from this technology are even more dangerous, since it’s always better to dream of an AI taking over the world rather than having a bunch of psychos armed with brain tech causing world terror.

📚 “Where should machines go to learn?” — good question and article by Auren Hoffman that discusses challenges we may face if we would like to create the one and only library of all human knowledge and related data on it. Covers good points on data privacy and why eventually access to data will be democratized.

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