Hub AI research

Artificial Intelligence is already part of everyday life. Since the ImageNet moment in 2012, when Deep Learning proved its great utility in combination with a lot of computing power and gigantic amounts of data, only about ten years have passed – yet there has been more progress than in half a century before.

Still, many questions remain: Will Deep Learning remain the gold standard of AI development? What are the performance limits of large AI systems? Do we need symbolic systems? What technology will lead to artificial general intelligence? Finally, what actually is intelligence, anyway?

We explore these topics and more in our Artificial Intelligence Research Content Hub.

AI research

OpenAI says GPT-5 shows 30 percent less political bias than previous models

AI research

OpenAI outperforms humans and Google at the world's top collegiate programming contest

AI research
Update

AI coding can make developers slower even if they feel faster

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AI research
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Dynamics Lab has launched Mirage 2, the latest version of its generative game world engine. With Mirage 2, users can upload their own images - like sketches or photos - and turn them into interactive game worlds. The engine also lets players change the game in real time by typing in commands. Worlds can be saved and shared. While Mirage 2 makes clear technical gains over its predecessor, it still struggles with precise controls and visual stability. In both areas, Genie 3 from Google DeepMind is far ahead, but Genie 3 isn't available yet and likely requires much more computing power. A Mirage 2 demo is available online.

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AI research
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Meta has released DINOv3, a new AI model for universal image processing that doesn't require labeled data. Trained with self-supervised learning on 1.7 billion images and built with 7 billion parameters, DINOv3 handles a wide range of image tasks and domains with little or no adaptation. This makes it especially useful in fields with limited annotated data, such as satellite imagery. Meta says the model performs well on challenging benchmarks that previously needed specialized systems.

Video: Meta

According to Meta's benchmarks, v3 outperforms v2, though the improvement is less pronounced than the jump from v1 to v2. Meta has released the pre-trained models in several variants, along with adapters and the training and evaluation code under the DINOv3 license, which allows for commercial use, all available on GitHub.

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AI and society
Comment

OpenAI and Microsoft call AGI pointless, then make it the linchpin of billion-dollar deals

AI in practice

Google leans on token metrics, not revenue, adding to bubble talk about AI growth

AI and society

OpenAI restructures under new foundation, Microsoft takes 27 percent stake

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