In 2020, OpenAI's machine learning algorithm GPT-3 blew people away when, after ingesting billions of words scraped from the internet, it began spitting out well-crafted sentences. This year, DALL-E 2, a cousin of GPT-3 trained on text and images, caused a similar stir online when it began whipping up surreal images of astronauts riding horses and, more recently, crafting weird, photorealistic faces of people that don't exist. Now, the company says its latest AI has learned to play Minecraft after watching some 70,000 hours of video showing people playing the game on YouTube. Compared to numerous prior Minecraft algorithms which operate in much simpler "sandbox" versions of the game, the new AI plays in the same environment as humans, using standard keyboard-and-mouse commands. In a blog post and preprint detailing the work, the OpenAI team say that, out of the box, the algorithm learned basic skills, like chopping down trees, making planks, and building crafting tables.

Experts at OpenAI have trained a neural network to play Minecraft to an equally high standard as human players. The neural network was trained on 70,000 hours of miscellaneous in-game footage, supplemented with a small database of videos in which contractors performed specific in-game tasks, with the keyboard and mouse inputs also recorded. After fine-tuning, OpenAI found the model was able to perform all manner of complex skills, from swimming to hunting for animals and consuming their meat. It also grasped the "pillar jump", a move whereby the player places a block of material below themselves mid-jump in order to gain elevation. Perhaps most impressive, the AI was able to craft diamond tools (requiring a long string of actions to be executed in sequence), which OpenAI described as an "unprecedented" achievement for a computer agent.

OpenAI has developed a neural network that can play Minecraft like humans. The Artificial Intelligence (AI) model was trained over 70,000 hours of miscellaneous in-game footage, along with a small database of videos in which specific in-game tasks were performed. Keyboard and mouse inputs are also recorded. OpenAI fine-tuned the AI, and now, it is skillful as a human-it can swim, hunt for animals, and eat. The AI can also do the pillar jump, where a player places a block of material below themselves in mid-air to gain more elevation.

Not all of us have the talent to whip up a piece of art at a moment's notice. But algorithms using machine learning are learning how to create "AI art" based on text prompts--and you can use them, too. Algorithms like DALL-E (and eventually, DALL-E 2), DALL-E mini, Craiyon, Midjourney, and more are learning how to take publicly available art and learn what makes them art. Or, at least, digest the various elements and style of a photo or artistic work and recombine them into something new. Sure, you can argue whether or not they're, in fact, "art," but the creations are unique, original, and compelling. Simply put, AI art uses a text prompt: something specific like McDonalds at the bottom of the sea, for example, or a bit more generic like the castle of time -- the prompt that generated the art at the top of this story.

��OpenAI�̌����`�[���́A�l�Ԃ��v���C����Minecraft�i�}�C���N���t�g�j�̉f�����畡�G�ȓ�����w�K���郂�f�����J�������B�w�K�������f���́A�n�������l�ł�20���ȏォ����_�C�������h�c�[���̍쐬��10�����x�Ő��������A���̗L�������������B

That's not to say that Skynet is going to take place soon, but its development has gone leaps and bounds. And it could get even better from here, especially with OpenAI leading the charge. For those of you unfamiliar, this organization is one of the biggest out there when it comes to artificial intelligence. Its research laboratory has been doing great things over the years, attracting a number of high-end partners. These include Elon Musk, Sam Altman, and Microsoft, who recently invested a billion dollars into them.

This article was featured in One Story to Read Today, a newsletter in which our editors recommend a single must-read from The Atlantic, Monday through Friday. Though everybody complains about Twitter, no one can deny that it has brought some amazing phrases into our lives--things we can't imagine having read in any other place, or at any other time in history. Near the top of any list of the most treasured sentence fragments posted there, the now-defunct account @Horse_ebooks would have several entries. Twitter users still recirculate strange classics like "(using fingers to indicate triangular shape) SMELL SMELL SMELL GOOD NEW NEW NEW slice drink MATCH SPARKLER (thrown in air) STARS STARS STARS." But the best-known @Horse_ebooks tweet, posted 10 years ago today, was astounding in its clarity and salience.

Craiyon, formerly DALL-E mini, is an AI model that can draw images from any text prompt!

In 2020, OpenAI's machine learning algorithm GPT-3 blew people away when, after ingesting billions of words scraped from the internet, it began spitting out well-crafted sentences. This year, DALL-E 2, a cousin of GPT-3 trained on text and images, caused a similar stir online when it began whipping up surreal images of astronauts riding horses and, more recently, crafting weird, photorealistic faces of people that don't exist. Now, the company says its latest AI has learned to play Minecraft after watching some 70,000 hours of video showing people playing the game on YouTube. Compared to numerous prior Minecraft algorithms which operate in much simpler "sandbox" versions of the game, the new AI plays in the same environment as humans, using standard keyboard-and-mouse commands. In a blog post and preprint detailing the work, the OpenAI team say that, out of the box, the algorithm learned basic skills, like chopping down trees, making planks, and building crafting tables.

On June 6, Hugging Face, a company that hosts open source artificial intelligence projects, saw traffic to an AI image-generation tool called DALL-E Mini skyrocket. The outwardly simple app, which generates nine images in response to any typed text prompt, was launched nearly a year ago by an independent developer. But after some recent improvements and a few viral tweets, its ability to crudely sketch all manner of surreal, hilarious, and even nightmarish visions suddenly became meme magic. As more people created and shared DALL-E Mini images on Twitter and Reddit, and more new users arrived, Hugging Face saw its servers overwhelmed with traffic. "Our engineers didn't sleep for the first night," says Clément Delangue, CEO of Hugging Face, on a video call from his home in Miami.