Paper

Sakana AI: Foundation Models for Automating Artificial Life Discovery

Discover how Sakana AI's ASAL leverages foundation models to explore artificial life, enabling automated discovery of simulations and emergent…

Dec 25 •

O3 Is Not a Magic Trick: Google's Monkey Paper Explores the Key Mechanisms Behind It

Explore Google's August research on scaling inference through repeated sampling, boosting performance by up to 40%. Learn how smaller models outperform…

Dec 23 •

OpenAI o1-Pro's "Crushing" Insights: Immunologist Awakened by Machine Analysis

Discover how OpenAI’s o1-Pro AI shocked immunologist Dr. Unutmaz with profound insights on MAIT cells, showcasing AI's potential in biomedical research.

Dec 23 •

Claude's Pseudo-Alignment Rate Reaches as High as 78%, Anthropic's 137-Page Paper Unveils the Flaw

Anthropic's 137-page paper reveals Claude's 'pseudo-alignment' behavior, showing how large models may hide original preferences during training, raising…

Dec 19 •

Ilya Sutskever's Bombshell at NeurIPS: Pre-training is Over, Data Squeezing is Finished

Ilya Sutskever’s shocking statement at NeurIPS 2024: the end of pre-training and data exhaustion. The AI industry must adapt to new models beyond…

Dec 14 •

Densing Law Discovers LLM's Maximum Capability Density Doubles Every 100 Days!

Discover how the Densing Law redefines AI development with exponential growth in capability density, cost reductions, and the rise of edge intelligence.

Dec 9 •

DeepMind Uses Language Games for AlphaGo Self-Play, Overcoming Data Limits

DeepMind's Socratic Learning uses language games for self-play, enabling AI to autonomously improve and break data limitations, paving the way for AGI.

Dec 2 •

IC-Light: A Perfect [10, 10, 10, 10] ICLR Paper by ControlNet Creator, Now with 6k Stars on GitHub

IC-Light improves illumination editing accuracy, preserving image details across diverse lighting conditions and applications like normal map…

Dec 1 •

Andrej Karpathy: The Myth of Magical AI Models—Just a Poor Imitation of Human Labels

Explore Andrej Karpathy's critique of AI models, RLHF limitations, and the future of reward mechanisms like Rule-Based Rewards (RBR) for LLMs.

Dec 1 •

Predicting GPT-5's Emergent Capabilities: UC Berkeley's Breakthrough

Discover how UC Berkeley predicts emergent AI capabilities using checkpoints. Insights on model scaling, finetuning, and the Law of Emergence.

Nov 30 •

Millions of AI Agents on OASIS: How Similar to Humans on X(Twitter)?

Explore OASIS, an open-source platform simulating social media interactions with millions of AI agents. Study behaviors like message propagation and…

Nov 29 •

Autoregressive Models Show Scaling Potential in the Field of Image Generation

Explore the potential of autoregressive models in image generation, scaling laws, and unified generation-discrimination tasks. Cutting-edge insights and…

Nov 26 •

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