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La veille de la cybersécurité

#artificialintelligence

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.


AI can now play Minecraft just as well as you - here's why that matters

#artificialintelligence

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 Introduces a Neural Network That Can Play 'Minecraft'

#artificialintelligence

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.


AI learns how to play Minecraft by watching videos - AI News

#artificialintelligence

Open AI has trained a neural network to play Minecraft by Video PreTraining (VPT) on a massive unlabeled video dataset of human Minecraft play, while using just a small amount of labeled contractor data. With a bit of fine-tuning, the AI research and deployment company is confident that its model can learn to craft diamond tools, a task that usually takes proficient humans over 20 minutes (24,000 actions). Its model uses the native human interface of keypresses and mouse movements, making it quite general, and represents a step towards general computer-using agents. A spokesperson for the Microsoft-backed firm said: "The internet contains an enormous amount of publicly available videos that we can learn from. You can watch a person make a gorgeous presentation, a digital artist draw a beautiful sunset, and a Minecraft player build an intricate house. However, these videos only provide a record of what happened but not precisely how it was achieved, i.e. you will not know the exact sequence of mouse movements and keys pressed. "If we would like to build large-scale foundation models in these domains as we've done in language with GPT, this lack of action labels poses a new challenge not present in the language domain, where "action labels" are simply the next words in a sentence." In order to utilise the wealth of unlabeled video data available on the internet, Open AI introduces a novel, yet simple, semi-supervised imitation learning method: Video PreTraining (VPT). The team begin by gathering a small dataset from contractors where it records not only their video, but also the actions they took, which in its case are keypresses and mouse movements. With this data the company can train an inverse dynamics model (IDM), which predicts the action being taken at each step in the video. Importantly, the IDM can use past and future information to guess the action at each step. The spokesperson added: "This task is much easier and thus requires far less data than the behavioral cloning task of predicting actions given past video frames only, which requires inferring what the person wants to do and how to accomplish it.


OpenAI's New AI Learned to Play Minecraft by Watching 70,000 Hours of YouTube

#artificialintelligence

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.


OpenAI's New AI Learned to Play Minecraft by Watching 70,000 Hours of YouTube

#artificialintelligence

In 2020, OpenAI's machine learning algorithm GPT-3 blew people away when, after ingesting billions of words scraped from the internet, …


AI can now play Minecraft just as well as you - here's why that matters

#artificialintelligence

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 spent $160,000 on Upwork for Minecraft gamers to train a neural net

ZDNet

The computer program achieved the feat in ten minutes, half the time it would take a proficient human player to do it. How important might it be to master the "diamond tool" in Minecraft? Important enough to spend $160,000, according to OpenAI, the artificial intelligence startup. That is the amount of money that a team at OpenAI spent to hire players of Minecraft on the online job listings platform Upwork to submit videos of themselves playing the game. In a paper unveiled this week, "Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos," OpenAI researchers Bowen Baker and team break ground in the use of large datasets to train a neural network to mimic human keystrokes to solve different tasks in the video game.


Can Machine Learning Translate Ancient Egyptian Texts?

#artificialintelligence

I have long been intrigued by archaeogaming--an academic discipline that explores the fusion of archaeological objects, methods, and characters into video games. So I was thrilled when the video game company Ubisoft released Assassin's Creed: Origins, set in Egypt during Cleopatra's reign. The designers collaborated with Egyptologists to ensure everything from the architecture to the hieroglyphics created an accurate, immersive world. Unexpectedly, this partnership inspired a machine-learning spinoff that changed the course of my early career. While working with Egyptologists, the game developers learned that translating and interpreting ancient hieroglyphic texts is time-consuming, and the process has changed little in the last century.


Microsoft's Code-Writing AI Points to the Future of Computers

#artificialintelligence

Microsoft just showed how artificial intelligence could find its way into many software applications--by writing code on the fly. At the Microsoft Build developer conference today, the company's chief technology officer, Kevin Scott, demonstrated an AI helper for the game Minecraft. The non-player character within the game is powered by the same machine learning technology Microsoft has been testing for auto-generating software code. The feat hints at how recent advances in AI could change personal computing in years to come by replacing interfaces that you tap, type, and click to navigate into interfaces that you simply have a conversation with. The Minecraft agent responds appropriately to typed commands by converting them into working code behind the scenes using the software API for the game.