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Understanding Reinforcement Learning and Multi-Agent Systems: A Beginner’s Guide to MARL (Part 1)

Towards AI

Photo by Hyundai Motor Group on Unsplash When we learn from labeled data, we call it supervised learning. When we learn by grouping similar items, we call it clustering. When we learn by observing rewards or gains, we call it reinforcement learning.

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Big Data – Das Versprechen wurde eingelöst

Data Science Blog

Big Data tauchte als Buzzword meiner Recherche nach erstmals um das Jahr 2011 relevant in den Medien auf. GPT-3 wurde mit mehr als 100 Milliarden Wörter trainiert, das parametrisierte Machine Learning Modell selbst wiegt 800 GB (quasi nur die Neuronen!) Neben Supervised Learning kam auch Reinforcement Learning zum Einsatz.

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What Is a Transformer Model?

Hacker News

Transformers made self-supervised learning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.

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What Is ChatGPT Doing … and Why Does It Work?

Hacker News

And in fact the big breakthrough in “deep learning” that occurred around 2011 was associated with the discovery that in some sense it can be easier to do (at least approximate) minimization when there are lots of weights involved than when there are fairly few.