🐐🎮 염소 시뮬레이터 3 인공지능을 위한 초현실적인 놀이터

인간 플레이 데이터를 활용하여, 구글은 최신 챗봇에 사용된 기술과 유사하게 새로운 게임에 학습하고 적응할 수 있는 AI 에이전트를 만들었습니다.

“`html

AI from Google DeepMind Masters ‘Goat Simulator 3

Have you ever played a video game where you take domesticated ungulates (that’s a fancy word for goats) on absurdly implausible adventures, sometimes involving jetpacks? Well, that’s precisely what Goat Simulator 3 is all about. 🐐✈️ But hold on to your keyboards, because this seemingly bizarre game has recently become the unexpected stage for a groundbreaking development in artificial intelligence.

Google DeepMind, the AI powerhouse behind projects like AlphaGo, has unveiled its latest creation: an AI program called SIMA (Scalable Instructable Multiworld Agent). SIMA has the remarkable ability to learn how to complete tasks not only in Goat Simulator 3 but also in a variety of other games. What’s truly impressive is that SIMA can adapt what it has learned from playing one game to excel at another game it has never encountered before. It’s like a gamer who becomes a master at different games by unlocking shared concepts and applying skills learned from previous experiences. 🚀👾

SIMA builds upon recent advancements in AI, leveraging large language models that have produced astonishingly capable chatbots such as OpenAI’s ChatGPT. But instead of just conversing or generating images, SIMA can take control of computers and perform complex commands. This is the direction pursued by both independent AI enthusiasts and big tech companies like Google DeepMind, who are heavily investing in harnessing the true potential of AI. 🤖💥

The Power of Shared Concepts

One of the most fascinating aspects of SIMA’s capabilities is its knack for leveraging shared concepts in different games. By tapping into these shared elements, this AI program learns essential skills and becomes better at accomplishing tasks. Frederic Besse, a research engineer at Google DeepMind, describes SIMA as “greater than the sum of its parts,” highlighting its ability to extract valuable knowledge from one game and apply it successfully in another. It’s like a gamer who becomes a superhero capable of using their accumulated skills from multiple games to conquer any challenge they face. 🎮👑

• PS5의 최신 업데이트로 향상된 오디오와 새로운 기능이 제공됩니다.
• 애플 비전 프로에 VLC 미디어 플레이어를 선보이는 환상적인 개발! 🍎🎥
• 😄 레기온 고 이동 중인 게이머를 위한 게임 콘솔

Game Training: From Atari to Goat Simulator 3

Google DeepMind has a rich history in training AI through gaming. Back in 2013, before its acquisition by Google, DeepMind demonstrated the power of reinforcement learning by training an algorithm to play classic Atari video games. This groundbreaking technique involved providing the algorithm with positive and negative feedback to improve its performance over time. The result? Computers that could excel at games like Pong and Breakout, paving the way for even more remarkable achievements. 🎮💪

In 2016, DeepMind’s AlphaGo program shocked the world by defeating a world champion Go player. Go, an ancient board game that requires sophisticated and instinctive skills, was considered a challenge beyond the reach of AI. But AlphaGo proved everyone wrong, showcasing the immense potential of AI in areas that demand deep strategic thinking and intuition. 🧠♟️

Now, with SIMA as its latest triumph, DeepMind has taken gaming AI to a whole new level. Collaborating with various game studios, the DeepMind team collected data from humans playing ten different games with 3D environments, including popular titles like No Man’s Sky, Teardown, Hydroneer, and Satisfactory. This data, combined with the processing power of language models, empowered SIMA to understand and respond to human commands in games. Through extensive human evaluation and fine-tuning, SIMA can now perform over 600 actions, from exploration to combat to tool usage. It’s like giving an AI player an arsenal of gaming skills to dominate any virtual world it encounters. 🔥🎮

SIMA’s Future: From Games to Real-World Applications

While SIMA’s current focus remains within gaming environments, the potential for broader applications is palpable. Imagine having AI agents like SIMA working alongside you in games, joining forces with you and your friends. The possibilities are immense. However, before AI agents can seamlessly transition to real-world applications, reliability is paramount. The DeepMind team acknowledges this and is actively working on making SIMA and similar agents more robust and dependable. After all, if AI agents can flawlessly perform complex tasks in the controlled world of video games, there’s no limit to what they could achieve in our everyday lives. 💼🌍

So, next time you find yourself embarking on a ludicrous goat-filled adventure in Goat Simulator 3, remember that you’re not just having fun; you’re also witnessing the incredible progress of artificial intelligence. It’s like playing with a cutting-edge tool that showcases the ever-expanding capabilities of AI while providing us with a glimpse into a future where unimaginable feats become commonplace. 🐐🎮🚀

“`

🤔 독자 질문에 답하다:

1. Q: SIMA는 이전에 경험하지 않은 게임에서 어떻게 뛌어난 성적을 올릴까요?
   • A: SIMA는 게임 사이에 공유되는 개념을 활용하여 학습한 기술과 전략을 다른 게임으로 전이할 수 있습니다. 이것은 패턴을 인식하고 이전에 습득한 지식을 적용함으로써 다른 게임에서 전문가가 되는 게이머처럼 작동합니다.
2. Q: SIMA는 비디오 게임 외의 영역에서 사용될 수 있을까요?
   • A: 현재 SIMA는 게임 환경에 초점을 맞추고 있지만, 현실 세계 응용 가능성은 엄청납니다. Google DeepMind와 다른 AI 연구자들은 사무실 업무부터 실제 일상 활동까지 다양한 영역에서 복잡한 작업을 수행할 수 있는 SIMA와 같은 AI 에이전트를 더 신뢰성 있고 능력이 있는 것으로 만들기 위해 적극적으로 활동하고 있습니다.
3. Q: 게임에서 SIMA와 같은 AI 에이전트에 대한 윤리적 고려 사항이 있을까요?
   • A: Google DeepMind는 윤리적 지침과 일치하여 SIMA와 같은 AI 에이전트의 교육 및 개발에 폭력적 행동을 특징으로 하는 게임을 의도적으로 피합니다. 목표는 AI 기술의 책임감 있고 윤리적인 사용을 보장하는 것입니다.

🌌 참고 자료:

1. “Luminary Clouds Simulator Taps GPUs to Help Speed Up Product Design” – TechCrunch 기사.
2. “Meta is Going for Artificial General Intelligence, Says Zuckerberg. Here’s Why It Matters” – ENBLE 기사.
3. “Best Google Pixel Deals: Save on Pixel 8, Buds, and Watch” – Digital Trends 기사.
4. “The New York Times Wants OpenAI and Microsoft to Pay for Training Data” – TechCrunch 기사.
5. “Quickly Access Recently Viewed Files and Folders in macOS” – ENBLE 기사.

이 흥미로운 뉴스를 단독으로 유지하지 마세요! 이 기사를 친구들과 동료 게이머들과 공유하세요. 📲💻 그리고 아래 댓글에서 우리에게 알려주세요: 가까운 미래에 상상할 수 있는 AI의 다른 환상적인 사용은 무엇인가요? 활기찬 토론을 시작합시다! 🗣️🤖✨

• ai
• algorithms
• artificial intelligence
• ChatGPT
• deep learning
• DeepMind
• google
• machine learning
• OpenAI